We build custom AI agents that don't just answer questions — they plan, call tools, and take multi-step action across your systems, with the guardrails and approval gates that make autonomy safe to deploy.
Planning, tool use, memory, and the guardrails that keep autonomy inside a policy you can defend.
A production agent loop: decompose the goal, call the right tools, keep state, and finish the job — or stop cleanly.
Typed, permissioned connections to the systems the agent is allowed to read and write — not an unbounded plugin list.
Policy checks before every side-effect. High-impact actions wait for a human; the rest can run.
Multi-step runs scored on completion, policy, and cost — not just whether the last message looked right.
Every plan, tool call, approval, and write is logged. Your team gets runbooks, not a demo notebook.
The runtime loop and the approval gate — not a slide about “autonomous AI.”
// elhaa Agent Runtime — plan, act, gate const run = await elhaaAgent.execute({ goal: ticket.summary, tools: ['crm.read', 'erp.draftCredit'], policy: { requireApproval: ['write', 'pay'] }, onGate: 'pause-for-human' });
A chatbot could explain why a vendor invoice was blocked. It could not gather the missing PO, draft the credit, or update the ERP — so every exception still landed on the same two people.
We built an agent with read tools on ERP and email, a draft-credit tool, and a hard approval gate before any write. Multi-step traces were evaluated on completion and policy, then rolled out behind the existing exception queue.
*Illustrative example based on a representative engagement.
Name the jobs the agent may start, the systems it may touch, and the writes that must wait for a person.
Specify typed tools, permissions, and approval rules before a single loop is written.
Implement the planner and tool layer, then score traces on completion, policy, and cost.
Ship behind the existing workflow, with live audit logs and a kill switch your team can use.
Share of goals the agent finishes without a handoff — scored on real traces, not demos.
Side-effects that hit the gate as designed. Ungoverned writes must stay at zero.
Attempted actions outside the allowed tool set or spend limits — must trend to zero.
Tokens, tool calls, and human review time against the baseline process it replaces.
A chatbot answers. An agent plans, calls tools, and takes multi-step action in your systems. If the job can be finished with a reply, you don't need an agent — and we'll say so.
Tools are typed and permissioned. Writes, payments, and other side-effects hit an approval gate. The agent can be paused. Every plan and tool call is audited. Autonomy is granted per action, not as a blank cheque.
Usually not at first. We start with one agent and a small tool inventory. Multi-agent orchestration is added only when a single loop can't own the job without becoming unreviewable.
We evaluate full traces — goal in, actions out — against completion, policy, and cost thresholds. A fluent last message is not a pass.
Yes — that's the point. We wrap the systems you already use as tools with explicit permissions, rather than asking you to move the work into a new product.
A 30-minute call. We'll tell you honestly whether this is the right solution — and what it would take.
A short form, then a 30-minute call. We reply within one working day.
We'll be in touch within one working day.