1 Category
EQUA AIMMS · LIVE IN PRODUCTION

The Agentic AI OS for Industrial Maintenance

Solving the Fault→Fix loop so your crew focuses on safe, on-time repair - not chasing parts and paperwork.

Approval-ready action in ~5 minutes. No chasing. No waiting.

AIMMS diagnoses root cause, sources the right part, and drafts an approval-ready repair packet - then writes every update back to your CMMS, ERP, and audit log automatically.

Grounded on manuals, BOMs & service history Overlays your CMMS & ERP - no rip & replace Every action receipted + logged
Signal Fault Detected Machine down, part request, or low stock alert
Process AIMMS Executes Agents diagnose, source parts, draft PO & WO
Output Repair Packet Ready Complete packet: diagnosis, SOP, PO, dispatch
TOTAL TIME: ~5 MINUTES · FULLY AUDITED
PO / RFQ issued
Work order updated
Parts reserved
Tech dispatched
Writes back to:
CMMS / EAM ERP Email Audit Log
IMPACT −0% unplanned downtime · Epcon Industrial
SPEED 0% faster quote & procurement cycles
EXECUTION ~5 min Fault→PO loop · fully audited
Deployed at Epcon Industrial Systems · site‑level · measured outcomes in Slide 5
INCIDENT THREAD // 3:14 AM CST LINE DOWN - UNPLANNED ROOT CAUSE: COORDINATION FAILURE

THE PLANT
FAILS AT 3:14 AM.

Downtime isn’t diagnosis. It’s coordination failure.

One fault triggers 5+ disconnected systems. The plant waits while humans manually reconcile CMMS, inventory, procurement, and tribal knowledge.

3:14 Alarm trips - tech opens work order CMMS
3:22 Calls expert - offline. No fix history. PEOPLE
3:31 Crib says “in stock” - shelf says otherwise INVENTORY
3:38 Requisition created - approval pending APPROVALS
3:47 Calls distributor - OEM lead time starts PROCUREMENT
Day 4+ Wrong part arrives - reorder - shift lost
RESULT: TIME LOST → SHIFT LOST → MARGIN DESTROYED
COORDINATION TAX SITE-LEVEL, ANNUALIZED
$0M Missing spares + write-offs per site ← No closed-loop between CMMS, inventory, and procurement Observed: SLB Technology Center (Shreveport) · site-level
$0K / DAY Waste from untracked spares consumption ← Manual counts miss consumption; reorders lag by days Observed: SLB Technology Center (Shreveport) · site-level
+2 WEEKS Delay from wrong part ordered ← Tribal knowledge offline; no cross-ref between asset + BOM Observed: Class I rail operator · site-level incident

These aren’t technology failures. They’re coordination failures.

CMMS
ERP
Human Router
Inventory
Manuals
Email
COORDINATION LATENCY - HUMAN BOTTLENECK

Systems of record track work. Humans execute work.
The gap between those two is where margin bleeds out.

Every asset-heavy operation loses margin here. You just don’t see it until someone counts.
Why Now

The One-Way Door

Three irreversible forces are converging on industrial maintenance faster than hiring can respond.

Workforce Exodus
0M maintenance jobs unfilled by 2033

Every 8 seconds a US manufacturing worker retires - taking the tribal knowledge that keeps plants running.

NAM / Deloitte & MI, 2024
Reindustrialization Mandate
$280B+ new industrial capex committed

The CHIPS Act, National Defense Industrial Strategy, and reshoring are scaling capacity at historic rates. The maintenance workforce to run it does not exist.

DoD NDIS 2024; White House CHIPS factsheet
Agentic AI Maturity
2025 AI crossed from answers to execution

Foundation models now reason, plan, and call tools. Automating fault-to-fix execution wasn’t possible 18 months ago - now it is.

Gartner Hype Cycle for AI, 2024; public model benchmarks
The Threshold

The fault-to-fix loop - triage, coordination, parts, close-out - still assumes a skilled human at every step. That assumption is now structurally broken.

Headcount won’t scale to meet demand.
The work still must.

Capacity: More wrench-time per shift - automate triage, coordination, and close-out so the same crew closes more work orders.
Cost: Fewer expedite cycles - route fault-to-fix internally, cutting outside service spend and emergency procurement.
Resilience: Faster recovery - encode tribal knowledge so the next shift doesn’t start from zero.
First-mover window is open now. Legacy vendors face years of re-architecture across data models, approval workflows, and integration surfaces - every quarter of delay compounds their disadvantage.
3.8M manufacturing jobs needed by 2033 - up to 1.9M unfilled¹
DoD NDIS ’24 names workforce readiness a national security priority²
Agent-native execution is production-ready - first-mover window is measured in quarters, not years³
NAM/Deloitte & MI Manufacturing Workforce Study, 2024 U.S. DoD National Defense Industrial Strategy, 2024 Gartner Hype Cycle for AI, 2024; industry benchmarks
The Mechanism - Fault → Fix

Not a Copilot.
A Governed Execution Engine.

Nothing executes until it clears a hard gate - policy, compliance, and human approval. Every action is logged and reversible.

Policy-Gated Actions Launch-Key Approval Receipts + Rollback
Context → Plan → Approval Gate → Executed Updates
01
Context Ingestion
“Line 3 down. Pump overheating + vibration.”
Manuals History BOM Inventory
Turns messy reality into structured context
02
Agentic Planning
Generates executable plans - not text.
Diagnose
Verify Parts
Draft PO/RFQ
Prep Updates
Example: Evidence-Linked Diagnosis
Seal wear causing friction heat; vibration = bearing play.
Recommended: Seal Kit SK‑481; alternate in stock.
03
Governance Airlock THE MOAT
Blocked Until Authorized
Policy checks (limits, roles, vendors) Safety + compliance rules Human approval required
Plan Ready: Pump #4 Repair
Action: Replace seal kit + recalibrate
Parts: 2 in stock • 1 substitute approved
Impact: Restore line in ~2 hours
✓ Execution Authorized
04
Execution + Audit
PO drafted + sent to vendor Logged
Work order updated in CMMS Logged
Tech scheduled + parts reserved Logged
Audit Trail (excerpt)
10:21:03 WO#1842 updated (diagnosis, tasks)
10:22:10 Parts reserved • RFQ sent +1 more
Faster Time-to-Fix
Full repair packet in minutes, not days of coordination
Lower Service Spend
Fewer contractor callouts, less expediting waste
Zero Unapproved Changes
Every execution gated, logged, and fully reversible
Chat Copilots Suggest · Summarize · Retrieve
Stop at advice AIMMS starts at governed execution →
Systems touched: CMMS/EAM ERP Email Tickets
EQUA // MEASURED PROOF // PRODUCTION
Epcon Industrial Systems OEM • Industrial Maintenance • Live since Nov ’25
Live in Production Paid Customer

30 days. Measured production outcomes.

From fault signal to completed fix - less downtime, faster quotes, every outcome measured.

Measured Outcomes - 30‑Day Production Window - Indexed Baseline = 100
▼ Reduction
↓32%
Unplanned downtime
Before
100
30 days
68
✓ Measured Epcon production ops • 30‑day window
▼ Reduction
↓80%
Quote cycle time
Before
100
30 days
20
✓ Measured Epcon production ops • 30‑day window
Financial Impact
Less unplanned downtime → higher throughput & on‑time delivery
80% faster quotes → service revenue captured in days, not weeks
Coordination labor eliminated → fewer contractor callouts & expediting costs
Paid production customer in 30 days - not a sandbox, not a POC.
Deployment Proof
Paying customerConverted in ≤ 30 days
Live productionReal ops, not a sandbox
Every action instrumentedTimestamped execution receipts
Approval‑Gated • Auditable
✓ Measured
Measurement Window 30 days • production
Downtime Delta ↓32% vs. baseline
Quote Cycle Delta ↓80% vs. baseline
Verified • Production Data
Outcome receipt - measured before & after on live operations
Expansion underway (Q2 ’26) - more assets, more workflows, same governance
Forward‑deployed sprint slots • outcome‑protected onboarding

Self‑funding in 30 days.
Payback before contract.

AIMMS captures waste already on your P&L - downtime, wrong parts, coordination labor - and converts it into measured savings that exceed the pilot fee.

Approval‑gated Full audit trail No rip‑&‑replace
Payback Physics
We fund AIMMS from waste already hiding on your P&L.
Waste Captured (30 Days)
Downtime eliminated
Stalled jobs resolved 3–5× faster
Wrong‑part spend cut
Reorders + expediting fees avoided
Coordination labor freed
Planner & buyer hours recaptured
Measured Proof
Executed actions loggedEvery email, PO, and update tracked
Cycle‑time deltasBefore vs. after, timestamped
CFO‑ready audit receiptsWhat changed, who approved, dollar impact
Net Payback
3–8× ROI
Captured savings − AIMMS fee
Pilot pays for itself before the contract starts. The math is auditable.
Every number traced to executed actions, timestamps, and audit‑linked receipts - not projections.
30‑Day Paid Proof Sprint
Production‑grade ROI in one month.

We deploy across your core fault‑to‑fix workflows, measure every outcome, and deliver a CFO‑ready ROI report on day 30.

Breakdown → Repair Packet Job Kit → Parts Purchasing → Vendor Email / PO Work Order Updates Inventory / Receiving
ROI Report
Audit‑linked • dollar‑quantified
Rollout Playbook
Repeatable multi‑site expansion plan
$5k–$25k pilot fee (by site complexity) - credited toward production contract
Zero risk: you keep every artifact, log, and playbook - even if you walk away.
Deployment Safety
1. AIMMS drafts
Actions prepared, payload staged
2. Human approves
Role‑based gate, nothing ships blind
3. Executes + audits
Email, PO, API - full receipt written
✓ Executed & logged
Your CMMS / ERP stays authoritative. Write‑back is staged, gated, and optional.

Every dollar of waste we capture is a dollar your CFO already approved spending.
AIMMS converts it into savings - before the contract starts.

MARKET • BUDGET • SCALE

A $698 B market. We convert maintenance OpEx into ARR.

Start inside existing budgets. Prove ROI at one site. Clone the audited playbook across plants.

Market Sizing

TAM
$698B
Global MRO spend (2024)
SAM
$1.2B ARR
~12 k NA plants × ~$100 k site ARR
SOM (24 mo)
$60M ARR
~500 sites × ~$120 k blended ACV
ACV band: $60 k–$240 k per site / year Source: industry MRO market reports, 2024

Budget Capture

Maintenance OpEx

Replace coordination, expediting & overtime overhead with governed digital execution - captured savings fund the subscription.

Before
100 %
After
−62 %
✓ OpEx-funded ✓ No IT budget fight ✓ Net-positive within 1 quarter

Scale Engine

  1. 0–14 days Land Shadow Mode live. ROI baseline set.
  2. 30–90 days Expand Full execution. Playbook delivered.
  3. 90–180 days Clone Multi-site rollout. Audit‑ready export.
  4. 180 + days Channel OEM / SI distribution Planned
Expansion trigger: margin + uptime proof → CFO‑mandated rollout

OpEx‑funded entry • No budget fight • Prove one site • Clone everywhere

Forward-Deployed & Shipping

Operators who ship.
Every fix governed. Every week closer.

Four forward-deployed builders embedded inside real plants - turning industrial chaos into production-grade outcomes, on site, every day.

Live in production - Epcon

Founding Team

Forward-deployed domain experts. Building & shipping inside real plants.

Srikant - CEO & Founder
Srikant
CEO & Founder
Forward-Deployed Ops

Enterprise systems veteran. Solving operational chaos in industrial workflows through on-site FDE - mapping processes to agentic AI workflows that keep technicians safe.

Lokesh - CTO & Co-Founder
Lokesh
CTO & Co-Founder
Agentic AI Architect

Forward-deployed AI engineer. Building enterprise-grade agentic AI with reliability, safety, and scalability at global scale.

Vivek - Founding Engineer
Vivek
Founding Engineer
Infra & Reliability

Production hardening specialist. Ensures data integrity and execution consistency under real-world industrial constraints.

Dhananjay - Chief Design Officer
Dhananjay
Chief Design Officer
Technician UX

Industrial UX expert. Turns complex maintenance workflows into trusted interfaces technicians adopt without training.

Next 12 Weeks - Execution Milestones

1

Standardize the Win Kit

Governed deployment packet + exportable proof of outcomes

Srikant · W0–3
2

Scale Production at Epcon

Full-plant coverage + measurable financial outcomes

Lokesh · W3–8
3

Parallel‑Site Launch

Templatized onboarding + repeatable deployment path

Dhananjay · W8–12

Ready to see it live? Let’s walk through production.

EQUA Website ↗