Industrial operations

Can you tell us what is actually happening?

As enterprise organizations rebuild critical industrial capacity, the problem is not only knowing where to invest. It is knowing, in a provable way, what is actually happening across the companies, suppliers and systems operating that capacity. That is the layer we are building: the trusted evidence and coordination layer for complex industrial operations.

What we can give you

Visibility into the actual operating state of a complex American industrial system, drawn from the systems it already runs, with every figure traced to the dated record that produced it and every disagreement between records surfaced rather than averaged away.

Why a layer above, and why neutral

The systems of record have an incentive to preserve their own version of reality. We are deliberately provider-neutral and sit above them. Our job is not to become another system of record. Our job is to reconcile the records, preserve disagreement, establish evidence, and make the resulting state usable by humans and AI.

Reconcile the records. Every system is read; none is rewritten.
Preserve disagreement. A contested figure stays contested, both sides shown with their dates, until the person with authority settles it.
Establish evidence. Every figure opens to the dated record and the owner that produced it.
Make the state usable. Routed to the human with authority to act, and served as governed context to whichever AI you choose.

What it lets you confirm

Production is actually happening. Confirmations from the execution system, reconciled against orders, shipments and the ledger, not a status report.
Critical suppliers are qualified. The qualification record from the quality system, joined to the purchasing record, so an order to an unqualified source is visible before it ships.
Bottlenecks are emerging. Where demand, capacity and supply records diverge over time, named by work center, part and supplier, with the owner who can act.
Capacity is being utilized. Planned against actual, from the planning tool and the floor, side by side.
Supply-chain dependencies are understood. The supplier graph mapped from the records you hold, down to raw-material origins where a record exists, with single sources, single regions and domestic capacity marked. Where no record exists, EOS says so rather than guessing.
Reported numbers can be independently substantiated. Every number in a report opens to its source record and its timestamp; a number that cannot is marked as unsubstantiated.

Mapping and mitigating supply-chain vulnerability, with intelligence that is governed

EOS Intelligence maps the industrial system from its records: which parts come from which suppliers, which suppliers depend on which sub-tier sources and raw materials, which of those are single points of failure, which capacity is domestic and which is not, and where lead times, quality holds and open purchase orders are moving in a direction that will become a constraint. It proposes; it does not decide. Every finding carries its evidence, every recommendation names the person with authority to act on it, and nothing is written back to any system of record. Where the chain runs past the records you hold, the map ends with a marked gap rather than an assumption.

Five questions a serious buyer asks, and the answers

1. Can you see across the entire supply chain, not just inside one company?: Yes, to the edge of the records. EOS connects read-only to each company's systems under that company's own tenancy, and a shared object (a part, a purchase order, a shipment) that appears in two companies' records is reconciled across them, each side keeping its own authority to settle its own record. Sub-tier suppliers appear wherever a record names them: purchasing, quality, customs, certificates of origin. Where the chain runs past the records anyone holds, the map ends with a marked gap, which is itself a finding.
2. Can you distinguish fact from inference, especially when AI is involved?: Every statement carries one of nine labels: observed, derived, inferred, assumed, scenario, recommendation, decision, action, outcome. A figure read from a record is observed; a figure computed from records is derived and shows its calculation; anything a model concludes is inferred until a record substantiates it, and it is never shown as the same thing as a fact. The label travels with the statement into every report and every AI answer.
3. Can you prove every important claim, not just draw a picture?: Every figure opens to the system, the record, the timestamp and the owner that produced it, and the chain of those references is hash-linked so it cannot be quietly edited. A number that cannot be traced is marked unsubstantiated rather than shown as if it were the same as the rest.
4. Can this work at industrial scale, not a 200-person company?: It is designed for estates of dozens of systems of record and the volumes those systems hold: connectors read incrementally, the estate is partitioned by tenant and by system, and reconciliation runs on changed records rather than re-reading everything. The scale of a specific estate is established in the assessment with the estate's own volumes, and written into the targets, so it is a measured statement rather than a brochure claim.
5. Can we use it without replacing anything we already have?: That is the design. Nerio never writes to a system of record and never asks you to move data out of one; it reads, reconciles, and routes. Every system you run today stays the system of record for what it holds. The connectors are read-only by construction, and the setup is a session, not a migration.

Proof in a real industrial environment

The public record will carry the first live customer result with that customer's consent, on the same page that already carries every claim we have made in order. Until it does, every figure on this page is simulated and says so. The path to that first record is the commercial model: a $15,000 assessment that connects read-only to a real estate and writes auditable targets, a $50,000 pilot with the assessment credited in full and the $35,000 balance fully refunded if the mutually agreed target is not achieved by day 90, and a commercial term paid as a share of value that finance verified. We prefer that order to a case study we could not prove.

What we publish about scale, security and deployment

Read-only by construction. Connectors read; nothing is written back; no credential EOS holds can change a record.
Isolation. Each organization is a tenant with its own data, evidence, decisions, keys and audit log; nothing crosses tenants except a shared object both parties chose to reconcile.
Evidence you can audit. The evidence chain is hash-linked and exportable in one file: findings, decisions, evidence, connectors, and the credit ledger.
Intelligence under governance. Models propose and never decide; every recommendation names the human with authority; you may bring your own model provider; your data is not used to train anyone's model.
Deployment. Managed, with encryption in transit and at rest, and a term that ends by itself with a thirty day export window. Deeper architecture is shared under agreement, not on a public page.

A second simulated finding: the shape of what reconciliation surfaces

Simulated. Not a customer. Every figure is synthetic.

A company with $3 billion of operations across 14 systems of record. In the first reconciliation pass EOS surfaced 37 material disagreements. Five affected production. Two represented critical supply-chain risks. One was a single-source dependency nobody had a record of.

The disagreement	The evidence	What management changed	90 days later
A machined housing showed 6,400 units available in the ERP and 2,900 on the floor in the MES.	ERP stock record Apr 12, 9:14 AM; MES count Apr 12, 6:00 AM; 3,500 units on a quality hold recorded only in the quality system.	Released the hold decision to the plant quality lead with authority; the ERP now reads the hold from the quality record.	Production schedule rebuilt on real availability; two missed ship dates avoided in the following month.
A brake actuator had one qualified supplier in the quality system and three in procurement.	Qualification records for one; purchase orders to three; two orders in flight to unqualified sources.	Stopped the two orders; qualified a second source through the quality process, closed by record.	All actuator receipts from qualified sources; the single point of failure gone.
A specialty alloy came from two distributors who shared one upstream mill, invisible to both purchasing and planning.	Certificates of origin on receipts named the mill; neither procurement record carried it.	Added the mill to the supplier graph as a single upstream source; opened a second mill qualification; held eight weeks of safety stock while it ran.	Second mill qualified; exposure recorded as mitigated and verified against receipts.
Working capital: $11.2 million of inventory bought against a demand plan the sales system had already revised down.	Planning demand as of Mar 1; sales forecast as of Mar 18; purchase orders raised between the two dates.	Aligned purchasing to the sales forecast at the record level; canceled what could be canceled.	$7.9 million of the working capital released and verified in the ledger; the value share computed on that figure at the published marginal schedule.

Mitigation tracking

Every vulnerability the map surfaces becomes an item with an owner, a mitigation, a due date and a state: open, mitigated, or verified. Mitigated is a claim; verified is a record. An item moves to verified only when the record that would prove it (a qualification, a receipt from the new source, a stock level, a ledger entry) exists and has been read. The mitigation ledger is part of the same evidence chain, so ninety days later "did it work" is a question the records answer.

A simulated engagement, end to end

Simulated. Not a customer. Every figure below is synthetic, generated to show the shape of an engagement and what the measured result looks like.

Step	What it looked like in the simulation
The manufacturer	A large discrete manufacturer with six plants, two of them acquired, running seventeen systems of record: three ERPs, two MES, two WMS, one procurement suite, one quality system, one PLM, one planning tool, and seven departmental tools that had become systems.
The conflicting facts	EOS read all seventeen and surfaced 2,140 contested figures in the first pass: the same supplier under nine names, 312 purchase orders whose quantity or value differed between procurement and finance, and 41 parts whose on-hand count differed between the WMS and the ERP by more than a shift's consumption.
The bottlenecks found	Three. A single-source machined casting whose only qualified supplier was at 96 percent of stated capacity; a heat-treat work center at plant 4 that planning believed had 20 percent headroom and the floor showed had none; and a resin whose two suppliers shared one upstream producer, a single point of failure nobody had a record of.
The exposure	Working capital of $6.8 million tied up in inventory bought against the wrong demand signal, and $4.2 million of revenue at risk in the quarter from the casting constraint. Both figures traced line by line to the records that produced them.
What management changed	Qualified a second casting source (the quality record, not a promise, closed the item); re-sequenced plant 4 around the real heat-treat capacity; dual-sourced the resin upstream; retired the nine supplier duplicates to one record with the authority to change it named.
The measured result	Ninety days later, measured on the same records: contested figures down from 2,140 to 260; the casting constraint cleared with on-time delivery at plant 4 up from 71 to 93 percent; $5.1 million of the working capital released; the resin single point of failure gone. The value share for the year would be computed on the verified $5.1 million and the revenue protected, at the published marginal schedule.

This is the shape, not a claim. A real engagement starts with the $15,000 assessment that writes the targets your finance function can audit, then the $50,000 pilot, with the assessment credited in full; the $35,000 balance is fully refunded if the mutually agreed target is not achieved by day 90. Request an assessment The commercial model. Supply chain in EOS.