IndustriesManufacturing

The line tells you it will fail. Nobody is reading it.

Vibration, temperature, and scrap data already show the drift, but they sit in systems nobody has time to read before the next shift. We build models that flag it, small language models that read your manuals and work orders, and agents that draft the work order for the planner who signs.

Start with a Decision BlueprintTalk to the engineer
FIG. 1 · Asset risk and draft work orderIllustrative
Press line 3Main hydraulic pump

Model · risk of unplanned stop, next 7 days

High

  • up: Vibration band energy vs. 30-day normal
  • up: Case temperature at the same load

SLM · manual

  • §7.3Shaft seal replacement, summarized in Turkishpump service manual p. 41

Agent · draft work order (not released)

  • TaskInspect shaft seal, replace if leaking; check coupling alignment
  • PartsSeal kit in stock (2), reserved
  • Estimate2.5 h, 2 technicians
  • Model
  • SLM
  • Agent

DecidesMaintenance planner

From the use case: Maintenance on the bottleneck line

Use cases in this sector

The desks we build for here.

  • ModelsSLMsAgentic AI

    Maintenance on the bottleneck line

    TodayThe press fails on the night shift; its vibration had changed weeks before.

    With the systemRising stop risk flagged, with a draft work order and a proposed slot.

    Maintenance planner decides

  • ModelsSLMsAgentic AI

    Visual inspection

    TodayInspectors check every part under a lamp; night shift misses more, and each nonconformance report takes half a day.

    With the systemA draft nonconformance report with its evidence, ready for a hold-or-release call.

    Quality engineer decides

  • Models

    Quality and yield

    TodayScrap is found at the end of the line, and nobody knows which setting caused it.

    With the systemThe setting most likely behind the scrap, with a window to test.

    Process engineer decides

  • SLMsAgentic AI

    Customer complaint 8D

    TodayContainment is due tomorrow, and the evidence is in five systems.

    With the systemEvidence from five systems in one 8D draft.

    Quality engineer decides

These use cases describe systems we build, written from how these desks work. They are not past client projects: no client names, no results.

The sector

What is different here

The way of working stays the same. These four things change with the sector.

Data
Sensor and machine data, maintenance history, inspection images, batch records, and manuals, often in another language; shift records name people.
Who signs
The maintenance planner, quality engineer, or process engineer. The agent drafts the work order and the 8D report; a person releases every work order and signs every 8D, and no model writes setpoints.
Where it runs
On your servers or your cloud account.
Rules you work under
  • Your customers' quality requirements and their 8D format
  • Your plant's safety rules: a person owns every stop on the line
  • Personal-data rules: the models watch assets, not operators
  • Equipment makers' manuals stay for internal use

Where it runs, what it connects to, and who can reach it

Kinds of AI

The three kinds of AI here

Each works on its own; they stack where the decision needs more.

  • Estimate

    Machine-learning models

    Models estimate the risk of a stop, a defect, or scrap from your machine and batch data.

    How it works

  • Understand

    Small language models (SLMs)

    Small language models read manuals, work orders, and complaints, and a vision-language model (VLM) reads inspection images.

    How it works

  • Prepare and act

    Agentic AI systems

    Agents draft the work order or the 8D report and stop where a planner or engineer must sign.

    How it works

Equalize the gap.

Bring one decision. Leave knowing the first step.

A short description of the decision is enough; no confidential records.

Start with a Decision BlueprintTalk to the engineer

https://eqlx.ai/industries/manufacturing · Printed copy; the website is the current version.