AI that earns its place in the system.

The highest-value AI opportunities are buried inside processes: reviewing hundreds of documents, extracting data, drafting analysis, routing work, comparing evidence, answering domain questions.

We map the workflow first. Then we decide whether the answer is an LLM, a retrieval system, an agent, a supervised model, plain deterministic software, or a combination.

Most organisations sit on documents, reports, messages, research and forms. We build pipelines that extract, classify, validate, enrich and structure that content so it can drive analytics, decisions and automation.

• Document ingestion and OCR handoff
• Extraction into structured schemas
• Entity resolution, classification and enrichment
• RAG and evidence-grounded interfaces
• Human validation for high-risk outputs
• Workflow triggers and downstream automation

Demos are easy. Reliable systems are not. We build evaluation datasets, measure accuracy and failure modes, compare models, manage latency and cost, and design review paths where the consequence of error matters.

Our goal is not “AI everywhere.” It is a better product, or a better operation.