MTekLabsAI engineers trust.
Customers can audit.
For manufacturers and their supply chains. We find where AI frees up working capital, raises throughput and cuts the cost of quality, prove it on one line or one category, then scale it plant to plant.
For plants, supply chains and service teams. Process IP protected by design.
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Sources readSupplier bidsQuality historySanctions lists
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AI recommendationAward to two suppliersScores computed by code, not generated
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Human decisionBuyer signs the awardNamed buyer · time · reason recorded
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RecordEvidence chain kept for auditEvery source and score traceable
The mandate is clear.
The path isn't.
Plants, supply chains and service teams are under pressure to “do AI.” Four problems keep getting in the way:
Pilots stuck on one line
The vision demo impressed the ops review. Two years on it still watches one line at one plant, because MES integration, controls and costs were never planned.
Process IP in public chatbots
Engineers paste process specs into public tools; buyers draft supplier terms with them. Your know-how leaves the building.
No one owns the risk
Customers, auditors and regulators ask where AI touches quality and safety decisions. No one has the answer, or the evidence.
IT and OT that don't connect
ERP here, MES there, know-how in people's heads. Projects get funded before anyone checks the data can support them.
The real cost isn't a failed pilot. It's two lost years while competitors take out cost you can't.
Results you can see
on the P&L.
Four areas where AI moves real manufacturing numbers: working capital, throughput, the cost of quality and service margin.
Supply chain
Lower supplier risk and less cash tied up in inventory.
For example: supplier and ownership screening, tracking what moves and what builds up across sites, sourcing assistants, purchase-order automation, and demand and supply scenarios.
Plant operations
Less downtime and more output from the same lines.
For example: machine-event triage, help finding the root cause of downtime, shift-handoff summaries, and plain-language search of SOPs and maintenance history.
Quality & compliance
Catch deviations sooner and get through audits faster.
For example: deviation analysis, nonconformance trends, complaint sorting, audit-ready document search, and guardrails on regulated workflows.
Commercial & service
Faster quotes and better service margins.
For example: faster proposals and quotes, field-service assistants, spotting patterns in customer issues, and post-sale support.
Your shortlist will be different. Finding it, and ranking it honestly, is what the Readiness Sprint is for.
Engineers stay in charge.
Every answer shows its work.
In manufacturing, trust is contractual: your customers audit you. We build three things into every recommendation, design and pilot.
People make the consequential calls
An engineer or buyer signs off on releases, dispositions and supplier awards. We test against your quality and sourcing rules, and map policies to ITAR, export control and customer data terms.
AI speeds up your engineers and operators. Accountability stays with them.
Every answer shows its sources
Each answer cites the SOPs, specs and history it used. No black-box recommendations in quality or safety work.
No disposition you can't defend to a customer or a regulator.
Evidence ready for any audit
Every prompt, source and decision is kept in an append-only log, traced from sensor and system of record to output. Evidence packs for customer audits, ISO surveillance and regulators.
When the auditor asks why, you have the receipts.
Your process IP stays yours.
AI opens new paths into the plant: new identities, new data flows between IT and OT, and new ways to reach your designs and supplier terms. Security is the first gate every recommendation must clear, not a review at the end.
- Find unapproved AI useSpot it in engineering and procurement, and move it onto protected tools.
- Protect designs and recipesDesigns, recipes and supplier terms redacted, encrypted and shared only with those who need them.
- An identity for every person and agentScoped access, and every action traced to who or what took it.
- Defend against attacks on AIGuard against prompt injection and misuse, and filter what goes in and out.
- AI on your side of the lineWorkloads stay on your side of the IT/OT boundary: in your cloud, on-premises or air-gapped.
- Continuous testingAccuracy checks, red-teaming and drift monitoring as a routine, not a one-off.
The result: an AI setup your CISO and your plant engineering can both sign, designed to pass customer, procurement and audit review the first time.
Start with one line.
Or one category.
A fixed-fee Readiness Sprint gives your board a defensible starting point in two to three weeks. If you're not ready, the readout says so, and says what to fix first.
- Q1Where does AI move throughput, quality or spend first, and what is it worth?
- Q2Is our IT and OT data ready? If not, what exactly is the fix?
- Q3Can we defend AI-assisted quality and sourcing decisions to customers and auditors?
- Q4What will it cost, and when does it pay back?
- Q5Who owns AI risk, at corporate and in the plant, and how is it monitored?
Typical arc: ranked use cases in about six weeks, a first pilot decision within a quarter, and a first workload in production within two.
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Step 1 · 2–3 weeks · fixed feeReadiness SprintIT and OT data, ERP, MES and SCADA, and OT security, scored
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Step 2 · 4–6 weeksRoadmapUse cases ranked by value, feasibility and risk, across plants
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Step 3 · 8–12 weeksPilot-to-ProductionOne line, one plant or one category, connected to your ERP and MES
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Step 4 · OngoingEmbedded AdvisoryRoll out plant to plant, with your team
Advice from people
who ship manufacturing AI.
Most AI advice comes from people who have never run a model in production, or stood on a plant floor. Ours comes from doing both.
- Manufacturing fluencyWe frame AI around throughput, sourcing, quality, maintenance and operating margin.
- Vendor-neutralBedrock, Vertex, Azure OpenAI or on-premises. We work for your outcome, not a reseller margin.
- Built to hand overYour people and your operating model get stronger at every step, and can run on their own at the end.
- Proven in live useWe built MatryxAI for manufacturers. It runs with ITAR-grade controls.
Find the right supplier. Faster.
AI agents discover and screen suppliers, including sanctions checks. Scores and award splits are computed by code, not generated, and buyers sign every award.
See supply chain risk build up.
Know what is moving through your supply chain, where it is going and who is behind it. Tributary flags regulated materials building up across sites and related companies, shipments that change course, and suppliers whose owners are on sanctions lists.
Explore TributaryIllustrative. These figures come from MTekLabs platform benchmarks and early pilots. They are not a guarantee of results in your environment. We check every target against your own data during the Readiness Sprint, and set a baseline before any number is claimed.
One plant.
One process.
One measurable win.
Bring us the process that costs you the most. We'll show you what AI can safely do with it.
From first call to a clear decision.
- 1A 30-minute callWe pick one plant, line or sourcing category.
- 2A fixed-fee sprintScope, team and dates agreed up front.
- 3Your readout in 2–3 weeksAn honest IT and OT scorecard, and a board-ready readout. You decide what comes next.