Industry AI agents

Agents fitted to the way your business actually runs.

We design, build and run custom AI agents for manufacturing, materials R&D, engineering, healthcare, finance and marketing teams. Each one is wired into your systems, tested on your own cases, and answers to the people who own the work.

Typical pilot: one workflow, 6–8 weeks.

Industries

Six fields, each with its own systems, rules and vocabulary.

A general-purpose assistant does not know your MES tags, your design codes or your compliance policy. Our agents are built around them from the start.

Agent run · example

Watch an agent work a real task

Every step is a tool call against your own systems, logged and reviewable. The result goes to a named person for sign-off.

Agent run · examplerun_7f3a21
TaskFirst-pass yield on Line 4 dropped from 97.8% to 93.1% since Tuesday. Find the likely cause.
  1. mes.query()
    Pulled 186 lots from Line 4 since Monday and split them into passing and failing groups by defect code.
  2. historian.read()
    Found reflow zone 6 running 4 °C above setpoint on 81% of failing lots, starting after Tuesday's maintenance.
  3. qms.search()
    Matched the pattern to a 2025 8D on the same oven, where a replaced thermocouple was miscalibrated.
Result · Ranked hypothesis report and verification plan sent to the Line 4 quality engineer for approval.
Approach

From one real workflow to an agent your team relies on.

Every engagement follows the same six stages. Nothing goes live until it has run beside your team and been measured against their work.

011–2 wks

Discovery

We sit with the people who do the work and map one workflow end to end, exceptions included.

021 wk

Design

We decide where the agent acts, where it asks, and where a person signs off, and agree how success is measured.

033–6 wks

Build and ground

We connect your systems and data, write the tools the agent uses and build an evaluation set from your real cases.

042–4 wks

Shadow run

The agent runs beside your team on live work without acting. We compare its output with theirs.

051–2 wks

Deploy

It goes live with permissions, rate limits and an audit trail, on-premise or in a private cloud if required.

06Ongoing

Operate and improve

We monitor quality, learn from corrections and extend to the next workflow.

Deep customization

What deep customization means in practice.

Your data, your rules

Grounded in your documents, systems and historical records, with your policies written in as hard constraints.

People sign off

Approval steps are designed in from day one for every decision that carries risk.

Measured on your cases

Each agent ships with an evaluation set drawn from your own work, re-run on every change.

Deployed where you need it

Public cloud, private cloud or on-premise, with the model provider you choose.

Engagements

Start small. Expand once the numbers hold up.

Production

3–6 months

Take a proven workflow live and connect it to your core systems.

  • Full system integration
  • Permissions, monitoring and audit trail
  • Team training and handover

Partnership

Ongoing

A standing team that builds and runs agents across departments.

  • Roadmap across business units
  • Shared agent platform and tooling
  • Quarterly review of results
Contact

Bring us one workflow.

Tell us how the work is done today and where it slows down. We reply within two business days with questions or a pilot outline.

Or emailcontact@freeseek.info