RAG & data access
Connect context and sources so answers remain traceable instead of merely plausible.
AI & AUTOMATION
Make AI production-ready, not just impressive in a prototype.
We connect AI features with good product logic, verifiable data flows and infrastructure that makes quality, cost and failures visible.
AI building blocks
From workflows to a dependable product feature.
Good prompts are only the beginning.
- Review sources, output and sensitive data
- Define useful evals and failure signals
- Think about application and operations together
AI workflows & integrations
Automate manual work with APIs, documents, checks and clear handoffs.
Evals & observability
Make quality, drift, latency and cost visible before failures spread through a process.
Run safely in production
Treat secrets, access, logs, backups and releases like any other production application.
A good fit when
An AI prototype needs to enter a real workflow.
- An AI MVP works as a demo but not reliably with real data.
- RAG answers are hard to evaluate or sources are not tracked properly.
- An internal workflow should process documents, invoices or data automatically.
- AI-generated application code needs structure, tests and a safe release path.
AI process
Clarify the workflow first, then make the model matter.
- 01
Bound the use case
Define the real user flow and decision where AI should help.
- 02
Check data & output
Make sources, schema, PII and failure cases visible and testable.
- 03
Build the workflow
Put integrations, fallbacks and human handoffs into the application.
- 04
Observe production
Keep quality, cost, latency and changes understandable over time.
FAQ
AI without product and operations fog.
Do you only work on prompts?
No. We focus on the full flow: data, application code, evaluation, integrations and operations.
Can you take over an existing AI prototype?
Yes. We review the repository, data flow, dependencies and deployment assumptions and shape a useful next step.
Which model or provider must we use?
That depends on data, cost, latency and requirements. We do not recommend a provider apart from the actual workflow.
Turn an AI demo into a dependable workflow.
Describe the user flow and data. We will help define the first production-minded step.