Frequently Asked Questions

Canvas apps are our default for task-focused, UX-rich scenarios and mobile or offline use. Model-driven apps fit process-heavy, data-model-centric applications, especially when integrated with Dynamics 365. Many estates use both, and we help you pick the right pattern per use case.

A focused business app typically goes live in 6–10 weeks. Larger line-of-business solutions replacing legacy systems usually run 3–6 months and are often split into multiple releases to deliver value sooner.

When requirements demand a highly customised UX at scale, very high concurrent user counts, complex real-time processing or deep non-Microsoft ecosystem integration. We are happy to say so and recommend a different approach when that is the right answer.

We always use solutions, environment separation (dev / test / prod) and pipelines – either Power Platform Pipelines or Azure DevOps / GitHub Actions – so apps move between environments in a controlled, auditable way.

Yes. We use Dataverse, Microsoft connectors, custom connectors, Azure API Management and Azure integration services to connect Power Apps to CRM, ERP, line-of-business APIs and SaaS platforms.

Yes. Synapx-as-a-Service includes ongoing support, enhancement and Microsoft update management for Power Apps, so your solutions keep pace with platform changes and business needs.

For most enterprise clients we now recommend Fabric capacities, which include Power BI Premium features and unlock Direct Lake over OneLake. PPU remains useful for individual power users. We run a short licensing review as part of every Power BI engagement.

A first certified semantic model with a suite of dashboards typically ships in 6–10 weeks. Larger estate migrations from Tableau, Cognos or SSRS usually run 3–6 months, often in parallel with a Fabric platform build.

Both, but our sweet spot is building the governed foundation – semantic models, workspaces, ALM, adoption – on which the business can then produce many reports safely. We are happy to deliver point reports where that is genuinely what is needed.

We certify semantic models, add clear measure descriptions, synonyms and formatting, tidy relationships and apply RLS, and standardise terminology. Copilot quality is directly proportional to model quality, so the work pays off immediately.

Yes. We run structured migrations from Tableau, Cognos, Qlik, SSRS and legacy SSAS onto Power BI / Fabric, rationalising reports and rebuilding models rather than doing a 1:1 copy that preserves old problems.

Yes. Synapx-as-a-Service provides ongoing Power BI operations – capacity optimisation, dataset refresh management, workspace governance, model enhancement and user support.

Business Process Automation is the use of technology to execute recurring business processes – approvals, onboarding, data entry, case management, customer service – with minimal human intervention. Synapx delivers BPA using Microsoft Power Automate, Copilot Studio agents, AI Builder, and Azure Logic Apps, often integrated with existing Microsoft 365, Dynamics 365, and line-of-business systems.

Cloud flows run on Microsoft infrastructure and trigger on events or schedules, using connectors to modern APIs. Desktop flows run on a user machine or unattended agent and drive UI-based (RPA) automation for legacy systems that lack APIs. Synapx uses both, often together, to automate end-to-end processes.

Finance (invoice approvals, PO processing, reconciliation), HR (onboarding, leave, timesheet reminders), operations (case triage, order management, SLA tracking), customer service (ticket routing, chatbot deflection), and knowledge-worker tasks (document generation, data extraction from PDFs/emails using AI Builder).

Across our engagements, typical outcomes are 40–80% reduction in manual effort on the automated process, payback within 6–12 months, and measurable error-rate and cycle-time reductions. We baseline metrics before build and measure impact after go-live.

We establish a Power Platform Centre of Excellence covering environment strategy, DLP policies, solution ALM, monitoring with the CoE Starter Kit, and maker enablement – so citizen-developed automations coexist safely with IT-owned mission-critical flows.

Power Pages shines when a portal needs to surface Dataverse or Dynamics 365 data, when you need enterprise identity, and when time-to-market matters. For highly bespoke, high-traffic consumer experiences, a custom build in Azure may still be the right choice.

A first portal typically goes live in 6–10 weeks. More complex portals integrating with multiple systems or supporting hundreds of thousands of users usually run 3–6 months.

Power Pages supports Entra ID, Entra External ID (B2C), Azure AD B2B, SAML and OAuth providers, plus local accounts. We design the identity model based on your audience – customers, partners, citizens, members – and integrate SSO where appropriate.

Portals enforce row-level and column-level permissions via Dataverse table permissions and web roles. We add network controls, WAF, rate limiting and penetration testing for public-facing portals handling sensitive data.

Yes, when built carefully. We design to WCAG 2.1 AA by default, test with real assistive technology and include accessibility acceptance criteria in every release – which matters particularly for public-sector clients.

Yes. Synapx-as-a-Service provides ongoing operations, content updates, security patching, enhancement and performance monitoring for Power Pages portals.

A cross-functional capability that gives your organisation safe, productive use of Power Apps, Power Automate, Copilot Studio and Power BI. It combines environment and DLP strategy, ALM, analytics, enablement and governance so makers can build confidently without creating risk.

It is a strong starting point for most clients. We deploy and customise it, but we always pair it with policies, processes and people. The tooling on its own does not govern the platform – the operating model around it does.

A baseline CoE – environment strategy, DLP, CoE Starter Kit, ALM patterns and maker enablement – typically takes 8–12 weeks to stand up. Embedding it across a large enterprise is a 6–12 month journey we can lead or support.

Usually a small core team (2–5 people) combining platform admin, governance, enablement and data protection skills, reporting into IT or the CDO. Many clients engage Synapx to run the CoE for them while internal capability grows.

We extend CoE policies to cover Copilot Studio agents and AI Builder – DLP, environment placement, approval workflows, content moderation and monitoring – so generative AI inside the Power Platform follows the same guardrails as the rest of the estate.

Yes. Synapx-as-a-Service includes managed CoE operations, admin, pipeline management, monitoring and maker support, with UK-based specialists who already understand your environment.

Either. We run Microsoft “in a Day” sessions (App, Dashboard, Automation, Agent, Power Pages) as standard courses, and we build fully bespoke curricula that use your own data, systems and processes where appropriate.

Both. Most clients opt for a blend – an in-person bootcamp or kick-off followed by remote sessions, office hours and recorded content your teams can revisit.

Yes. We deliver structured preparation for PL-100, PL-200, PL-400, PL-500, PL-600, PL-900 and related AI / Azure certifications, with hands-on labs and timed mock exams.

Senior Synapx consultants, including Microsoft MVPs and Microsoft Certified Trainers, who spend most of their time actually delivering Power Platform projects. Training is grounded in real, recent delivery rather than slideware.

Single-topic “in a Day” sessions run 1 day. Bespoke maker bootcamps run 3–5 days. Longer academies (e.g., a citizen-developer cohort programme) typically run 8–12 weeks with ongoing mentoring after that.

Yes, and we strongly recommend it. Training has much more impact when your Power Platform environments, governance and paved roads are already in place, so makers can apply what they learn safely.

A typical Synapx Data Strategy engagement runs 4–8 weeks, depending on the size of the organisation and the number of business units involved. By week 6 most clients have an executive-ready roadmap, prioritised use cases and a quantified business case.

No. We are platform-agnostic on data strategy and regularly assess Azure, Fabric, Databricks, Snowflake and hybrid estates. That said, as a Microsoft Solutions Partner for Data & AI we can accelerate delivery significantly when Fabric, Synapse or Azure is the chosen direction.

We pair strategy consultants with hands-on Microsoft engineers from day one. That means the roadmap we deliver has been pressure-tested against what we can actually build – and we can mobilise the same team to execute the first sprint immediately after sign-off.

Typically a senior business sponsor (CFO, COO or CDO), a data / IT lead, and 4–6 representatives from the business areas in scope. We facilitate the workshops and do most of the heavy analysis between sessions, so the time commitment is light.

Yes. Most Synapx data strategy engagements transition straight into a Fabric, Databricks, Power BI or governance build phase delivered by the same Synapx team – no awkward hand-off, no second discovery.

A board-ready data strategy and roadmap, a target architecture aligned to Microsoft best practice, a prioritised backlog of use cases with business cases, a governance and operating model, and a delivery plan for the next 6–12 months with clear owners and KPIs.

We only build models we expect to put into production. Every engagement starts with the business decision and the operational workflow that will consume the model – so the output is a running, monitored system, not a slide deck.

Primarily Microsoft Fabric Data Science, Azure Machine Learning and Databricks, with MLflow for experiment tracking. We use Python, PySpark, and common libraries (scikit-learn, XGBoost, LightGBM, PyTorch) alongside Azure OpenAI for generative workloads.

A focused use case typically takes 8–12 weeks end-to-end. Simple models on clean data can be quicker; heavily regulated use cases with model risk sign-off take longer.

Explainability and bias assessment are built in from day one using SHAP, LIME and Microsoft Responsible AI tooling. We document datasheets, model cards and validation results so compliance and audit teams can review the model with confidence.

A business sponsor, a domain expert, and a data or IT point of contact. Our team handles data science, engineering and MLOps; yours provides context and the decision rights that make the model useful.

Yes. We offer ongoing model monitoring and retraining through Synapx-as-a-Service, tracking drift, performance and data quality so your models stay accurate as the business evolves.

No. We regularly design hybrid estates where Databricks handles heavy engineering and ML, and Fabric surfaces curated data to Power BI, Copilot and business users. The right split depends on workloads, team skills and commercial model.

A governed foundation – networking, identity, OneLake / catalogue, CI/CD and a first domain – typically takes 8–12 weeks. Full migration off a legacy warehouse usually runs 6–12 months depending on complexity and change appetite.

Yes. We implement Fabric Real-Time Intelligence, Event Streams, KQL databases, or Databricks structured streaming – choosing the pattern that best fits latency, volume and downstream consumption.

We baseline capacity, tag every resource, monitor Fabric capacity units and Databricks DBUs, and tune workloads continuously. Clients on Synapx-as-a-Service typically see 20–40% cost reduction in the first six months.

Yes. We run data platform programmes for financial services, healthcare and public sector clients with private networking, customer-managed keys, Purview classification, audit logging and evidence trails for regulators.

Yes. Synapx-as-a-Service provides 24/7 platform operations, enhancement and cost optimisation by the same UK-based team that built it, so knowledge is retained and improvements continue.

Microsoft Fabric is a unified SaaS analytics platform that brings together data engineering, data warehousing, data science, real-time intelligence, Power BI, and Data Activator on a single lake-centric foundation (OneLake). It replaces the need to stitch together separate Azure data services.

Yes. Synapx is a Fabric Featured Partner, Fabric Databases Featured Partner, and Real-Time Intelligence Featured Partner – one of approximately 30 Microsoft partners globally holding all three Fabric designations.

We start with a readiness assessment covering workloads, data estate, and licensing. We then deliver a reference Lakehouse or Warehouse in 4–8 weeks using our Fabric accelerator, establish governance (Purview, domains, workspaces), migrate or ingest source data, and build Power BI semantic models on top.

Often yes – but not always. We run a Fabric vs Databricks vs Synapse comparison as part of every assessment. Fabric is strongest where clients want consolidated licensing, self-service Power BI integration, and reduced operational overhead. We are comfortable running Fabric alongside Databricks where appropriate.

We monitor Fabric capacity units, implement autoscale and pause policies where supported, tune Spark and SQL workloads, and right-size capacities per workspace. Our Synapx-as-a-Service managed offering includes ongoing Fabric cost optimisation.

Yes. We hold Microsoft Solutions Partner designations for Data & AI and Azure Infrastructure, and our engineers are certified on Databricks (Data Engineer, ML, Platform Admin). We deliver Databricks primarily on Azure, with experience on AWS where required.

Databricks is our typical recommendation for heavy data engineering, large Spark workloads and production ML. Fabric is stronger for Power BI-centric estates and consolidated licensing. We are one of the few partners that delivers both, often side-by-side in the same estate.

We use cluster policies, job compute, spot instances, autoscaling, photon where it pays back, and Unity Catalogue usage analytics to understand spend by workload. Clients moving off legacy platforms typically see 30–50% total cost reduction.

Yes. Unity Catalogue provides fine-grained access controls, row / column security, lineage and audit logging. We pair it with Azure policies, private networking and customer-managed keys for financial services, healthcare and public sector clients.

A governed Lakehouse foundation with the first workload live typically takes 8–12 weeks. Full migrations from Hadoop, Synapse or legacy warehouses usually run 4–9 months depending on pipeline count and complexity.

Yes. Synapx-as-a-Service covers platform operations, cluster and cost optimisation, Unity Catalogue administration and ongoing enhancement, with UK-based engineers who already know your estate.

Both are excellent and we deliver on both. Fabric tends to win when Power BI is central, when you want a SaaS experience with consolidated licensing, and when real-time intelligence matters. Databricks tends to win for heavy ML, very large Spark workloads and multi-cloud estates. Many clients run both.

A first domain – e.g. finance, sales or operations – typically takes 8–14 weeks from discovery to production, including governance and CI/CD. Subsequent domains are faster as the platform and patterns are reused.

Yes. Every pipeline we build is in source control, code-reviewed, automatically tested and deployed through CI/CD. We use Git-integrated Fabric, Azure DevOps / GitHub Actions, and treat data products with the same rigour as application code.

Yes. We run lift-shift-optimise programmes that move legacy ETL into Fabric Data Factory or Azure Data Factory, re-platforming only where it delivers measurable value, so you avoid an expensive big-bang rewrite.

We implement data contracts at source, automated tests in pipelines (Great Expectations, dbt tests, Fabric data quality), and observability via Purview and Monitor. SLAs, runbooks and on-call rotations make reliability operational, not aspirational.

Yes. Synapx-as-a-Service provides ongoing platform operations, cost optimisation, enhancement and on-call support, with UK-based engineers who already know your estate.

An accelerator is a pre-built, opinionated solution package – typically a combination of Fabric / Azure infrastructure-as-code, reference data models, Power BI templates, Purview policies and DevOps pipelines. We tailor the accelerator to your tenant rather than starting from a blank page.

Most accelerator engagements deliver a production-ready environment in 3–6 weeks. The first business workload typically goes live within 6–10 weeks, depending on data readiness and approval cycles.

No. Everything we deploy uses standard Microsoft services, open formats (Delta, Parquet) and documented patterns. Your team owns the code and the environment, and can extend or replace any component without vendor lock-in.

Yes. Our accelerators are designed with financial services, healthcare and public sector controls in mind – including Purview classification, private networking, customer-managed keys and audit logging. We regularly harden them further to meet specific regulator requirements.

An Azure tenant with sufficient privilege to deploy resources, a named data owner, and access to the first few source systems. We handle the rest – infrastructure, configuration, governance and knowledge transfer.

No. Accelerators execute a strategy faster; they are not a substitute for one. If you do not yet have a clear roadmap, we usually run a short Data Strategy engagement alongside the first accelerator deployment.

For most organisations, yes. Teams Phone supports PSTN calling via Calling Plans, Operator Connect or Direct Routing, plus call queues, auto-attendants and analytics. We run a structured voice assessment before recommending an approach.

A typical Teams Phone deployment for a mid-sized organisation takes 8–14 weeks including voice design, number porting, pilot and full rollout. Larger multi-country rollouts usually run 4–8 months.

We implement naming conventions, provisioning templates, guest access controls, sensitivity labels, expiry policies and periodic access reviews, typically via the Teams admin centre, Entra ID governance and custom automation.

Yes. We deliver Teams apps using the Microsoft 365 Agents SDK (formerly Teams Toolkit), Power Apps, Power Virtual Agents and Copilot Studio, depending on the use case and existing skill base.

Yes. We configure Teams for frontline use with Shifts, Walkie Talkie, Tasks and Approvals, plus appropriate F-series licensing, shared device mode and simplified app layouts on mobile.

Yes. Synapx-as-a-Service provides managed Teams operations, including voice administration, number management, Rooms device monitoring, governance reporting and end-user enablement.

We focus on SharePoint Online and Microsoft 365, and we help clients migrate off on-premises SharePoint 2013, 2016 and 2019. Where hybrid is required in the short term we can support it, but the target is always cloud.

A modern intranet typically goes live in 8–14 weeks including design, build, governance and initial content migration. Larger enterprise rollouts with many business units usually run 4–6 months.

Yes. SharePoint readiness is one of the most important Copilot prerequisites. We run permissions audits, sensitivity labelling, retention and content cleanup so Copilot answers are accurate and do not expose data the wrong people should not see.

We run discovery, quality assessment and a remediation plan before any migration. We use Microsoft’s Migration Manager and third-party tools (ShareGate, Quest) as appropriate, and migrate in waves so the business is never blocked.

Yes. We configure Entra external ID (B2B), sensitivity labels, Conditional Access and DLP so external sharing is both safe and practical – rather than blanket-disabled or blanket-allowed.

Yes. Synapx-as-a-Service provides managed SharePoint and Microsoft 365 operations, including governance, site lifecycle, permissions reviews, Copilot readiness and continuous enhancement.

Usually yes, over time. We recommend co-management as the stepping stone – shifting workloads from ConfigMgr to Intune in a controlled sequence rather than a risky big-bang migration – and most clients retire ConfigMgr within 12–24 months.

Yes. Intune provides full MDM for iOS, iPadOS, Android and macOS, and app protection policies for personal devices under BYOD. We regularly deliver mixed estates with consistent compliance policy across platforms.

A baseline design and pilot typically takes 6–10 weeks. Full rollout across a mid-sized organisation (2,000–10,000 endpoints) usually runs 3–6 months, paced by change management rather than technology.

Intune is the device half of Microsoft Zero Trust. We combine Intune compliance with Entra Conditional Access so access to Microsoft 365, Azure and line-of-business apps is granted only to healthy, known devices.

Yes, with Endpoint Privilege Management. We run a discovery, define elevation rules per app and role, and roll out progressively so users keep what they legitimately need while risk drops meaningfully.

Yes. Synapx-as-a-Service provides managed modern endpoint operations, including policy management, patching, app packaging, compliance reporting and end-user support tooling.

Custom intranets, SPFx web parts and extensions, Teams apps, document-driven workflows, external portals and integrations between SharePoint and line-of-business systems. Our focus is solutions that genuinely fit how your organisation works rather than generic templates.

Yes. We use SharePoint Framework (SPFx), Microsoft Graph, Microsoft 365 development APIs and PnP patterns, with source control, ALM and automated deployment. Everything is upgrade-safe and aligned to Microsoft’s modern roadmap.

A first solution typically goes live in 6–10 weeks. Larger intranet builds or integration programmes usually run 3–6 months depending on scope, integrations and change management needs.

Not when built correctly. We design extensions and content structures that Copilot can understand, and we tidy permissions, labels and metadata so Copilot answers are accurate and safe.

Yes. We regularly integrate SharePoint with Dynamics 365, Dataverse, line-of-business APIs, document AI and third-party SaaS using Graph, Power Automate and Azure integration services.

Yes. Synapx-as-a-Service provides ongoing enhancement, support and Microsoft 365 lifecycle management for bespoke SharePoint solutions, so they keep working as the platform evolves.

A typical Synapx AI Strategy engagement runs 4–8 weeks. By the end you have an executive-ready AI vision, a scored and sequenced use-case portfolio, a responsible AI operating model and a funded delivery plan for the next 6–12 months.

Our AI strategists work side-by-side with hands-on Microsoft engineers, data scientists and governance specialists. The roadmap we deliver has been pressure-tested against what can actually be built – and we can mobilise delivery the week after sign-off.

Often yes. Most organisations we see have pockets of Copilot and point AI solutions but no coherent plan for value, risk or capability. An AI strategy makes sure those investments add up to something, and that the next wave (agents, custom models, automation) is sequenced deliberately.

A senior sponsor (CEO, COO, CDO or CIO), a data / IT lead, a risk or legal contact, and 4–8 business leaders from the areas in scope. We facilitate the workshops and do the heavy analysis between sessions, so the time commitment is light.

Yes, as a core part of every strategy. We map your ambitions against the EU AI Act, ICO guidance and sector-specific regulators (FCA, PRA, NHS DSPT, etc.) and embed responsible AI controls into the operating model from day one.

Yes. Most AI strategy engagements transition directly into delivery – Copilot rollout, agentic solutions on Copilot Studio, bespoke ML on Azure AI Foundry, or data foundation work in Fabric or Databricks – delivered by the same Synapx team.

Data, identity, networking, security, governance, FinOps, skills and operating model. The output is a scored assessment against a Microsoft-aligned readiness framework, a prioritised remediation plan and an order-of-magnitude cost estimate for the AI platform build.

Typically 3–5 weeks, including stakeholder workshops, technical deep-dives and an executive read-out. We keep the business time commitment light – most analysis happens behind the scenes.

A production-ready Azure AI Foundry platform with guardrails, CI/CD and first workloads typically takes 8–14 weeks to build. Subsequent workloads land in days rather than weeks once the foundation is in place.

Yes. We design for a mix of Copilot Studio, Azure OpenAI, open-source models and bespoke ML so teams can pick the right tool for each use case within a single governed environment.

Through workload tagging, capacity quotas, model routing (e.g., to cheaper models where appropriate), token budgeting and continuous FinOps monitoring. Clients moving from ad-hoc OpenAI usage to a managed platform typically see 30–50% cost reduction.

Yes. We design AI platforms with private endpoints, customer-managed keys, Purview integration, Entra identity and audit logging so they meet financial services, healthcare and public sector requirements.

Primarily Azure Machine Learning, Databricks (MLflow, Model Serving, Feature Store) and Microsoft Fabric Data Science, integrated with Azure DevOps or GitHub Actions. The choice depends on where your data lives and the rest of your Microsoft estate.

A minimum viable MLOps platform – pipelines for training, deployment, monitoring and CI/CD – typically takes 8–12 weeks. Onboarding subsequent models is much faster, often a couple of weeks once the pattern is in place.

Yes. We often inherit notebook-based or hand-deployed models and migrate them into a governed MLOps pipeline without a full rewrite, delivering most of the value of a greenfield build at a fraction of the cost.

We monitor data drift, concept drift, performance against ground truth, infrastructure health and (for GenAI) prompt / response evaluation. Alerts feed into the same observability stack your platform team already uses.

Yes – we often call it LLMOps. The principles are the same: versioned prompts, evaluation datasets, regression tests, safe rollout patterns and production monitoring for quality, cost and safety.

Yes. Synapx-as-a-Service provides ongoing model operations, retraining, monitoring and enhancement by the same UK-based engineers who built your platform.

We align to the EU AI Act, NIST AI Risk Management Framework, ISO/IEC 42001 and Microsoft Responsible AI Standard. For regulated sectors we also layer in FCA, PRA, ICO, NHS DSPT and sector-specific model risk expectations.

A working framework – policies, risk register, review board, model documentation templates and monitoring – typically takes 6–10 weeks to establish. Embedding it across a large enterprise is a 6–12 month programme we can lead or support.

No. We regularly review and remediate AI systems built by other partners, SaaS vendors or in-house teams. An independent assessment is often the fastest way to understand real AI risk in your organisation.

We use SHAP, LIME, fairness metrics and Microsoft Responsible AI dashboards during model build and in production. Every model we ship has a model card, documented test results and a human-in-the-loop pattern where appropriate.

Yes. We routinely deliver Copilot readiness programmes covering SharePoint / OneDrive permissions hygiene, Purview sensitivity labels, DLP, retention, prompt and response logging, and user training – so Copilot rollouts are both fast and audit-friendly.

It varies. We usually help clients set up a cross-functional AI council led by the CDO, CTO, CISO or Chief Risk Officer, with legal, HR and business representation. We stay involved as advisors as the framework matures.

Microsoft 365 Copilot is the ready-made assistant inside Word, Excel, Teams and Outlook, licensed per user. Copilot Studio is the low-code platform for building your own agents over your data, with actions and governance. Most organisations get the best results treating them as two workstreams: adoption for the first, agent delivery for the second.

Copilot Studio is our default when you need a conversational agent over documents, data and business actions, especially in Teams or the web. Azure AI Foundry is the right choice when you need a bespoke application, deep UX control, complex orchestration or specialist model deployment. We deliver both and often combine them.

A focused Copilot Studio agent typically takes 4–8 weeks from kick-off to production, including governance and change management. More complex agentic automations that take action in several systems usually run 8–16 weeks.

Yes. Copilot Studio connects natively to Microsoft 365, Dataverse and Power Platform, and we use custom connectors or the Azure AI Foundry SDK to integrate with CRM, ERP, ticketing, line-of-business APIs and legacy systems where needed.

Permissions first. Copilot answers from whatever a user can already access, so oversharing in SharePoint and OneDrive becomes visible fast. Our readiness work remediates permissions, applies Purview sensitivity labels and DLP, and cleans up the content Copilot will draw on, before the licences go live.

No. Copilot Studio is licensed separately, per message capacity or per user, and agents can be deployed to Teams, websites and other channels without M365 Copilot licences. The two work well together, but neither depends on the other.

Software engineering where AI agents do real work: writing code, generating tests, reviewing changes and producing documentation, with engineers directing and reviewing rather than typing every line. Done well it compounds; done as a licence drop it becomes expensive autocomplete. The difference is adoption discipline, which is what we deliver.

Often both, for different jobs. GitHub Copilot excels at in-editor assistance inside the Microsoft and GitHub estate most teams already run. Claude Code is an agentic tool that takes on whole tasks across a codebase. We assess your stack, security posture and ways of working, then recommend a mix with costs modelled honestly. We work with both, and with Claude as a registered Anthropic partner.

It is as safe as your review discipline. Our rule is simple: nothing agent-written merges unreviewed. We set up review gates, secrets and data boundaries for agent contexts, dependency and licence scanning, and audit trails of what agents changed, so speed scales without eroding the controls your security team relies on.

We baseline before anything changes: cycle time, review turnaround, defect escape rate and delivery cadence for the pilot squad. Rollout decisions are then made against evidence from your own teams rather than vendor benchmarks, and you get numbers you can defend to the board.

Almost certainly. Coding agents are strongest in mainstream languages and frameworks, and still useful in legacy estates, where their ability to read and explain unfamiliar code is often the biggest win. The assessment at the start of every engagement confirms where they will pay off first in your codebase.

Bootcamps run two to five days and finish with your engineers shipping agent-built changes in your own environment. A typical adoption programme, from baseline through pilot squad to organisation-wide rollout, runs one to two quarters depending on team count.

Several AI agents collaborating on one problem: typically a planner decomposing the work, workers executing steps in parallel and a reviewer challenging the output before anything reaches a person or a customer. The pattern suits workflows too heavy for a single agent, and it demands proper orchestration, tracing and human approval gates.

We ground agents in your content using retrieval over curated SharePoint, Fabric or bespoke vector stores, constrain answers with prompt engineering and tool use, log every interaction, and add human-in-the-loop patterns for sensitive actions.

Yes, when designed well. We use private networking, Purview sensitivity labels, Entra identity, data residency configuration and prompt / response logging. We have delivered agents in financial services, healthcare and public sector.

We baseline the target workflow before build (volumes, handling time, deflection, CSAT) and measure impact after go-live. Typical outcomes include 40–70% deflection on routine queries, 20–50% handling-time reduction and measurable user satisfaction gains.

The framework follows the workload. Azure AI Foundry Agent Service when a managed, Azure-native runtime with enterprise governance is the right call; LangChain and LangGraph when the workflow needs full control of the reasoning graph; CrewAI when role-based agent crews fit the problem and speed matters. We build on all three, so the recommendation is not shaped by what we happen to sell.

Azure OpenAI models inside Azure AI Foundry for estates that need Azure-native controls, and Claude, as a registered Anthropic partner, where complex multi-step reasoning and tool use earn their keep. Model choice is evaluated per use case against quality, cost and governance requirements, not decided by habit.

Fractional (e.g., 1–3 days a week), embedded (full-time within your team for a fixed term), project-based (outcome-focused delivery), and fully managed services. Most clients blend approaches as their AI programme matures.

For senior AI roles we typically put forward named candidates within 48 hours and mobilise within 1–2 weeks. For fully managed services, the transition usually runs 4–6 weeks including knowledge transfer.

Named, permanent Synapx engineers – not anonymous rate cards or off-shore body-shopping. Every AI-as-a-Service engagement is staffed with people whose CVs and certifications you review up front.

On a fully-loaded basis, equivalent senior AI capability via Synapx is typically 20–50% cheaper than hiring permanently, once recruitment, benefits, bench risk and the ability to flex are accounted for. It is especially efficient for capability you do not need year-round.

Yes. Our Synapx-as-a-Service offering provides ongoing operations, retraining, monitoring and enhancement of AI solutions – whether we originally built them or inherited them.

Yes. All IP built on your engagement is yours, and we actively transfer knowledge to your team through pair working, documentation and training. The goal is to leave you stronger, not more dependent.

The five WAF pillars: reliability, security, cost optimisation, operational excellence and performance efficiency. We apply them to a specific workload or a broader Azure estate, combining Microsoft tooling with hands-on architectural review.

A single-workload review typically runs 2–4 weeks. A broader estate-wide review across dozens of workloads usually takes 4–8 weeks. You get a prioritised remediation plan at the end in either case.

Often, yes. Microsoft offers Azure migration and innovation funds that can partly offset WAR engagements, especially when coupled with a modernisation or migration plan. We help clients apply for and use these where applicable.

Most reviews surface 20–40% cost-reduction opportunities across reservations, right-sizing, storage tiering and idle resources, along with meaningful reliability and security improvements that are harder to quantify but often more valuable.

No. We regularly review estates built by other partners or internal teams. An independent Well-Architected perspective is often the most credible way to understand the real state of a complex Azure footprint.

Yes. We can deliver or co-deliver the remediation with your team, and measure the improvement with a follow-up review – so the recommendations translate into real business outcomes, not shelved slides.

Yes. Synapx holds the Microsoft Solutions Partner designation for Security, alongside Cyber Essentials and Cyber Essentials Plus certification. Our security engineers are certified on Defender, Sentinel, Entra and Purview.

An initial posture assessment and prioritised remediation plan typically takes 3–5 weeks. Implementing the top-priority controls and reaching a defensible baseline usually runs another 6–12 weeks after that.

Yes. We offer managed detection and response on top of Microsoft Sentinel and Defender XDR, with 24/7 coverage, threat hunting, incident response and continuous posture management.

We prioritise the highest-risk attack paths first – privileged identity, legacy auth, device compliance, sensitive data – rather than trying to boil the ocean. We deliver Zero Trust in iterative releases tied to measurable risk reduction.

Yes. We include AI-specific controls in every engagement: Copilot permissions hygiene, Purview classification, prompt / response logging, content filters, DLP, and tenant configuration for safe generative AI use.

Treating your internal cloud, data and AI infrastructure as a product with paved roads, templates and self-service – so product and data teams get what they need quickly, without giving up on security, reliability or cost control.

A useful MVP with a handful of paved roads and real consumers typically takes 10–16 weeks. Mature internal developer platforms are a long-running product investment rather than a one-off project.

No. Many clients start with a small core platform team (4–6 people) and scale as consumption grows. Synapx can run the platform team on your behalf, or work alongside yours to uplift capability.

Paved roads are secure by default. Templates bake in networking, identity, encryption, policy-as-code and monitoring, so product teams get safety without having to become security experts themselves.

Yes. We extend the same paved-road thinking to Fabric, Databricks, Azure ML and Azure AI Foundry so data and AI teams benefit from the same developer experience and guardrails as application teams.

Yes. Synapx-as-a-Service covers ongoing platform operations, enhancement, SLO management and consumer support – leaving you free to focus on what runs on the platform rather than the platform itself.

A landing zone and first-wave migration usually takes 8–16 weeks. Full data centre exits for mid-market and enterprise clients typically run 9–18 months, depending on application estate size and modernisation appetite.

Yes, as our default. We use the CAF and Azure Well-Architected Framework to structure strategy, plan, ready, adopt, govern and manage phases, while tailoring the detail to your organisation’s maturity and risk appetite.

We implement FinOps from day one – tagging, cost alerting, rightsizing, reserved instances / savings plans, autoscaling, and workload-specific tuning. Clients moving from un-optimised estates typically see 20–40% reduction in the first six months.

Yes. We design Azure-first but pragmatically support hybrid scenarios with Azure Arc, ExpressRoute, on-prem connectivity and integrations with AWS or GCP where they already exist.

Yes. Synapx-as-a-Service delivers managed Azure operations, patching, monitoring, cost optimisation and enhancement, with UK-based engineers who already know your environment.

Clients moving from un-optimised Azure estates typically see a 20–40% reduction in the first six months, with a further 5–15% from ongoing optimisation. AI and generative workloads often deliver 30–50% savings through model routing, quotas, and prompt optimisation.

No. We embed FinOps practices into migrations, landing zones, and platform builds from day one so spend is governed before it grows. Engaging early avoids expensive remediation later.

FinOps is about value, not just cost. We focus on eliminating waste and right-sizing without restricting teams, using policy-as-code and automated guardrails so engineers retain autonomy within agreed budgets.

Yes. We govern Azure OpenAI, Azure AI Foundry, GPU compute, and third-party model spend with quotas, capacity reservations, model routing, token budgeting, and continuous monitoring tailored to AI consumption patterns.

Yes. Our practice is built around the FinOps Foundation principles, capabilities, and personas, combined with Microsoft Cost Management, Azure Advisor, and Azure Carbon Optimisation tooling.

Yes. Synapx-as-a-Service delivers ongoing FinOps – tagging hygiene, optimisation backlog, reservation management, anomaly response, and monthly executive reporting – with savings tracked against agreed KPIs.

In sequence: quotas and budgets per team first, so a runaway workload cannot become an incident. Then model routing, so the cheap model handles the cheap work. Then prompt optimisation and caching, which cut tokens before they are bought. Most estates find the routing step alone is the biggest single saving.

Only once demand is real and steady. PTUs trade commitment for a discount and predictable latency, which is valuable for production workloads with proven volume, and expensive for anything still finding its usage pattern. We model your actual token history before recommending a commitment, the same way we treat reservations for compute.

Both. We routinely deliver on Azure DevOps, GitHub Enterprise and hybrid setups, and we help clients choose the right long-term target – or migrate between the two where it makes sense.

A typical engagement runs 6–12 weeks to establish a golden-path pipeline, IaC pattern and security baseline, with one or two workloads migrated. Wider rollout across an engineering organisation is usually a 3–9 month programme we can lead or support.

We use the DORA metrics – deployment frequency, lead time for changes, change failure rate and mean time to restore – alongside developer experience and security posture metrics. We baseline them before build and track improvement transparently.

Yes. We integrate SAST, SCA, secret scanning, IaC scanning (Checkov, tfsec, PSRule), container scanning and policy-as-code (OPA, Azure Policy) so every change is evaluated automatically against your security standards.

Yes. We regularly migrate Jenkins, TeamCity, Bamboo, Octopus Deploy and classic Azure Pipelines estates onto modern YAML pipelines or GitHub Actions, re-using as much existing configuration as possible to minimise disruption.

Yes. Synapx-as-a-Service includes ongoing platform engineering – pipeline maintenance, runner / agent operations, security updates and developer support – so your teams keep moving while core plumbing is looked after.

Azure AI Foundry is Microsoft’s unified platform for building, evaluating and operating AI applications and agents. It combines Azure OpenAI, the model catalogue, AI Search, Agents, prompt flow, evaluations and responsible AI tooling inside a single, enterprise-grade environment.

Copilot Studio is the fast path for conversational agents over documents, data and business actions, especially in Teams. Azure AI Foundry is the right choice when you need a bespoke application, deep UX and orchestration control, custom model hosting or specialist evaluation. We deliver and combine both.

A production-ready Foundry environment with the first workload live typically takes 8–12 weeks. Additional workloads ship much faster once the platform pattern is in place.

We deploy Foundry with private endpoints, customer-managed keys, Purview integration, Entra identity and prompt / response logging, and pick regional model deployments to meet data residency requirements – including UK and EU sovereignty needs.

Yes. We design Foundry with hubs, projects, RBAC and capacity quotas so product, data and research teams share the platform without treading on one another, with clear chargeback and FinOps controls.

Yes. Synapx-as-a-Service provides ongoing Foundry operations, model lifecycle management, cost optimisation and enhancement, delivered by the UK-based engineers who built your environment.

It genuinely depends on your workloads, your team and how you prefer to pay for compute. Fabric usually wins for BI-centric estates that live in Microsoft 365; Databricks usually wins for engineering-heavy and data science workloads. Plenty of our clients run both, mirrored through OneLake so nothing is stored twice. We run a short platform decision workshop that settles the question against your actual data rather than a slide deck.

Yes. We run dedicated migration engagements from SQL Server, Teradata, Snowflake, Redshift and on-premises warehouses into Fabric or Databricks. We assess readiness, map workloads, re-platform the ETL and cut over with minimal disruption to business reporting.

Governance is designed in, not bolted on. We implement Microsoft Purview for cataloguing, lineage and access policy, build automated data quality testing into pipelines, and set up ownership models so every dataset has a named steward. For Power BI we certify semantic models, so the business knows exactly which numbers to trust.

Synapx is a registered Anthropic partner. In practice that means we build production agentic systems on Claude, including with the Anthropic Agent SDK, alongside our Microsoft work on Copilot and Azure OpenAI. We choose the model per workload, not per allegiance.

Designing systems where an AI agent plans a task, calls tools and APIs, checks its own output and escalates to a human at defined points. We build the orchestration, the tool layer, the evaluation harness and the guardrails, then run the system in production. It suits multi-step, document-heavy or investigation-style work where a single prompt cannot cope.

Yes, and we would encourage you to demand this of any AI partner. Our agentic upskilling covers engineering bootcamps, official Microsoft Agent in a Day workshops, AI-assisted engineering adoption and embedded mentoring, all designed so your second agent gets built without us.

Yes, by design. Deep expertise in one cloud beats a shallow spread across three. Our engineers hold the Microsoft Solutions Partner designations for Infrastructure (Azure) and Digital & App Innovation (Azure), and everything we build, from landing zones to pipelines, assumes Azure. If you are committed to AWS or GCP, we are the wrong partner, and we will say so.

No, and we would rather tell you that on the first call. We are not a network operations centre. What we provide is engineering-led CloudOps: senior engineers who monitor, patch, improve and cost-optimise your estate through code, with incident response during working hours and automation doing the night shift.

A production-ready landing zone, with identity, networking, policy and cost management all defined as code, typically takes 4–6 weeks. Workload migrations then run in waves on top of it. If a partner quotes you two days for this, ask what happens at your first security review.

It starts with a cost review that usually pays for itself: tagging, rightsizing, waste and commitment coverage. Quick wins land in the first month; the rest becomes an operating rhythm of budgets, anomaly alerts and a monthly conversation between finance and engineering. See our FinOps page for the full picture.

Often, yes. Microsoft runs funding programmes for qualified migration and modernisation projects, and as a Microsoft Solutions Partner we can scope, apply for and deliver against them. Eligibility depends on your agreement and workloads, so we check early in discovery.

Yes. Alongside VM estates we replatform applications onto App Service, AKS and Azure SQL, and refactor the systems that justify it. Every workload gets an explicit rehost, replatform or refactor decision during assessment, because the cheapest migration and the cheapest five years of running costs are rarely the same option.

That is the normal arrangement. We design and build with your team in the repository from day one, and enablement is part of the scope. The goal is that your engineers can run and evolve the platform confidently once we step back.

Anything that shapes the day-to-day Microsoft 365 experience: SharePoint intranets and document management, Teams collaboration and telephony, Intune endpoint management, and bespoke Microsoft 365 development. Most engagements start with one pain point, usually the intranet or device management, and grow from there.

Usually, yes, because the cause is usually the same: the intranet was built around the org chart instead of around what people need to find. We rebuild the information architecture around tasks and search, brand it properly, give every page an owner, and measure engagement afterwards rather than assuming it.

Yes. We deploy Teams Phone as a replacement for legacy PBX systems, including number porting, call queues, auto attendants and compliant call recording where regulation requires it. One client for chat, meetings and calls, managed alongside the rest of Microsoft 365 rather than as a separate system with a separate bill.

We design and implement Intune for corporate and personal devices: zero-touch enrolment with Windows Autopilot, compliance policies, application management and endpoint privilege management. Your IT team gets one console, and your users get devices that work on day one.

Adoption is scoped into every engagement: champion networks, role-based training, communication plans and usage analytics. A digital workplace nobody uses is a cost, not an asset, so we measure success in engagement data rather than delivery milestones.

Yes. We hold the Microsoft Solutions Partner designation for Modern Work, alongside five other Solutions Partner designations across the Microsoft Cloud, including Security.

Yes. File-share migrations into SharePoint and Teams come with information architecture, permission mapping and a clean-up of the content nobody has opened for years. Legacy intranet replacements follow our adoption-first rebuild approach, and we can usually preserve the URLs that matter.

Copilot amplifies whatever workplace you have, including the mess. Well-governed SharePoint, sensible permissions and tidy Teams make Copilot dramatically more useful and considerably safer. We prepare the workplace first, then roll Copilot out with role-based enablement; our AI practice takes over for agents and extensibility.

Yes. Business Support covers the day-to-day running, and Synapx-as-a-Service keeps improvement moving month on month, delivered by the team that built your environment.

Licensing is where Power Platform budgets most often go wrong, so we run licensing reviews as standard: matching per-user against per-app plans, checking Dataverse capacity, and rationalising duplicate solutions. The Fidelis Partnership saved over £60,000 a year through exactly this work.

Frequently. We inherit estates with hundreds of ungoverned apps and flows built by enthusiastic makers. A short assessment maps what exists, what is business-critical and what can be retired, then a Centre of Excellence puts guardrails around the rest. No blame attached: sprawl is what success looks like before governance arrives.

Most start with a discovery call and a short assessment, then move into fixed-scope delivery or an agile pod depending on the work. For ongoing needs, Synapx-as-a-Service provides retained capacity across every practice. You will always know who is working on your account and what they did last week.

Start from the pain, not the technology. Reporting chaos points at Data. Manual processes point at Power Platform. An Azure bill nobody can explain points at Cloud. AI ambition without a plan points at an AI use-case workshop. A discovery call settles it quickly, and there is no obligation attached.

Deliberately. The cloud team lays the landing zone the data platform runs on; the data team builds the governed estate that grounds Copilot and custom AI; Power Platform puts the results into apps and workflows people use every day. One partner across the stack means no integration finger-pointing.

Headquartered at 2 Leman Street in London, with delivery hubs in Bengaluru, Hyderabad and Gurugram. Client-facing consulting is UK-led, and engineering capacity scales through the India hubs under the same standards and tooling.

Mostly UK mid-market and enterprise, across financial services, insurance, construction and property, and energy, among others. The common thread is organisations that have outgrown spreadsheets and point solutions, and want the Microsoft platform they already pay for to start earning its keep.

Thirty minutes with a consultant, not a salesperson. You describe the problem; we ask the awkward questions about data, licensing and appetite; you leave with a recommended route and a rough shape of effort. If the honest answer is that you do not need us yet, that is the answer you will get.

Yes, and we usually do. Most estates already involve an MSP for infrastructure, sometimes an agency, occasionally another consultancy. We slot in around them, keep the interfaces clean and documented, and reserve our opinions for where the work genuinely overlaps.

Business Support keeps an existing Microsoft estate healthy: incidents, monitoring, optimisation and releases. Managed RPA designs, runs and maintains your automation estate end to end. Synapx-as-a-Service is retained senior capacity across every practice, for organisations that want one flexible team building and improving continuously. They combine well, and many clients use two of the three.

All three run on a monthly subscription against reserved hours or agreed scope, so costs sit in operational expenditure and stay predictable. There are no mobilisation fees and no surprise invoices. Hours flex between disciplines within the month, and we review utilisation with you so you are never paying for capacity that is not working.

Service levels are agreed per contract based on the criticality of what we support, covering response times, escalation paths and reporting. A customer-facing portal outage and a cosmetic report bug get different clocks, and the severity definitions are written down before go-live so there is no debate mid-incident. As a Microsoft Solutions Partner we can also escalate directly into Microsoft when a platform issue is genuinely theirs.

Engagements roll monthly after an initial onboarding period. We keep the lock-in short deliberately: a 98% client retention rate is a better bond than a long contract.

Named Synapx consultants and engineers, the same people who deliver our project work, not a separate support tier. You will know who is on your account, and continuity is part of the design so knowledge of your environment compounds over time.

Yes, within the agreed model. Many clients use retained hours for a mix of support, small enhancements and new builds. Larger initiatives can be scoped as projects alongside, with the retained team providing the continuity.

Most clients do. A common pattern is Business Support for the estate with Synapx-as-a-Service capacity layered on for improvement work, or Managed RPA running alongside either. One account team, one monthly review, one view of the whole relationship.

Monthly service reports covering work delivered, hours used, incidents and their root causes, and what is planned next, reviewed in a call where you can challenge anything. Retention is earned in that meeting, not in the contract.

A structured offboarding if you want one: documentation refreshed, access handed back, knowledge-transfer sessions with whoever takes over. Exit is deliberately easy, which is precisely why most clients stay.

The Microsoft estate you already run: Power Platform apps and flows, Power BI, Dataverse, SharePoint and the surrounding Azure services. Incidents and requests, proactive monitoring, release and update management, licensing optimisation and small enhancements, delivered by Microsoft-certified engineers who learn your environment properly.

Microsoft supports its platform; we support your solutions built on it. When something breaks, the question is rarely "is Azure up" and usually "why does this app, flow or report misbehave", which needs people who know your customisations. Where an issue genuinely is a platform fault, our Solutions Partner status gives us a direct escalation route into Microsoft.

Yes, frequently. We start with a short assessment of the estate, document what exists, stabilise anything fragile, then take on the run responsibility. No blame culture about the previous builder; we would rather fix than critique.

Yes, licensing reviews are part of the service: plan mix, capacity, and rationalising duplicate solutions. The Fidelis Partnership saved over £60,000 a year in licensing costs through our governance and licensing work.

A structured onboarding: access and security setup, estate documentation, monitoring configuration and a stabilisation period, typically two to four weeks depending on estate size. After that you get a steady operating rhythm with monthly service reporting.

Response and resolution targets are agreed per severity level and per client, because a broken expense app and a broken trading report do not deserve the same clock. Performance against them is part of the monthly service review.

After onboarding, agreements roll monthly. The onboarding period exists because documenting and stabilising an estate properly takes a few weeks; after that, we would rather keep you through service than through terms.

The full lifecycle: process discovery and ROI modelling, bot design and build on Power Automate cloud and desktop flows, deployment, then ongoing monitoring, error handling, maintenance and improvement. You get the outcomes of an automation estate without having to build the team that runs one.

Automation estates need supervision, because the systems they touch keep changing. Our monitoring picks up failures, retries what is safely retryable, and queues what needs human attention with full context. Recurring failure patterns get engineered out, not just restarted.

High-volume, rules-based work with structured inputs: invoice processing, data entry between systems, report distribution, onboarding checklists, reconciliations. During discovery we score candidate processes on volume, stability and complexity, and we will tell you which ones are not worth automating.

Automating well-chosen processes typically removes 40–80% of the manual effort involved. Discovery includes ROI modelling per process, so the business case is explicit before we build anything.

Power Automate is usually the right engine because it already sits inside your Microsoft licensing, and we optimise the plan mix as part of the service. Where you have existing investments in other RPA tools, we will be honest about whether to keep or migrate them.

Yes. Everything is built in solutions with proper ALM, documented, and owned by you. Some clients graduate to running their own estate with our training; most keep the managed service, because supervision is the part they never wanted to staff.

Yes. We assess the existing estate, document and stabilise the fragile parts, then bring the bots under our monitoring and governance. It is one of the most common ways clients arrive.

Discovery typically takes two to three weeks, and a first well-chosen automation usually reaches production within four to eight weeks of starting. We deliberately pick an early win with visible value, because nothing builds appetite for automation like a process that stops being anyone's job. The pace after that is set by the roadmap we agree together each quarter.

A retained engagement that reserves capacity from our senior consultants and engineers across Data, AI, Power Platform, Cloud and Modern Work. One monthly subscription, one team that knows your environment, and priorities reviewed with you every month.

Anything we do: new builds, enhancements, support, advisory, training. Hours flex across disciplines within the month. Most clients run a mix of steady improvement and responsive support, with the occasional spike for a bigger initiative.

A fixed monthly fee based on reserved capacity, agreed in advance. No mobilisation costs and no surprise invoices, with utilisation reporting so you can see exactly where the hours went.

Capacity flexes month to month within agreed bounds, and the contract rolls monthly after onboarding. If your needs drop, you scale down without a negotiation. In practice, 98% of clients stay.

A discovery session to map your estate and goals, a proposed capacity and priority plan, then onboarding: access, tooling and a first-month backlog. Most clients are in a steady rhythm within four to six weeks.

Within agreed bounds, yes. Utilisation is reviewed monthly and capacity can be rebalanced across disciplines or carried into the following month, so a quiet period becomes headroom rather than waste. You should never feel you are paying for a bench that is not working, and the utilisation report makes that easy to check.

Yes. Many clients fold support or automation supervision into their retained capacity, or run them as parallel agreements under the same account team. We will recommend the simplest structure that fits.

AI Strategy, AI Readiness Assessments, Agentic solutions with Microsoft Copilot Studio, MLOps, AI Governance, Azure AI Foundry implementation, and delivery accelerators. We cover generative AI, traditional ML, computer vision, and NLP.

We are a Microsoft Solutions Partner for Data & AI (Azure) with 3 Microsoft MVPs on staff and 150+ Microsoft certifications, and we publish a weekly Data & AI newsletter with 6k+ readers. Our AI delivery experience spans insurance, construction, financial services, and public sector.

Yes. We design and deliver agentic AI solutions using Microsoft Copilot Studio, grounding them on your Microsoft 365, SharePoint, Dataverse, and Azure data, and integrating with Power Automate for action-taking workflows.

Every engagement is scoped against our AI Governance framework covering model risk, data privacy, auditability, human-in-the-loop controls, and alignment with the EU AI Act and UK AI regulatory principles. We also deliver standalone AI Governance engagements for clients with existing AI estates.

AI Readiness Assessments run 2–4 weeks. Proof-of-concept agents or ML models typically deliver in 4–8 weeks. Production AI products including MLOps and governance usually run 3–6 months.

We deliver the full Microsoft data stack: Microsoft Fabric (Lakehouse, Warehouse, Real-Time Intelligence, Data Activator, Fabric Databases), Azure Databricks, Azure Synapse, Azure SQL, Power BI, and Purview for governance. We also modernise existing estates on SQL Server, SSIS, and SSAS.

Our accelerators deliver a working Fabric or Databricks foundation in 4–8 weeks. Full enterprise data platforms (multi-source, governed, with Power BI and AI layered on) typically run 3–6 months using our agile pod model.

Yes. We run dedicated migration engagements from SQL Server, Teradata, Snowflake, Redshift, and on-prem warehouses into Fabric. We assess readiness, map workloads, re-platform ETL, and cut over with minimal business disruption.

Yes. Our Synapx-as-a-Service model provides ongoing platform engineering, performance tuning, cost optimisation, and roadmap development for Fabric, Databricks, and Azure data estates.

The Microsoft Power Platform is a low-code suite for building apps (Power Apps), automating processes (Power Automate), analysing data (Power BI), creating external websites (Power Pages), and building AI agents (Copilot Studio). Synapx delivers end-to-end Power Platform solutions inside your existing Microsoft 365 and Azure estate.

Yes. Business Process Automation is a core Synapx practice. We automate finance approvals, HR onboarding, procurement, case management, and knowledge-worker processes using Power Automate cloud flows, desktop flows (RPA), AI Builder, and Copilot Studio agents. Typical outcomes: 40–80% reduction in manual effort and measurable cycle-time savings.

We establish a Power Platform Centre of Excellence (CoE) covering environment strategy, DLP policies, ALM (Dev/Test/Prod), solution packaging, monitoring, and maker enablement, so citizen-developer innovation is encouraged safely and IT stays in control.

Yes. Synapx holds the Microsoft Solutions Partner designation for Business Applications, which covers Power Platform and Dynamics 365, alongside the broader Microsoft Solutions Partner umbrella.

Our in-a-day workshops (App-in-a-Day, Dashboard-in-a-Day, Automation-in-a-Day, Agent-in-a-Day) deliver a working prototype in a single session. Production-ready solutions typically ship in 4–12 weeks depending on complexity and integration needs.

Synapx is headquartered in London, UK, with delivery teams across the UK and India. We work with clients globally, with a strong focus on UK enterprise and mid-market organisations.

We work across financial services, insurance, construction, professional services, retail, and public sector. Our Microsoft data and AI expertise is sector-agnostic, but we have deep referenceable experience in insurance and financial services.

Microsoft Solutions Partner for Data & AI (Azure), Microsoft Solutions Partner for Business Applications, Microsoft Fabric Featured Partner, Fabric Databases Featured Partner, and Real-Time Intelligence Featured Partner. We also hold 150+ active Microsoft certifications across the team.

The fastest route is a Discovery Call, a no-obligation 30-minute conversation to understand your data, AI, or automation challenge and outline the most appropriate engagement. You can book via our contact page.