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Company Brain for Industrials

The machine records everything. Nobody knows why.

ERP, maintenance, MES, quality spreadsheets and shop-floor sensors each hold a piece of the same asset and the same batch. Strattum resolves that as one governed context, inside your plant, and serves it to the AI your teams already use.

Better decisions on the floor, with the right context

Reach the cause without the four-hour meeting

Asset, work order, operator, shift and batch linked to each other. Unplanned downtime stops being a meeting without a conclusion and becomes a query with the history attached.

Trace the batch end to end

Raw material, invoice, supplier certification and finished product resolved as the same chain. The customer’s audit stops turning into three weeks of digging.

Run inside the plant, network or no network

Industrial networks are hostile and cloud-only does not serve the shop floor. The deployment is hybrid: edge in the plant, syncing when the link comes back.

2026 PILOT · 2027 SCALE

We are building industrials as our second vertical.

Strattum started in financial services: fintechs, mid-sized banks and credit unions. But the governed-context thesis holds as well for equipment data as it does for customer data. By 2027 we intend to be the reference for agentic AI in Brazilian metalworking.

To get there, we are selecting 3 pilot companies in 2026: mid-sized metalworking firms (R$ 300M–2B in revenue), running TOTVS or SAP in production, willing to build the full industrial playbook with us. Symbolic cost, on-site FDE, visibility in the market.

Put my company forward →

Four everyday questions,
and the answer with its source attached.

Each of them today ends in a root-cause meeting, an engineer who remembers a similar stoppage, or a report built by hand. The figures below are illustrative scenarios.

Case 01 · Maintenance and assets

Why this machine stopped again

The work order sits in the maintenance system, the parameter in the MES, the batch in the ERP and the operator on the roster. They arrive as one case, with the earlier stoppage that had the same pattern.

  • Asset, work order, parameter and shift in one context
  • The comparable earlier stoppage comes with what fixed it
  • The answer does not depend on who was on shift
Case 02 · Quality and complaints

The root cause of the customer complaint

The batch complained about, the machine parameter at the moment it was produced and the raw material that went into it arrive together. The investigation stops beginning with asking who was on the line.

  • Batch, parameter and raw material resolved as one case
  • The process deviation appears beside the specification
  • Fewer complaints repeating the same cause
Case 03 · New operator

The first shift without stopping production

The equipment procedure, what to do on each alarm, when to call maintenance and what must be recorded. What is shadowing an experienced operator today becomes an on-demand answer, drawn from procedures the plant already has.

  • Assembled from the plant’s procedures in force
  • Serves new and contract operators without stopping the line
  • Every item points back to the procedure it came from
Case 04 · OEE and availability

The OEE that dropped with nobody knowing where

Availability, performance and quality read together by line. When OEE falls while output holds steady, the responsible component arrives tied to the data that exposes it.

  • Availability, performance and quality in one context
  • The component that dropped is pointed at as soon as it appears
  • Every number carries the system it came from

Your whole company context
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