AI & Machine Learning · 1 of 5
Generative AI Solutions
Leverage Azure OpenAI, Microsoft Copilot, and RAG architectures to build intelligent applications that generate content, automate workflows, and enhance productivity.
Why it matters
Where Generative AI Solutions fits
Leverage Azure OpenAI, Microsoft Copilot, and RAG architectures to build intelligent applications that generate content, automate workflows, and enhance productivity.
This sits inside our ai & machine learning practice, and rarely arrives alone — most engagements combine it with two or three of its neighbours. The assessment decides which, and in what order.
What the practice is measured on
Accelerated Innovation
Deploy AI solutions 3x faster with our proven frameworks
Cost Optimization
Reduce operational costs by up to 40% through automation
Enhanced Experience
Improve customer satisfaction with personalized AI interactions
Data-Driven Insights
Make better decisions with predictive analytics
Generative AI Solutions
Azure OpenAI, GPT-4, Copilot Studio, RAG Architecture, LangChain
You are herePredictive Analytics
Azure ML, Python, TensorFlow, PyTorch, Scikit-learn
Computer Vision & NLP
Azure Cognitive Services, OpenCV, BERT, Transformers, OCR
Azure OpenAI- GPT-4
Copilot Studio- RARAG Architecture
LangChain
Microsoft Azure
Amazon AWS
The Tech Stack We Work In
The tooling we actually build generative ai solutions on.
Google Cloud
Databricks
Snowflake
Kubernetes
Docker
Terraform
PyTorch
AI Integration Platforms
Power Platform, AI Builder, M365 Copilot, Custom Copilots, API Integration
Model Ops & Governance
MLflow, Azure DevOps, Model Registry, A/B Testing, Monitoring
How We Deliver It
A sequence you can plan around, with a decision point at the end of each phase rather than one big reveal at the end.
Discovery & Assessment
Analyze your business needs and identify AI opportunities
Strategy & Planning
Design AI architecture and implementation roadmap
Development & Training
Build and train custom AI models for your use cases
Integration & Deployment
Deploy AI solutions into your production environment
Monitoring & Optimization
Continuously monitor and improve model performance
Where we apply it by sector
The constraints differ more than the technology does. Each sector page sets out what changes in that context.
Why organisations choose us for this
Five commitments that hold on every engagement, not just the ones that go well.
Audit first, build second
Every engagement opens with an assessment that produces a prioritised backlog. Engineering starts against that, not against an assumption.
Incremental, not big bang
Existing systems keep running while we work. Delivery arrives in increments you can put in front of users rather than one release at the end.
Fixed scope per phase
Each phase has defined outputs and a defined cost, with a decision point at the end. You can stop between phases without stranding the work.
Ownership-first documentation
Architecture decisions are written down with their rationale, in your repositories, so the reasoning survives the people who made it.
Compliance-aware by default
Access control, auditability, and data residency are settled in the first architecture review rather than retrofitted before an audit.
Frequently Asked Questions
What we are asked most often about generative ai solutions.
Almost never. We work incrementally around what you already run, extracting interfaces and migrating in phases so the existing system keeps serving users while the new one takes over piece by piece.
That is what the assessment establishes. We map your current architecture, data and constraints first, and if the approach will not hold in your environment we say so before anyone commits to a build.
Discovery is fixed-price and ends with a costed roadmap. Build phases are then priced per phase against defined outputs, so you are never approving an open-ended budget.
You do — code, infrastructure definitions, any trained models, and the documentation. All of it lands in your own repositories and cloud tenancy as we go.
Monitoring, alerting and agreed response targets are part of delivery. Where we also run the platform under managed services, we are the ones on the other end of the alert.
Get a free generative ai solutions assessment
We map what you have, what it would take, and in what order — specific to generative ai solutions in your environment.
Book a Free Architecture ReviewWhat you get from the audit
- A complete architecture map of what you have today
- A prioritised change list, worst-first
- A sequenced roadmap broken into phases
- A fixed-price estimate for phase one
Yours to keep whether or not you engage us.
