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Forward Deployed Engineers01 / 06

Put AI engineers
inside the problem.

Embedded engineers use Claude to build, test and ship governed agentic workflows alongside your business and technical teams.

  • Claude
  • Agentic workflows
  • Embedded delivery
The challenge

Generic AI prototypes rarely understand the organisation’s data, controls, tools or real ways of working.

How we help

Embedded engineers use Claude to build and test in short cycles, then transfer documentation, capability and ownership.

Embedded buildWorking in weeks
BUSINESS QUESTION

Review this claim, compare the evidence and prepare the next action.

01ReasonRead structured + unstructured data
→
02Use toolsCheck systems and policies
→
03Act safelyRoute, document and hand off
CLAUDE / CONTROLLEDHigh-risk indicators found.

Case routed with evidence, explanation and recommended next step.

Human review required

Forward deployed engineering

Embedded AI engineering, powered by Claude.

What is a Forward Deployed Engineer?

An FDE works alongside business and technical teams in day-to-day operations rather than behind a remote ticket queue. Using Claude, they prototype, automate and deploy solutions shaped around your data, systems and ways of working—delivering value in weeks rather than months.

AI services, powered by Claude

Claude can reason over complex unstructured business data, orchestrate multi-step agentic workflows and safely use tools to take action. It adds a conversational, agentic layer to Corporate Data Platforms such as Databricks and DataWalk while retaining enterprise safety, governance and control.

We apply generative AI to practical problem-solving, document intelligence, decision support and process automation rather than treating AI as a disconnected experiment.

How we work

  1. Discovery sprint: identify the highest-value problems and shape a clear, bounded plan.
  2. Embedded build: work alongside your team to build, test and iterate in short cycles.
  3. Handover and enablement: train the team and transfer documentation and ownership.

Use cases

  • Claims triage and investigation
  • Natural-language reporting over Corporate Data Platforms
  • Document and contract intelligence
  • Multi-step process automation

Data Analytics02 / 06

Turn information into
clear direction.

We create trusted reporting, real-time insight and predictive intelligence from data spread across systems, spreadsheets and documents.

  • Business intelligence
  • Predictive analytics
  • Responsible AI
The challenge

Critical data is spread across systems, spreadsheets and documents. Teams spend too much time collecting and reconciling information before they can ask the questions that matter.

How we help

We connect and enrich the data, shape reusable analytical models and deliver dashboards, self-service reporting, predictive models and responsible AI.

Decision intelligenceExplainable
QUESTION / LIVEWhere is margin changing fastest?
Confidence94.8%

Data analytics and visualisation

Turn raw data into meaningful action.

How do we turn raw data into insight?

We help you unlock the true value of your data by analysing it in depth to identify meaningful patterns, trends and relationships. Through advanced analytics techniques, we turn raw data into clear, actionable insights that support strategic planning and day-to-day decision-making.

Our approach starts with your business goals, asks the right questions of the data and delivers insight that drives efficiency, growth and measurable outcomes.

Data Visualisation

We transform complex datasets into clear, intuitive visual stories that make information easy to understand and act upon. Interactive dashboards and tailored reports help stakeholders quickly see what matters, monitor performance and explore data with confidence.

Visualisations are designed to highlight key trends, surface opportunities and support faster, better-informed decisions across the organisation.

Custom Reporting Solutions

We design reporting solutions around your goals, measures and decision-making processes, ensuring the right information reaches the right people at the right time.

From automated reports and executive summaries to detailed operational views, the solution remains flexible and scalable as the business changes.

Data Engineering03 / 06

Teach your systems
to work together.

Dedicated data engineering pods build pipelines, integrations and governed data products — turning fragmented sources into a dependable flow built for analytics, applications and AI.

  • Dedicated pods
  • Pipelines
  • Integration
  • Cloud engineering
The challenge

Duplicated data, manual extracts and brittle pipelines make new analytical and AI ambitions inherit the same instability.

How we help

A dedicated pod works inside your team — engineering batch and real-time pipelines, integrating structured and unstructured sources, and building in quality, observability, security and ownership.

Live integration field4 sources connected
MICROSOFT AZUREAWSDATABRICKS
TRUSTED / LIVEOne useful stream.
99.7% quality · governed · observable

Data engineering

Unify critical data and move faster.

How do we approach data modelling?

Well-organised and transformed data enables better decisions. We structure data around your requirements by identifying key entities, defining relationships and modelling the business processes that matter.

We automate extraction, transformation and loading into your chosen data lake or warehouse, using technologies including Databricks, Microsoft Fabric and AWS.

Data Integration

We overcome silos by integrating information from multiple systems into a single trusted view. Robust pipelines move data reliably between applications, databases and platforms in near real time or on a controlled schedule.

This makes consistent, high-quality data available for reporting, analytics and operational processes while reducing manual effort and complexity.

Real-Time & IoT Integrations

Scalable streaming and event-processing solutions ingest and combine data from connected devices, sensors and event-driven systems as it is generated.

This can monitor equipment, track assets, detect anomalies and power live alerts and dashboards—giving operational teams immediate visibility and the ability to automate a response.

What is a data engineering pod?

A dedicated pod is a small, standing team of data engineers assigned to your organisation rather than pulled from a shared bench. The same people stay on the engagement from the first pipeline through to handover, so context compounds instead of resetting with every ticket.

A pod typically pairs one or two senior engineers with a technical lead, working inside your delivery rhythm and reporting into the same governance as an internal team—scaled up or down as the pipeline backlog changes.

Cloud Platforms & DevOps04 / 06

A platform your
team can run with confidence.

We design, implement and manage cloud data environments across Azure, AWS, Databricks and Microsoft Fabric, with deployment automation, observability and security controls built in.

  • Cloud platforms
  • Deployment automation
  • Observability
The challenge

Infrastructure overhead and manual, inconsistent deployments slow teams down and make change harder to control.

How we help

We build governed cloud foundations with automation, monitoring and security designed in from the start, not bolted on afterwards.

Cloud platformOperational
PLATFORMSAzureAWSDatabricksMicrosoft Fabric
01
DesignGoverned cloud foundation
✓
02
ImplementProvision and configure
✓
03
AutomateConsistent, controlled deploys
✓
04
OperateObserve, secure, support
→
OPERATIONAL SUPPORT100%

Deployment automation

Change controlled

Cloud platforms & DevOps

Cloud foundations, managed end to end.

What does this cover?

We design, implement and manage data environments across Azure, AWS, Databricks and Microsoft Fabric, including deployment automation, observability, security controls and operational support.

This gives teams a scalable platform they can run with confidence while reducing infrastructure overhead and keeping change controlled.

Deployment automation

Consistent, repeatable deployment reduces the risk that comes with manual changes, so releases move through environments the same way every time.

Observability and security

Monitoring and security controls are designed in from the start, giving teams visibility into how a platform is running and confidence that access and change are governed.

Platforms we work across

Azure, AWS, Databricks and Microsoft Fabric — we design and manage cloud environments across whichever of these a customer already runs.

Business App Development05 / 06

Put insight
inside the work.

Composable applications, portals and automated workflows turn data into a working service through short sprints and regular playbacks.

  • Business apps
  • Process automation
  • Agentic AI in the SDLC
The challenge

Lengthy specifications and disconnected suppliers increase risk while the business requirement changes before the software arrives.

How we help

A focused two-to-four-week mini-plan leads into two-week sprints and regular playbacks, delivering usable software early.

Operational workflowRunning
Today128decisions supported
Automated73%manual effort removed
Cycle time−41%signal to action
Signal
Decision
Action
Insight → owner → action → measured outcome24h

Business applications

Business and data app development with agentic AI in the SDLC.

The challenge

Businesses need to adapt quickly to grow in a competitive landscape. Traditional projects spend months collecting and signing off requirements before development begins—by which point needs may have changed and opportunities may have passed.

How do we use agentic AI in the SDLC?

Agentic AI is built into how we plan, build and test business and data applications, not bolted on afterwards. It replaces lengthy up-front specifications with a short mini-plan, iterative build sprints and regular playbacks, using microservice architecture and Corporate Data Platforms to configure new applications quickly.

Claude works alongside our engineers across the software development life cycle — drafting and refactoring code, writing and running tests, and preparing changes for review — while a combined client and Data Company team directs the work, reviews every change and owns the architecture and decisions that matter. A focused two-to-four-week mini-plan defines the solution, followed by two-week build sprints and regular playbacks until the vision is realised.

Microservice architecture and Corporate Data Platforms let us configure new applications and processes rapidly, with agentic AI accelerating implementation while stakeholders stay close to every decision.

How we do it

  • Business insights: extract and enrich information hidden in systems, spreadsheets and documents.
  • Business applications: deliver composable applications that respond quickly to customer and market needs.
  • Solutions: combine data and software to support growth, profitability and better service.

Delivery capability

  • Experienced multidisciplinary teams and project management
  • Business analysis and process re-engineering
  • Bespoke mobile apps, web apps, portals and business systems
  • Rigorous technical and user acceptance testing
  • Ongoing maintenance, support and cloud services

Solution Architecture06 / 06

Build around the
business outcome.

We combine data, applications, industry experience and partner technology to launch services, improve processes and automate manual work.

  • Insurance
  • Construction
  • Health + FinTech
The challenge

Business improvement often cuts across information, process, technology and ownership. A point product rarely resolves the whole problem.

How we help

We combine Corporate Data Platforms, bespoke applications, analytics and partner technology through one accountable team, using agentic AI across the SDLC to move faster from plan to working software.

Solution assemblyOutcome led
BUSINESS OUTCOMEOne working solution.

Data, process and technology assembled around the result.

01Launch services

New digital propositions and customer experiences.

02Improve operations

Connected, auditable processes with less friction.

03Automate work

Manual activity converted into controlled workflows.

04Enable growth

Scalable platforms that adapt with the organisation.

Outcome-led solutions

Delivering data and business agility.

What solutions do we deliver?

Our solutions help organisations rapidly launch new services, enhance existing processes and automate manual tasks through our technology platforms.

We use Corporate Data Platforms and bespoke business applications to increase efficiency, drive revenue and support expansion.

Solution architecture & consultancy

We translate business goals into a practical data and technology roadmap, shaping the architecture, platforms, governance and delivery approach needed to move from ambition to implementation.

Our consultants work across business and technical teams so design decisions remain grounded in measurable outcomes, operational constraints and long-term ownership.

People, process and technology

Business agility comes from bringing these elements together. Deep industry experience and specialist data expertise allow us to understand needs quickly and turn them into effective solutions using a delivery methodology that puts agentic AI to work across the SDLC.

Delivery as one team

We work closely with business and IT teams through agile sprints and regular progress demonstrations. This keeps everyone aligned and ensures the final solution remains faithful to the original vision and requirements.

Broader capability

Partnerships with leading service providers complement our own skills and allow us to deliver joined-up solutions across Insurance, Construction, Health, FinTech and other sectors.