ServicesAgents in production

Agents that act in your systems, under control.

From one business workflow to an agent operating in your ERP, CRM or ticketing system, with a managed harness, an evaluation suite, scoped permissions and a handover your team can run.

Who it is forOperations and technology leaders with a workflow that is repetitive, rule-bound and expensive in people's time, and teams with a prototype that works in a demo and nowhere else.

The problem

Prototype agents are easy; production agents are not. The difference is the harness: evaluation before building, traces of every step, permissions per tool, a way for humans to step in, and a model you can swap when a better one arrives.

We build that harness first, on Amazon Bedrock AgentCore and Strands Agents or on Azure AI Foundry and Microsoft Agent Framework, and we expose tools over the Model Context Protocol so the agent is not married to one vendor's loop.

What we deliver

Workflow selection and evaluation cases written before any prompt
Agent built on a managed harness, with tools over MCP and agent-to-agent communication over A2A
Scoped permissions, human approval gates and full traces
Evaluation suite, batch scoring and red-team before launch
Deployment in your tenancy with runbooks and dashboards
Knowledge transfer and handover to your engineers

How we work

Discover

One workflow, one measurable outcome. Evaluation cases agreed in writing.

Prototype

A working agent against real tools, behind MCP, with traces from day one. Used on real cases, not slides.

Harden

Guardrails, red-teaming, permissions, identity for every tool call, budgets for tokens and latency.

Run

Handover with dashboards and a playbook, or a monthly engagement to operate it with you.

What backs it

Our trace view on the home page shows what a production agent looks like to us: every tool call, its duration and its cost. The six-week Build engagement is fixed scope and fixed price.

Common questions

Which model will the agent use?

Whichever wins on your evaluation cases. Claude, Amazon Nova, OpenAI and open-weight models are all candidates, and the harness lets you change later.

What can the agent not do?

Anything you have not explicitly permitted. Tools are read-only by default; writes go through permission checks and, where it matters, a human approval.

How long until it is in production?

Six to twelve weeks for a first workflow, depending on the systems involved and how quickly access is granted.

Related services

Talk to an engineer about this

Thirty minutes, no slides. Bring the workload and we will tell you what we would do and what it would cost.

Talk to us [email protected]