From business problem to production system.
We combine product thinking, AI engineering, and production operations in one team, so the people who scope a system are the people who build, deploy, and can operate it.
LLM System Design
Architecture, model selection, and pipeline design for production AI systems tailored to your data, workflows, and compliance requirements.
RAG & Knowledge Systems
Retrieval-augmented generation on your proprietary data, accuracy, latency, and compliance built in from day one. Not a demo. In production.
AI Agent Development
Multi-step autonomous agents that integrate with your tools, APIs, and internal systems to automate complex, high-value workflows.
Fine-Tuning & Evaluation
Domain adaptation, custom eval suites, and adversarial testing to ensure models perform reliably inside your specific environment.
AI Ops & Infrastructure
Production deployment, cost optimisation, latency monitoring, and ongoing reliability engineering for live AI systems at scale.
Strategy & Roadmapping
Executive advisory on where AI creates real leverage in your business, and a phased, cost-effective roadmap that actually ships.
Sound familiar?
You don't have an AI problem. You have a business problem AI can solve.
Most of the companies we work with don't come to us asking for a model. They come to us with a bottleneck that is costing them time, money, or risk. That's where we start.
My team spends hundreds of hours a month on work software should be handling.
We automate the high-volume, repetitive parts of a workflow end to end, so your people spend their time on the work that actually needs them.
Nobody can find what they need across our own systems and documents.
We give your team instant, cited answers from your own knowledge, so the right information is one question away instead of a half-hour hunt.
Our support team is drowning, and a generic chatbot only made it worse.
We build support that actually resolves issues from your real knowledge base and escalates honestly when it isn't sure, instead of deflecting with confident wrong answers.
We want to automate this, but we're afraid of AI getting it wrong.
We prove the system on your data before you commit, measure its accuracy against a real evaluation set, and build in guardrails and human oversight from day one.
One team takes a problem from business case to a system that keeps running, and we start with whichever part carries the most risk for you.
Solutions by industry
- RAG for Financial Services
- AI Agents for Legal
- AI Agents for Customer Support
- RAG for Healthcare
- RAG for Legal Research
- AI Agents for Finance Operations
- AI Agents for Insurance
- Knowledge-Grounded Support (RAG)
- AI for HR & Recruitment
- Fine-Tuning for Clinical Documentation
- LLM Strategy & AI Readiness
- AI Agents for Sales
- LLMOps for Production AI
- Enterprise LLM System Design
- AI Strategy & Roadmap
- AI Proof of Concept
- Document Workflow Automation
- Private AI for Regulated Industries
- Measuring AI System Accuracy
- AI Readiness Assessment
- Document Automation ROI Audit
Start here
Start with a diagnostic, not a leap of faith
Before a build, the honest first question is whether it is worth building at all. Each of these is a fixed-scope, fixed-price engagement that answers one question with evidence, and each ends with a written report and a live readout call. They stand on their own, and where the answer is build, they lead naturally into a proof of concept.
Have a use case worth solving?
Tell us what you're trying to automate, improve, or build. We'll tell you whether AI is a good fit, what we'd recommend, what it would take to build, and what it's likely to cost.