PyTorch
Transformers
Azure DevOpsIntelligent Document Processing
Automate document extraction and processing using AI-powered OCR and NLP
AI & Machine Learning
Transform Your Business with Intelligent AI Solutions
Harness the power of generative AI, machine learning, and intelligent automation to drive innovation, enhance productivity, and create exceptional customer experiences.
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Projects delivered
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Years of engineering
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Active clients
Five ways this goes wrong
Why choosing the right partner matters
Every one of these is something we have been called in to fix after someone else built it. Which is why we plan for all five before writing code.
01/05
What usually happens
Pilots that stall
Most initiatives never leave proof of concept, because nobody planned for production. The demo works, the business case never lands, and the budget quietly moves on.
Seen on projects we inherited, not hypotheticals.
How we handle it
Discovery ends in a production plan, not a demo. If a pilot cannot reach production, we say so before it is built.
Which of these is yours?Discovery names it in the first two weeks — and the roadmap is yours either way.
Inside the practice
What Our AI & Machine Learning Services Cover
5 capabilities, and engagements usually combine several. Open any one to see how we deliver it.
Measured, not promised
What You Get Out of It
Four outcomes we agree at the start of an engagement and hold ourselves to at the end. If we miss one, that shows up in the review, not in the small print.
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
Shipped more than once
Where It Gets Used
Patterns we have built before, and the shape of problem each one suits. If your situation is close to one of these, we have the reference architecture already.
Conversational AI Assistants
Build custom chatbots and virtual assistants that understand context and provide intelligent responses
Predictive Maintenance
Prevent equipment failures and optimize maintenance schedules using machine learning
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.
01
Discovery & Assessment
Analyze your business needs and identify AI opportunities
02
Strategy & Planning
Design AI architecture and implementation roadmap
03
Development & Training
Build and train custom AI models for your use cases
04
Integration & Deployment
Deploy AI solutions into your production environment
05
Monitoring & Optimization
Continuously monitor and improve model performance
Generative AI Solutions
Azure OpenAI, GPT-4, Copilot Studio, RAG Architecture, LangChain
Predictive Analytics
Azure ML, Python, TensorFlow, PyTorch, Scikit-learn
Computer Vision & NLP
Azure Cognitive Services, OpenCV, BERT, Transformers, OCR
Azure OpenAI
Microsoft Copilot
Python
TensorFlow
Azure ML- Power Platform
- Microsoft Azure
AI
The Tech Stack We Work In
The tooling we actually build ai & machine learning on.
Amazon AWS
Google Cloud
Databricks
Snowflake
Kubernetes
Docker
Terraform
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
Frequently Asked Questions
What we are asked most often before a ai & machine learning engagement starts.
You do not have to know. Discovery exists to answer exactly that, and it ends in a written recommendation — including the recommendation not to proceed, if the numbers do not support it.
Discovery runs one to three weeks. Build phases are typically six to sixteen weeks depending on scope, delivered in increments you can actually run rather than one release at the end.
That is the normal case rather than the exception. Integration and phased migration are scoped in the first phase, because something that cannot reach your existing workflows and data is not finished.
You do. Source, infrastructure definitions, trained models and documentation land in your own repositories and cloud tenancy as we go — not in a handover at the end.
Monitoring, alerting and agreed response targets are part of delivery, not an upsell. Where we run the platform under managed services, we are the ones who respond.
Get a free ai & machine learning assessment
Tell us what you are trying to change and we will map what it actually takes — architecture, sequence and cost — before anyone commits to a build.
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.
