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TalentXM

Industries · Manufacturing

Connect the shop floor to the systems that run the business.

We work where operational technology meets ERP and maintenance systems: machine health, technical documents and the integrations between them. Engineers and planners approve every action.

Discuss Your AI PrioritySee the use cases

Use-case map

Manufacturing workflows we work on.

Where we have built and tested work in manufacturing, with the systems involved and the control that keeps a person in charge.

  • Machine health monitoring

    Validated POC
    Systems
    Equipment telemetry, anomaly model, Copilot Studio, CMMS
    Control
    Planner approves every work order
    Delivery
    Capability pod
    Measures
    Alerts confirmed by engineers; lead time on test data

  • Chemical and technical document extraction

    Validated POC
    Systems
    Document AI, quality records
    Control
    Qualified reviewer approves extracted data
    Delivery
    Project delivery
    Measures
    Field accuracy; time per document

  • ERP and MES integration

    Available
    Systems
    Workato, n8n, ERP and MES APIs
    Control
    Monitored integrations with named owners
    Delivery
    Managed service
    Measures
    Failed transactions; time to recovery

Featured agents

Agents for manufacturing.

Filter the catalogue
Validated POC

ML Model + assistant

Machine Health Monitoring

Problem
Telemetry sits in historians and spreadsheets.
How it works
An anomaly detection model watches equipment telemetry. An assistant explains what changed and drafts a maintenance request for a planner to approve.
Industry fit
Manufacturing · Asset operations
  • Anomaly detection
  • Microsoft Copilot Studio
  • CMMS write-back
View agent
Validated POC

Solution Accelerator

Chemical-Document Interpretation

Problem
Engineers read long documents to find a few values.
How it works
Reads chemical and technical documents, extracts the fields engineering and quality teams need and shows the source for every value.
Industry fit
Manufacturing · Quality & engineering
  • Document AI
View agent

Standards and practices

  • Read-only OT connections
  • Approval before write-back
  • ISA-95 aware integration design

What we do not claim

  • Our agents do not control equipment or replace safety systems.
  • Agents shown here have been validated as proofs of concept, not rolled out across plants.
  • We do not name client organisations without written permission.

Pod composition

A typical manufacturing pod.

A senior lead who knows the industry, plus a small execution team sized to the workflow.

Lead layer

Manufacturing operations lead

Owns the brief, the quality bar and the fortnightly readout.

  • Execution layer

    OT and data engineer

  • Execution layer

    ML engineer

  • Execution layer

    Integration engineer

  • Execution layer

    Reliability analyst

Roles vary by engagement. A pod is sized to the workflow, not to a headcount target.
See all delivery models

FAQ

Manufacturing: common questions.

Do you connect directly to PLCs?

We prefer to read from historians or gateways your OT team already trusts, with read-only access.

Can this run at the edge?

Yes. Models can run close to the equipment, with summaries sent to the cloud.

How much data do we need?

Several months of telemetry for the assets in scope is a good start. We check data quality in the first sprint.

Discuss Your AI Priority

Talk to us about manufacturing.

Tell us about the workflow and the systems involved. A named person will reply.

The workflow, the systems involved and what a good outcome looks like.