AI Agents & Machine Learning
Production AI agents, RAG pipelines and LLM integrations — multi-agent systems built to run unattended.
Most AI projects die between the demo and production. The demo works because a human is watching; production fails because nothing handles the case where stage four returns malformed output at 3am. We build the second kind. That means structured contracts between agents, isolation so one failing stage does not corrupt a run, evaluation you can actually act on, and observability that tells you which step degraded rather than that the output got worse. We have shipped a nine-agent content pipeline that runs unattended and a document-AI system operating inside a licensed, regulated profession.
Scope the task an agent can actually own
Build the evaluation set before the agent
Ship one stage at a time, measured
Instrument for failure, not for the happy path
Hand over with the evals and the runbook
Workflow Automation & Integrations
n8n, Temporal and custom workflows that connect your systems and keep running when something upstream breaks.
Read moreWeb Application Development
React and Next.js applications built to stay fast and maintainable long after launch.
Read moreSaaS Product Development
Multi-tenant SaaS products with billing, roles and metering designed in from the first commit.
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