Applied AI, built into working software
Applied AI inside working software: agents, retrieval over your own data, and generative features that are evaluated before release.
Services in this category
Pick the one you need. Each has its own page
We refuse to build an AI feature before we can measure it. A two-week POC establishes whether the workflow is worth automating, on your data, at a cost per request you have seen. Only then do we build the production version around it.
Capabilities
What the team actually does here
Retrieval over your data
Document ingestion, chunking, embeddings and a retrieval layer tuned on your own content, so answers are grounded and traceable.
Agents & automation
Agents that act inside the tools your team already uses, with tool permissions, guardrails and audit logging.
Generative features
Drafting, summarising and asset creation constrained by your rules, with human approval where output carries risk.
Evaluation & monitoring
Test sets, scoring and regression checks before release, then production monitoring of quality, latency and spend.
Cost engineering
Model routing, caching and prompt discipline sized to the business case, so unit economics survive scale.
Tech stack
Technology stack that powers the build
Models & frameworks
Data & retrieval
Tools
Ready to start an AI project?
A written scope, estimate and timeline before code starts. No sales pitch.