Services

AI systems, and the foundations they need

Agents, language models and retrieval at the top. Data platforms, cloud and security underneath — because that is where AI projects actually fail. We do both, and we say plainly when a piece of work does not need us.

Artificial Intelligence & Machine Learning

Machine learning that survives contact with production. We build models, the pipelines that feed them and the monitoring that tells you when they drift.

Custom model developmentRecommendation and personalisation enginesNatural language processingTime-series forecasting+5 more
How we approach it

Generative AI & LLM Engineering

LLM applications built like software: evaluated, versioned, cost-controlled and safe to put in front of customers.

Model selection and benchmarkingPrompt engineering and versioningStructured output and tool callingEvaluation harnesses+6 more
How we approach it

AI Agents & Agentic Automation

Agents that do the work — read the inbox, update the record, chase the approval — with the permissions, audit trail and stop button that makes that safe.

Workflow agentsTool and API integrationHuman-in-the-loop designPermission scoping+6 more
How we approach it

Conversational AI — Chat and Voice

Assistants that resolve the request instead of deflecting it, and hand over cleanly to a person when they should.

Customer support assistantsVoice agentsWhatsApp and messaging channelsMultilingual conversation+5 more
How we approach it

Enterprise RAG & Knowledge Systems

Search and answers over your own documents, with citations, permissions that match your existing access rules, and honest behaviour when the answer is not there.

Document ingestionChunking and indexing strategyHybrid retrievalReranking+6 more
How we approach it

Computer Vision & Document Intelligence

Systems that read documents and interpret images — invoices, forms, IDs, inspection photographs — with confidence scores and a review path for what they get wrong.

Intelligent document processingOptical character recognitionStructured extractionIdentity and KYC document handling+5 more
How we approach it

Predictive Analytics & Forecasting

Forecasts that carry their uncertainty honestly, connected to the decision they are supposed to inform.

Demand and sales forecastingChurn and retention modellingCredit and risk scoringInventory and capacity planning+6 more
How we approach it

MLOps & AI Platform Engineering

The unglamorous layer that decides whether your AI work survives its first year: pipelines, registries, evaluation in CI, cost visibility and on-call.

Training pipelinesModel registry and lineageEvaluation in CIDeployment patterns+6 more
How we approach it

AI Strategy, Governance & Responsible AI

Deciding what to build, what to refuse, and how to prove afterwards that the system behaved as you said it would.

Use-case prioritisationAI readiness assessmentRisk tieringModel documentation+6 more
How we approach it

Data Science & Analytics

The pipelines, warehouse and definitions that everything else depends on — including every AI system you plan to build.

Data warehouse and lakehouse designETL and ELT pipelinesData quality testingMetric definitions and semantic layer+6 more
How we approach it

Cloud Solutions & DevOps

Infrastructure that deploys predictably, scales when it has to, and costs what you expected at the end of the month.

Cloud architectureMigration and modernisationKubernetes and containersCI/CD pipelines+7 more
How we approach it

Web & Mobile Development

Products people can actually use — fast on a mid-range Android on a patchy connection, accessible, and maintainable after we leave.

Web applicationsMobile applicationsProgressive web appsAPI design+6 more
How we approach it

Cybersecurity

Security engineering for modern stacks, including the parts of AI systems that traditional reviews miss entirely.

Application securityAI system securityCloud security postureIdentity and access management+6 more
How we approach it

Digital Transformation

Replacing the processes that run on spreadsheets and goodwill — sequenced so the business keeps running while you do it.

Process mappingSystems assessmentERP and CRM implementationLegacy integration+5 more
How we approach it
How we package it

Four ways we work

Most engagements start with the first, and move to the others only when they have earned it.

Advisory

Working out what is worth building. Use-case review, data readiness, risk tiering and a sequenced roadmap you could hand to another supplier if you wanted to.

Prioritised use casesHonest feasibility viewSequenced roadmap

Build

Designing and shipping the system — agents, models, retrieval, data foundations and the integrations into the tools your teams already use.

Production systemsEvaluation you can trustDocumented handover

Managed operations

Running it after launch: monitoring, evaluation as models change, cost control, incident response and retraining when reality drifts.

Monitored in productionCost under controlSomeone on call

Products

Where our own software fits your problem, deploying that instead of building from scratch — including renting agents rather than commissioning them.

Faster to liveLower build costRentable AI agents

Which one you need

If you already know what you want built, start at Build. If you have a list of AI ideas and no way to rank them, start at Advisory — it is cheaper to kill a bad use case on paper than in production. If something is already live and nobody is watching it, start at Managed operations. And if one of our products already does the job, we will point you there instead of quoting a build.

By sector

What we are most often asked to build

Two things per industry that come up again and again. They are starting points, not products off a shelf.

Healthcare & Life Sciences

Clinical documentation support with human review

Claims and referral document extraction

Banking & Financial Services

Onboarding and KYC document intelligence

Explainable risk and anomaly detection

Manufacturing & Industry 4.0

Vision-based quality inspection

Condition-based maintenance forecasting

Retail & E-Commerce

Demand forecasting with promotion effects

Catalogue enrichment and service assistants

Education & EdTech

Course material retrieval with citations

Student service assistants with staff handover

Energy & Utilities

Load and generation forecasting

Maintenance prioritisation across distributed assets

Logistics & Supply Chain

Shipping and customs document extraction

Exception detection and triage

Real Estate & PropTech

Lead qualification and routing

Agreement and approval document processing

Getting started

What actually happens next

No discovery phase that bills for three months before anything works.

1

A conversation, not a pitch

You describe the process or the stalled project. We ask what decision it feeds and what it costs you today.

2

A short assessment

We look at the data and the systems involved, and come back with what is feasible, what it would take, and what we would not do.

3

One thing, built properly

A single workflow taken to production, with evaluation agreed up front, rather than a programme announced across six.

4

Handover or ongoing operation

Your team takes it on with documentation and runbooks, or we keep running it. Both are fine; being unclear about which is not.

Not sure which of these you need?

Describe the problem rather than the technology. We will tell you which of these applies, and which of them you can skip.

Talk to an engineer