How we work

Requirements & Data Audit

We start by understanding the business and the data you actually have, not just the brief, so the system we design solves the real problem.

• Stakeholder interviews
• Data & systems audit
• Use-case prioritization
• Success metrics definition

System & Model Design

Every model choice, retrieval path, and data flow is planned before a line of code is written, so the build never backtracks.

• LLM & model selection
• RAG / agent architecture design
• Data pipeline planning
• Cost & latency budgeting

Data & Infrastructure Setup

The unglamorous work that decides whether the system survives real usage — vector stores, pipelines, auth — done first rather than last.

• Vector database setup
• Data ingestion pipelines
• Authentication & security
• Cloud infrastructure

Development & Integration

Models, agents, and application code come together, third-party APIs get wired in, and everything gets evaluated before it ships.

• Agent / chatbot development
• API & tool integration
• Prompt & retrieval tuning
• Evaluation & testing cycles

Deploy & Monitor

Launch day is the start, not the finish. We stay on to monitor drift, retrain, and improve — that's what the retainers are for.

• Production deployment
• Usage & cost monitoring
• Model retraining & tuning
• Ongoing feature work