service · agentic AI
AI agents for operations
Supervised AI agents that do the operational work — using your tools and data.
Turning a defined manual operation into a supervised, multi-step AI-agent workflow that uses your own tools and data, with a human in the loop.
- Claude / LLMs
- LangGraph
- CrewAI
- MCP
- pgvector / RAG
- LangSmith
overview
What it is
Most operational work is a loop a person runs across a few tools: read this, check that, decide, update the system, notify someone. An AI agent can run that loop — but only safely when it is scoped to one well-defined operation, grounded in your own data, integrated with your real systems, and kept under human oversight with approval gates.
We design, build, and harden that agent — single agents or multi-step crews — and hand it over with the logging and monitoring to actually trust it. The model proposes; your rules and your people stay in control of anything that matters.
what's included
Capabilities
Workflow discovery & scoping
We map a real manual operation end to end and pick the one workflow worth automating first — clear inputs, a clear definition of done, and bounded risk.
Agent design & orchestration
A single agent or a multi-step crew with branching, retries, and state — built on stateful frameworks (LangGraph, CrewAI), not brittle one-shot prompt chains.
Tool & API integration
The agent acts through your real systems — CRMs, internal APIs, email, databases — via typed tools and MCP, so it does the work rather than just describing it.
RAG knowledge grounding
Decisions and answers grounded in your own documents and data, so the agent reasons over your reality with citations — not generic web knowledge.
Human-in-the-loop guardrails
Approval gates, allow-lists, and hard limits the agent cannot override. A person stays in control of every consequential action.
Evaluation, logging & monitoring
Every run is logged and reconstructable, with evals and agent-observability (AgentOps) so you can see what the agent did, why, and catch regressions early.
why it matters
Benefits
- Repetitive, multi-step operational work gets handled without a person babysitting every step.
- Your team is freed for judgement work while the agent runs the routine loop — with a human approving anything that matters.
- Because it is grounded in your data and wired into your tools, it fits your actual process, not a generic template.
- Auditable by design: every decision is logged and reconstructable, so the system is safe to run and easy to trust.
in practice
Use cases
how we work
The engagement
Discovery & workflow selection
We map your operation and choose one workflow with clear inputs, a clear definition of done, and bounded risk.
Supervised pilot
We build the agent end to end and run it alongside your team, with a human approving every consequential step.
Hardening
Guardrails, evals, logging, and integration hardening until it is reliable on the real workflow.
Handoff & ownership
We hand over a monitored, documented system your team owns — and extend to the next workflow when you're ready.
get in touch
Let's talk
Have an operation you'd like an agent to run, or want to see how AI agents for operations could fit your work? Tell us about it and we'll come back with a tailored plan.