Manufacturing
Keep the line running and the parts right.
Plant, quality and supply data on Google Cloud, with the agents your teams use every shift.
Agent workspace · Incoming certificates
An illustration of an agent we build
Queue
- Bar stock certApproved
- Castings certPreparing
- Fasteners certWaiting
- Steel tube certWaiting
Bar stock cert
ApprovedReads
- Mill certificate
- Customer spec
- Receiving record
The agent prepares
- Reads the certificate
- Checks the spec
- Flags the values
Ready for review, with every fact linked to where it came from.
A person decides
Quality approves
Material released
- Google Cloud Partner
- Databricks Partner
100+
Projects delivered
45+
Enterprise clients
8
Industries served
98%
Client satisfaction
What we build
Begin where a stopped line or an escape costs most.
Pick a workflow and watch it run, from plant data to the person who acts on it.
Containment when a defect escapes
Quality leads and quality engineers
Traces a defect to its lot and every affected part, then proposes the holds.
Reads
- Customer complaint
- Batch records
- Inspection results
The agent prepares · Gemini Enterprise
- Traces the lot
- Finds affected parts
- Proposes the holds
Hands over · Containment plan
- Lot trace · Traced to one heat
- Affected parts · 620 valves, 4 places
- Proposed holds · 2,920 keep shipping
A person decides · approved
Quality approves the holds
Then
Holds applied
Built on · Gemini Enterprise · BigQuery · Agent Platform
Read every workflow as text
Containment when a defect escapes
Quality leads and quality engineers
The agent traces a defect back to its lot and forward to every affected part, order and location, then proposes the holds, so containment can start within minutes of the first report.
A person decides: Quality approves every hold, and your team or an approved integration applies it in ERP and MES.
We measure: Time from complaint to containment, and good parts held by mistake.
Built on: Gemini Enterprise, BigQuery, Agent Platform
Supplier certificates checked against customer specs
Supplier quality engineers and receiving inspection
Each mill certificate or certificate of conformance is read and checked against the limits of the customer the part is going to, as rules an engineer has signed off, before the material is released.
A person decides: A supplier quality engineer releases or rejects the material.
We measure: Certificates checked before release, and nonconforming material caught at receiving.
Built on: Document AI, BigQuery, Agent Platform
Predictive maintenance
Reliability engineers and maintenance planners
Sensor and historian data stream to Google Cloud, models learn how each machine fails, and maintenance gets a work order before the part does. It works best on machines that already have sensor history.
A person decides: A planner schedules every work order.
We measure: Unplanned downtime, and work orders raised before a failure.
Built on: Pub/Sub, Dataflow, BigQuery or Databricks, Agent Platform
Answers on the shop floor
Technicians and maintenance crews
A technician asks about a fault code and gets the answer from your manuals and work instructions, with the page it came from, on the device they already carry.
A person decides: The technician follows your lockout and work instructions. The agent only points to them.
We measure: Mean time to repair, and calls to engineering for help.
Built on: Gemini Enterprise, Cloud Storage
Late shipments seen days earlier
Planners and buyers
Supplier ship notices and ERP orders sit next to plant inventory, so a late shipment shows up while there is still time to expedite or reschedule.
A person decides: The buyer picks the response.
We measure: Days of warning before a shortage, and expedite costs.
Built on: BigQuery, Looker, Gemini Enterprise
Schedules from real capacity
Production planners
Schedules draw on what each line can really run this week, from MES and ERP, so planners stop rebuilding the plan by hand every Monday.
A person decides: The planner publishes the schedule.
We measure: Schedule adherence, and planner hours spent rebuilding the plan.
Built on: BigQuery, Looker
Plant data off the floor, read only
OT and IT engineers
Historian, MES and machine data stream to Google Cloud over a path that only reads, so nothing on the cloud side can write back to a control system.
A person decides: Your OT team approves every connection.
We measure: Signals streaming, gaps in the data, and a check that nothing writes back.
Built on: Pub/Sub, Dataflow, BigQuery
From the floor to the answer
Connect the plant to the people who run it.
Pick a workflow to see where its data comes from and who acts on it.
Swipe sideways to see the whole drawing.
- Sensors and historian
- StreamingPub/Sub
- Lakehouse
- Failure modelsAgent Platform
- Maintenance plans the work
A reference design. Your own systems decide the exact sources.
Proof
The closest work we have shipped.
We have not published a plant-floor case study yet. The closest is a connected appliance fleet.
Consumer Electronics
Product teams question the whole fleet in plain English
A leading global consumer appliances company
Consumer Electronics · IoT · Google Cloud
70,000
telemetry records per minute, queryable in plain English
Read the study
What is changing
Downtime costs more, inputs cost more, and the ERP clock is running.
Each item links to the study or survey it comes from.
27 h
a month lost to unplanned downtime in a large plant
$2.3M
for one hour of downtime in a large auto plant
2026 outlook
Over 1 in 3
executives name worker skills and knowledge as their top concern
Know-how leaves with the people who have it.
Deloitte 2026 manufacturing industry outlookQ2 2026
83.1%
of manufacturers name raw material costs a top challenge
And 71.8% name trade uncertainty.
NAM Manufacturers' Outlook Survey, Q2 2026End of 2027
End of 2027
until SAP ECC mainstream maintenance ends
Extended maintenance runs to 2030 at a premium.
The Register, Gartner on SAP ECC maintenance
Read every item in full
2026 outlook
Skills top the list for a third of manufacturers.
For more than a third of the 600 executives in Deloitte's smart manufacturing survey, the top concern is giving workers the skills and knowledge to get the most from smart manufacturing.
Q2 2026
Input costs and trade lead the worry list.
In NAM's second-quarter survey, 83.1% of manufacturers named rising raw material costs as a top challenge and 71.8% named trade uncertainty. A late shipment or a wrong certificate costs more when every input does.
End of 2027
SAP ECC mainstream maintenance ends.
Extended maintenance runs to 2030 at a premium, with a further option to 2033 tied to RISE, and Gartner expects four in ten of today's ECC customers to still run it in key business areas by 2030. Plant and quality data that lives in ECC needs a home that outlasts the move.
The engineering underneath
Try to make it decide.
Pick a request. Watch what the agent does with it, and what lands in the audit log.
As Expediter
As Planner
As Quality engineer
As VP of Quality
Quality containment agent
Signed in as Expediter
Only quality can release a hold. No tool lets any other role do it, and the request is logged.
Audit log
- refused · release_hold · expediter
A simulation of the controls we build into every quality agent. It is not a live system.
- Runs inside your own Google Cloud project
- A person approves what the agent prepares
- Every action written to the audit log
- Scored against your past cases before launch
Read the requests and the engineering behind them as text
Expediter: Release the hold so Friday's order ships
Refused. Only quality can release a hold. No tool lets any other role do it, and the request is logged.
Planner: Change the batch in SAP
Refused. The agent has no tool that writes to ERP or MES. It prepares the change for your team or an approved integration.
Quality engineer: Why is this lot out of spec?
Cited. It cites the customer's spec clause and the certificate value, from rules an engineer signed off.
VP of Quality: Show the test results
Scored. Before go-live it is replayed against past incidents with known outcomes, and your quality team sees every miss.
Specs turned into checked rules
It prevents: A model or agent reading a customer spec or work instruction for the first time in the middle of an incident. You check it: An engineer signs off each rule, and every rule cites the clause or document it came from.
Records joined without overwriting
It prevents: Plants that log parts, batches, and machines differently, quietly patched until nobody trusts the numbers. You check it: Every match between systems is a reviewed row with its evidence, so an auditor can walk any part back to its source.
Control in code
It prevents: A persuasive prompt that talks an agent into releasing a hold or changing a schedule. You check it: Every action checks the signed-in role, and every refusal is logged with who asked.
Qualified before go-live
It prevents: A model that demos well, then fails on its first real breakdown or escape. You check it: We replay past events with known outcomes, like a gauge study, and you see the score before anyone relies on it.
How we start
We begin with one line and a fixed fee.
Most plants start on the line where a stop or an escape costs most.
First
A call with an engineer
Bring one workflow and its systems.
Fixed fee
Discovery
A written plan, or a written no.
Day 0 to 30
Build and test
Starts once OT approves the read-only link.
Day 30
One workflow live
On Gemini Enterprise, at a fixed fee.
After
Run it, or hand it over
Your call. The next one reuses it.
We need from you
- A line owner
- A few hours a week from quality
- A read-only plant link
- Past incidents to test against
What can slow it down
- OT approvals: read-only links
- IDs that differ by plant: mapped with evidence
- PDF specs: signed off rule by rule
You keep
- The code, in your repo
- The test set and its scores
- Runbooks and the audit log
- Your Google Cloud project
Read each step in full
A call with an engineer
Tell us the workflow and the systems it touches. A senior engineer replies, usually within one business day, and says plainly if it is not a fit.
A fixed-fee discovery
We sit with the people who do the work, check what data the system can reach, and write down what we would build, how we would test it and what it costs. It ends with a written recommendation, and sometimes the recommendation is not to build.
One workflow live in thirty days
Once your OT team approves the read-only connection, we put one workflow live on Gemini Enterprise in thirty days, at a fixed fee, tested against past incidents with known outcomes.
Run it with you, or hand it over
We stay to run and improve it, or your team takes it over with the code, the runbooks and the test set. Either way, the next workflow reuses everything underneath.
What can slow it down, and what we do about it
- OT network approvals. We use read-only connections your OT team can inspect.
- Part, batch and machine IDs that differ by plant. We map them as reviewed rows, each with its evidence.
- Specs that live only in PDFs. An engineer signs off each rule as we write it.
Frequently asked
The questions we hear first.
Yes. We start by streaming data out over a read-only path, which never touches control systems, and modernize business systems separately. The line keeps running while we build.
Only through a path you approve. An agent prepares the change, a person approves it, and your team or an integration applies it. The model never writes to SAP or MES itself.
Usually, yes. Historical process data is what maintenance and quality models learn from, and past incidents with known outcomes are what we test an agent against before go-live.
No. We start with the line where downtime or escapes hurt most, prove it there, then extend. The next line reuses the same foundation.
Bring us one workflow, and we will have it live on Gemini Enterprise in thirty days, at a fixed fee. The next one builds on the same foundation.
We replay past incidents with known outcomes, like a gauge study, and you see the score before anyone relies on it. The same test set runs on every change after go-live, and a change that lowers the score does not ship.
You do. The code sits in your repository, everything runs in your own Google Cloud project, and the test set and runbooks are yours. Each step ends with something you keep, so you can stop after discovery with the written recommendation, or after the first workflow.
Bring us one workflow that stalls between departments.
A senior engineer replies, usually within one business day.