Service · ai-automations
AI Automations & Agents
Production AI agents and automation pipelines, engineered to hold up under real load for months.
What we do
We design, build, and run AI agents that do work, not demos. RAG, multi-step workflows, tool-using agents, plus the unglamorous evaluation harnesses and guardrails that keep them from going off the rails on day 30.
Why us
Most agent demos work on a happy path and fall apart on edge cases. We build the eval harness first, then the agent, so when something regresses you find out in CI, not in production. Cite-or-refuse is the default rule, not an afterthought.
- OpenAI API
- Claude API
- LangChain
- LlamaIndex
- Pinecone
- n8n
- Zapier
- Make
- FastAPI
- Postgres
What you get
- Internal RAG / “chat with your data”, properly grounded in your sources, with citations and refusal on low-confidence retrieval.
- Customer-facing chatbots with safe-handoff to humans (the move that keeps healthcare / finance compliance teams comfortable).
- Multi-step agents using tools (read mailbox, write to CRM, query database, post to Slack) with explicit allow-lists, not “let the model decide”.
- Workflow automation in n8n / Zapier / Make where a no-code stack is enough, custom code where it isn’t.
- Evaluation harnesses you actually run in CI. Most “we tried that and it didn’t work” stories trace back to no eval.
How we ship
- Failure modes first. What can the agent never do? Those rules become the first eval tests, before any prompt is written — we build the eval harness before the agent.
- Cite-or-refuse. No graceful hallucinations. If the retriever doesn’t find a confident hit, the model says so.
- Safe-handoff as a primary action, not a fallback. When in doubt, escalate to a human, and log it.
- Daily evals. Every prompt change, every model swap, every retriever tweak runs the harness.
- Observability. You see which agent, on which input, fired which tool, with which result.
Agents often only work as well as the data infrastructure underneath them — we build that layer too, and you can see both in our shipped work.
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