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.

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.
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.

MFG4 scenarios · 2 cases

Advanced Manufacturing

Agents that read MES, SPC and QMS data, trace yield losses to root cause, draft 8D reports and plan changeovers, with engineers signing off every change.

  • Yield-drop root-cause analysis
  • Production scheduling and changeover planning
  • 8D, PFMEA and SOP drafting from defect records
  • Maintenance work-order triage from sensor alarms
Read the analysis
MAT4 scenarios · 2 cases

New Materials R&D

Agents that turn scattered experiments, papers and instrument files into structured data, then propose the next formulations and flag patent risk before scale-up.

  • Formulation and process-window recommendation
  • Literature and patent mining into composition–property datasets
  • Characterization data interpretation and ELN structuring
  • Freedom-to-operate pre-screening
Read the analysis
ENG4 scenarios · 2 cases

Engineering Design

Agents that check drawings against codes, generate parametric models from briefs, trace design changes into quantities, and draft RFIs and submittal reviews for engineers to sign.

  • Code-compliance review of drawings and calculations
  • Parametric model generation from design briefs
  • Design-change impact and bill of quantities
  • RFI, specification and submittal drafting and review
Read the analysis
MED4 scenarios · 2 cases

Healthcare Services

Agents that run follow-up, documentation, intake and payer paperwork around care, with every clinical judgment left to licensed clinicians.

  • Post-discharge and chronic-disease follow-up
  • Discharge summary and referral letter drafting
  • Patient intake and appointment routing
  • Prior authorization and claims coding support
Read the analysis
FIN4 scenarios · 2 cases

Fintech

Agents that prepare KYC files, triage AML alerts, draft credit memos and map regulatory change, with every decision left to an authorised officer.

  • KYC/KYB onboarding review
  • AML alert triage and SAR narrative drafting
  • SME credit memo drafting
  • Regulatory change impact analysis
Read the analysis
MKT4 scenarios · 2 cases

Marketing

Agents that draft on-brand content with claim checks, read campaign data across platforms, research target accounts and localize campaigns, with marketers approving what goes live.

  • On-brand content production with claim checks
  • Campaign analytics and budget reallocation proposals
  • Account research and personalized outreach for B2B pipeline
  • Localization of campaigns across languages and markets
Read the analysis
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