AI Engineering

AI that survives production

Most AI work stalls between the demo and the deadline. We build the unglamorous half — retrieval over your real documents, agents scoped to a job they can finish, and the evaluation that proves it before your customers do.

See the work All services

Advanced RAG & Knowledge Systems3 capabilities
AI Agents & Multi-Agent Systems3 capabilities
Agentic Workflows & Automation2 capabilities
Core AI Foundation Services2 capabilities

What we build

01
Advanced RAG & Knowledge Systems
Retrieval that survives contact with real company data — permissioned, multi-modal and able to reason across documents.
- Enterprise RAG Systems
  Secure search over private company documents, with the access rules your business already runs on. Answers never cross a permission boundary, and every one of them can be traced back to the source it came from.
- Multi-Modal RAG
  Retrieval that reads text, tables, charts and images together, so a figure buried in a scanned chart is as findable as a sentence in a policy document.
- GraphRAG
  Knowledge graphs paired with language models, so the system can follow relationships between entities and answer the questions that span dozens of documents rather than sitting inside one.
02
AI Agents & Multi-Agent Systems
Agents scoped to a job they can actually finish — and the judgement to hand back to a person when they cannot.
- Task-Oriented AI Agents
  Specialists rather than generalists: an agent for customer support, for sales qualification, for data entry. Narrow scope, defined tools, a measurable outcome you can hold it to.
- Multi-Agent Orchestration
  Networks of agents that delegate to one another — a planner, a researcher, a reviewer — to complete workflows no single prompt could carry on its own.
- Human-in-the-Loop Agents
  Automation that knows its limits. The system does the work and routes the final call to a human with the full context attached, so approval takes seconds instead of a re-investigation.
03
Agentic Workflows & Automation
Replacing brittle rule-based automation with systems that plan, adapt and recover.
- Autonomous Agentic Workflows
  Model-driven planning and execution in place of rigid if-this-then-that chains that break on the first exception nobody predicted.
- Tool-Use Integration
  Function calling wired safely into the APIs, databases and CRMs you already run — typed contracts, scoped permissions, and a clear record of every action an agent took.
04
Core AI Foundation Services
The groundwork that makes everything above safe to put in front of a customer.
- Custom LLM Fine-Tuning
  Adapting open models to your industry's language, formats and tasks — frequently smaller, cheaper and more accurate on your work than a general-purpose model.
- AI Evaluation & Guardrails
  Evaluation harnesses, data-privacy controls and guardrails that catch hallucinations and unsafe output in testing, rather than letting your customers find them first.

How an engagement runs

01
Find the work worth automating
We start with the process, not the model — where the hours go, which decisions repeat, and what a good answer actually looks like to the people doing the job today.
02
Prove it on your data
A narrow prototype on real documents and real edge cases, scored against a written definition of correct. If it does not clear the bar, you find out in weeks rather than quarters.
03
Ship it with guardrails
Evaluation suites, permission boundaries, fallbacks and human hand-off built in before launch — so the system fails safely and visibly instead of quietly.
04
Measure, tune, hand over
Live monitoring of cost, latency and answer quality, then tuning against what production teaches us — and documentation your team can run without us.

What we work across

We are not tied to one vendor, model or framework. Which model to use, where it runs and what it stores depend on your data, your constraints and your budget — so we choose per project and keep the architecture portable enough to swap any piece later.