Most AI projects stall between the demo and production, usually on the data underneath. We build both: the pipelines, warehouse and reporting that make your data dependable, and the agents, assistants and models that put it to work.
Agents that work your real systems through scoped credentials, with step limits and a hard stop.
Assistants on your own knowledge base, document extraction, and forecasts measured against today's baseline.
Every prompt, model or tool change measured before it ships, and every run traced with its cost.
Your applications, databases and third-party systems feeding one warehouse, with definitions agreed once.
Reporting built for specific decisions, and real-time queries on ClickHouse where yesterday's number is too late.
Automated checks that catch a broken upstream change before it reaches a report or a model.
We start from the decision or workflow you want to improve, then build backwards to the data and the model.
We identify the decisions and workflows the business wants to improve, rank them against your data and systems, and agree what success looks like numerically.
We assess what data exists and how reliable it is, then build the pipelines and warehouse the use case needs, with tests and monitoring from the start.
Working dashboards, agents or models, measured against how your team does it now, then deployed with scoped credentials, approval gates and budgets.
We run the platform, add sources as you grow, and tune prompts, tools and models as your data and business change.
A dashboard is only useful if people believe it, and an agent that cannot be observed, budgeted or stopped is a liability. We build the parts that make both safe to rely on.
Scope a use case