Agent Hive for manufacturing

See the full picture before you act.

Bring plant data, procedures and engineering judgement together before anyone decides what happens next.

Book a demo See a battery example

A factory event is investigated, reviewed by an engineer and prepared for action.

Start with the evidence in one place.

Agent Hive pulls the relevant signals, documents and past decisions into one case your engineers can check.

MES, QMS, historian, engineering documents and expert input move through Agent Hive to investigation, engineer review and an approved next step.

Nothing is hidden. Engineers can trace every recommendation back to its source.

Choose a workflow your team already owns.

Start with a real production or engineering question. Agent Hive follows the evidence and fits the way your team reviews decisions.

Production issue investigation

Find out what changed, and why it matters.

Agent Hive links the deviation to process history, recent changes, current procedures and similar cases. Engineers review the likely causes.

Deviation, context assembly, hypothesis testing, engineer review and containment.

Battery cell manufacturing equipment in a controlled production environment

Battery manufacturing example

Bring live plant data and engineering knowledge together.

This proposed deployment connects equipment events, procedures, recipes, specifications and genealogy in one plant knowledge graph.

Live plant events and engineering documents move through discovery into a context graph, agent reasoning and engineer review.

This is an anonymized look at the proposed deployment. It describes the scope and architecture only; no production results are claimed.

Read the full story

Deploy it where your plant needs it.

Keep Agent Hive inside the plant network, or use a controlled gateway for model access. Your data and audit trail stay under your control.

What runs together

Plant context
Live systems, engineering documents and what your team has learned before.
Agent coordination
Different agents work on the same question and share what they find.
Testing
Real questions, reviewed answers and checks before release.
Controls
Permissions, engineer sign-off and a record of every decision.
Deployment
Run locally or use approved model endpoints through a gateway.

Keep everything on the plant network

Run the graph, agents and models locally.

For plants where process recipes and operational data cannot leave the site.

Plant users, Agent Hive runtime, context graph and local models operate inside a no-egress plant network.

What manufacturing teams usually ask us.

Most teams start with one difficult decision, the evidence behind it and the people who need to sign it off.

Does Agent Hive replace our MES, QMS or historian?

No. Those systems remain the source of record. Agent Hive brings the relevant data and documents together when your team needs to investigate a question.

Can an engineer check how the answer was reached?

Yes. Engineers can open the sources, follow the reasoning, correct mistakes and approve the next step.

Can we keep everything inside the plant network?

Yes. Agent Hive can run fully air-gapped. A hybrid option is also available when approved model access is allowed through a controlled gateway.

Where should we start?

Choose one important decision that currently takes too much searching and coordination. Make sure the source systems, reviewers and success criteria are clear.

Is the battery story a completed customer deployment?

No. It is an anonymized account of a proposed scope and architecture. We do not claim production results from it.

Bring us a real manufacturing problem