PARTNER WITH SOLEMI
SOLEMI / INDUSTRY FIELD GUIDEMANUFACTURING

Make everyfactory signaleasier to act on.

Your client already has production data, maintenance history, quality records, and experienced operators. Solemi helps your firm turn those disconnected signals into controlled agents that prepare the next decision without taking control away from the plant.

EXPLORE ALL INDUSTRIES ↗
Stainless steel process equipment, valves, and gauges in a clean production system
STAINLESS / PROCESSPHOTO / POLICARPO BRITO
A CNC spindle positioned over a marked metal surface
CNC / PRECISIONPHOTO / DANIEL SMYTH

Connect factory data so operators can act sooner.

Bring ERP, MES, machine, quality, and operator context into one workflow so plant leaders can investigate a constraint before it costs another shift.

Start where people lose time rebuilding operational context.

These are starting patterns, not preselected products. Discovery determines whether the workflow, data, controls, and expected value justify engineering an agent.
01

Production exception agent

Watch schedule, material, work-center, inventory, and quality signals; assemble the likely constraint and present viable next actions to the supervisor.

HUMAN AUTHORITYThe production owner approves schedule or operating changes.
02

Maintenance preparation agent

Combine condition signals, asset history, manuals, work orders, and parts availability to prepare diagnosis and a complete technician brief.

HUMAN AUTHORITYQualified staff retain every safety-critical decision.
03

Quality investigation agent

Trace specifications, inspection records, deviations, supplier lots, and prior corrective actions to prepare a reviewable investigation.

HUMAN AUTHORITYQuality leaders approve disposition and corrective action.

How the work could take shape.

These representative engagements combine recurring patterns from industrial AI programs into original scenarios a partner can use to understand the problem, proposed build, rollout, and accountable decision owners. They are not named client work or promised outcomes.
IMPLEMENTATION 01 / LARGE AUTOMOTIVE MANUFACTURERDATA + AGENT ENGINEERING / ENGINEER REVIEW
EARLIER ANSWERSTarget outcome: begin each investigation with a prepared evidence trail instead of rebuilding context by hand.

Test-fleet investigation system

The operating need
Vehicle engineers were losing critical time joining test telemetry, service notes, technical documentation, and prior investigations before they could evaluate an anomaly.
What the team built
A delivery team connected the approved sources and built specialist agents to retrieve evidence, compare test conditions, surface plausible causes, and assemble a cited investigation brief.
How it went live
The team started with one test program, evaluated the briefs against completed engineer investigations, improved retrieval and traceability, and expanded only after the evidence held up.
Who stays responsible
Engineers initiate the investigation, inspect every cited source, reject unsupported hypotheses, and own the final technical conclusion.

Composite scenario based on public implementation research. It is not a named Solemi client engagement.

IMPLEMENTATION 02 / MID-MARKET COMPONENTS MANUFACTUREROPERATIONS + INTEGRATION / SUPERVISOR DECISION
ONE OPERATING VIEWTarget outcome: give plant leaders the context behind a line stop, scrap event, or yield change while it can still be acted on.

Factory exception investigation agent

The operating need
Plant teams could see individual ERP, MES, quality, and machine signals, but answering a basic operational question still required several people and multiple system exports.
What the team built
The team resolved product, work-center, shift, and asset identities across systems, then engineered an agent that traces an exception and prepares likely contributors with supporting records.
How it went live
One production line became the proving ground. Historical events were replayed first, live recommendations followed, and each unsupported connection was used to improve the data model.
Who stays responsible
Supervisors and qualified operators choose the action. The agent cannot change a schedule, machine setting, quality disposition, or safety-critical instruction.

Composite scenario based on public implementation research. It is not a named Solemi client engagement.

The agent is only as useful as the plant context it can safely reach.

Discovery begins by locating the minimum sources needed for one workflow, resolving identifiers and ownership, and defining which actions remain recommendations, require approval, or are prohibited.
01ERP + planning
02MES + work-center events
03Machine + OT history
04Quality + specifications
05Maintenance + parts
06Roles + approval limits
A clean modern production plant with machinery and process infrastructure
PLANT / OPERATIONSPHOTO / PETER XIE

The best manufacturing partners already understand the systems or the operation.

If your firm already implements the ERP, improves plant performance, manages infrastructure, or advises the leadership team, you have the context and trust required to find the first defensible workflow. Solemi supplies the PM, data, product, and agent engineering behind your brand.

Own the transformation behind the recurring plant exception.

Partner with Solemi to determine whether the data, process, controls, and economics support a real agent engagement. Your firm owns the client and the offer; our white-label team engineers and delivers it.

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