AI Advisory for Manufacturing · A Service Offering

AI for manufacturing, from ideation to the plant floor.

A contractual advisory offering for manufacturers navigating the AI journey — an honest readiness picture across IT and OT, an executable roadmap, and AI that is responsible, auditable, explainable, and secure at the forefront.

01 · Readiness 02 · Roadmap 03 · Pilot-to-Production 04 · Embedded Advisory
The Manufacturing Dilemma

The mandate is clear. The path isn't.

Four patterns we see across plants, supply chains, and service operations under pressure to "do AI" — each an argument for starting with advisory rather than procurement.

01

Pilot purgatory

The vision demo wowed the ops review. Two years on it still watches one line at one plant — MES integration, guardrails, and unit economics were never scoped.

02

Shadow AI on the floor

Engineers paste process specs into public chatbots; buyers draft supplier terms with them. Your process IP is leaving the building, ungoverned.

03

The accountability gap

Customers, auditors, and regulators are asking where AI touches quality and safety decisions — questions with no owner and no evidence trail.

04

The readiness illusion

Decades of IT and OT grew apart: ERP here, MES there, tribal knowledge on the floor. Use cases get funded before anyone checks the data can carry them.

The cost of getting this wrong isn't a failed pilot — it's two lost years while competitors take out cost you can't.
The Manufacturing Value Map

Where AI pays off on the P&L.

Four domains where AI moves real manufacturing numbers — working capital, throughput, cost of quality, and service margin.

Working capital · Resilience

Supply chain intelligence

Vendor rationalization, sourcing copilots, supplier risk scoring, PO workflow automation, and demand–supply scenario planning.

Throughput · OEE

Plant operations

Machine-event triage, downtime root-cause copilots, shift-handoff summaries, and natural-language access to SOPs and maintenance history.

Cost of quality · Audit

Quality & compliance

Deviation analysis, audit-ready document retrieval, complaint categorization, nonconformance trend detection, and regulated-workflow guardrails.

Revenue · Service margin

Commercial & service

Proposal and quoting acceleration, field-service knowledge assistants, customer-issue correlation, and post-sale support automation.

Your shortlist will differ — surfacing it, and ranking it honestly, is exactly what the readiness sprint and roadmap are for.
Step 01 · Manufacturing AI Readiness

Know where you stand before you spend.

A two-to-three-week, fixed-fee diagnostic that replaces optimism with evidence — and gives the board a defensible starting point. Structured interviews with plant, quality, sourcing, and IT leadership; technical deep-dives into the IT/OT estate; scoring against our manufacturing benchmark.

How the sprint runs

Week 1

Interviews with ops, quality, sourcing & IT; artifact review

Week 2

Deep-dives: data estate, ERP/MES landscape, OT security

Week 3

Scoring, gap analysis, board-ready readout

Readiness scorecard — six dimensions · illustrative

What gets scored

Data estate (IT + OT)52
Systems: ERP · MES · SCADA61
Talent & skills44
Governance & risk33
Security posture (incl. OT)68
Use-case portfolio47
Illustrative scores only. Shown to demonstrate the instrument, not to represent any organization. Each dimension is scored 0–100 against our manufacturing benchmark, and every gap is mapped to a costed remediation.
Fixed fee. Fixed calendar. If we find you're not ready, the readout says so — and says exactly what to fix first.
Step 02 · Roadmapping, Ideation to Production

A roadmap that survives contact with the floor.

Five phases, four executive gates. Investment tracks evidence rather than momentum — and nothing advances without the numbers to justify it.

Phase 1

Ideate

Use-case discovery with the people who own throughput, quality, and spend — not just IT.

Phase 2

Prioritize

Portfolio ranked by value, feasibility, risk, and data readiness — across plants.

Phase 3

Prove

Pilot on one line or one category, with production criteria set on day one.

Phase 4

Productionize

ERP/MES integration, OT-aware hardening, MLOps / agent-ops, and cost controls.

Phase 5

Operate & scale

Monitoring, evals, and operator enablement — then plant-to-plant rollout.

◆ Gates

Executive decision gates

Continue, redirect, or stop. Four gates between ideation and scale; each one is a real exit ramp, priced in from the start.

Typical arc: prioritized portfolio in 6 weeks · first pilot decision in one quarter · first production workload inside two.
The Trust Architecture

AI your customers can audit.

Three properties we engineer into every recommendation, architecture, and pilot — because in manufacturing, trust is contractual: customers audit you.

Humans in command

Responsible

Human-in-the-loop on consequential calls — releases, dispositions, supplier awards. Bias and neutrality testing against your quality and sourcing mandates. Policy packs mapped to your reality: ITAR, export control, customer data.

For you: AI accelerates your engineers and operators — accountability never leaves them.

Evidence by default

Auditable

Append-only logs of every prompt, retrieval, and decision. Lineage from sensor and system-of-record to output. Evidence packs for customer audits, ISO surveillance, and regulators.

For you: When the auditor asks "why", you have the receipts.

Answers with receipts

Explainable

Citations to SOPs, specs, and history on every AI answer. Decision traceability from output back to source and policy. No black-box recommendations in quality or safety workflows.

For you: No disposition you can't defend — to a customer or a regulator.

Security at the Forefront

Secure by design, down to the floor.

In manufacturing, AI's attack surface reaches the floor — new identities, new data flows between IT and OT, new paths to your process IP and your suppliers' terms. We treat security as the first gate every recommendation must clear, not a review at the end.

Shadow-AI discovery & containment

Find ungoverned use in engineering and procurement; convert it to protected paths.

Process-IP & data protection

Designs, recipes, and supplier terms — redacted, encrypted, least-privilege.

Identity for humans and agents

Non-human identity, scoped credentials, and full attribution of every action.

Prompt-injection & model threat defense

Input shielding, output filtering, and abuse and anomaly monitoring.

OT/IT segmentation & sovereignty

AI workloads on your side of the Purdue line — VPC, on-prem, or air-gapped.

Continuous assurance

Evals, red-teaming, and drift monitoring as an operating rhythm rather than an event.

Aligned to your frameworks: NIST AI RMF · IEC 62443 · CMMC · ITAR / EAR · SOC 2. The result is an AI posture your CISO and your plant engineering co-sign — and an architecture that passes customer, procurement, and audit review the first time.
Engagement Model

Contract for a step, not a leap of faith.

Four fixed-scope engagements, each separately contracted with named deliverables. You re-decide at every gate — momentum is earned, never assumed.

Step 01

AI Readiness Sprint

2–3 weeks · fixed fee
  • Readiness scorecard across IT & OT
  • Security & governance snapshot
  • Board-ready executive readout
Step 02

AI Roadmap

4–6 weeks
  • Prioritized manufacturing use-case portfolio
  • 90-day plan & 12-month arc
  • Governance & security baseline
Step 03

Pilot-to-Production

8–12 weeks
  • Pilot on one line, one plant, or one category
  • Guardrail & integration architecture
  • Go / no-go evidence for the board
Step 04

Embedded Advisory

Ongoing · quarterly
  • Fractional AI leadership & CoE stand-up
  • Quarterly board reporting & reviews
  • Continuous assurance: evals, red-teaming
Every step stands alone — and every step de-risks the next. Most manufacturers begin with the sprint.
Outcomes

You leave with decision-grade artifacts.

Not observations — instruments. Each artifact is built to move a specific decision: fund, fix, pilot, or stop.

Readiness scorecard

Where you stand — IT and OT, scored honestly against benchmark.

Use-case portfolio

Ranked by margin impact and feasibility, with named owners and source systems.

Executive roadmap

A sequenced 90-day plan and 12-month arc, decision-ready.

Governance baseline

Policies, human-in-the-loop gates, and audit posture defined before the first build.

Pilot blueprint

Production criteria set from day one, with metrics, guardrails, and integration points.

AI operating model

Centre-of-excellence design, plant roles, and decision rights.

Questions you'll answer with confidence

Q1

Where does AI move throughput, quality, or spend first — and what is it worth?

Q2

Is our IT/OT data estate ready? If not, what exactly is the fix?

Q3

Can we defend AI-assisted quality and sourcing decisions to customers and auditors?

Q4

What will it cost — and when does it pay back?

Q5

Who owns AI risk — corporate and plant — and how is it monitored?

Why MTekLabs

Advice from people who ship AI for a living.

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.

Practitioners, not analysts

We design, build, and operate production agentic-AI systems. Every recommendation arrives pre-tested against deployment reality.

Manufacturing fluency

We frame AI around throughput, sourcing, quality, maintenance, workforce enablement, and operating margin — not tech for its own sake.

Vendor-neutral

Provider-agnostic across Bedrock, Vertex, Azure OpenAI, and on-prem. We optimize for your outcomes, not a reseller margin.

Built to hand over

Enablement is the deliverable: your people, your operating model, your capability — stronger after every phase, independent at the end.

Credentials, not case studies. Production AI platforms designed, shipped, and operated in regulated industries — including MatryxAI, the agentic sourcing and procurement platform we built for manufacturers, with ITAR-grade controls in live use.

Start with one plant, one process, one measurable win.

One 30-minute executive session is enough to scope your readiness sprint. Two to three weeks later: an honest IT/OT scorecard, a board-ready readout, and a clear decision on what comes next.

Scope a readiness sprint or email info@mteklabs.com

Responsible · Auditable · Explainable · Secure from the floor up

← All advisory services