R42 Industrial AI Fund I, LP

Investing in the intersection of Physical AI and infrastructure.

We back early-stage companies at the intersection of artificial intelligence and physical-world industrial operations — led by operators who have built, scaled, and exited industrial technology.

Pre–Seed–A
Investment stage
focus
50+yr
Combined operator
experience, GP team
5–7yr
Industrial AI
M&A exit horizon
01 — Thesis

Industrial AI is not a software category. It is an infrastructure investment thesis.

Artificial Intelligence

Intelligence layer

  • Edge AI inference
  • LLM / NLP for OT data
  • Computer vision
  • Multi-agent orchestration
  • Reinforcement learning
Industrial Technology

Infrastructure layer

  • Private 5G / CBRS
  • OT cybersecurity
  • Edge computing platforms
  • Industrial data fabric
  • Connected Worker 2.0
The compounding result

Physical AI enabled industrial operations

Predictive maintenance · Smart manufacturing
Digital twin + reasoning
Why now

Three forces are converging on the plant floor.

01

Industrial transformation

Decarbonization mandates, manufacturing labor shortages, and decades-old control systems reaching end of life are forcing non-discretionary upgrades across heavy industry.

02

AI capability explosion

LLMs now extract value from unstructured OT data, edge inference runs at industrial-grade latency, and computer vision delivers quality and safety at the machine level.

03

Connectivity revolution

Compute is migrating to the machine. Private 5G, OPC UA FX for deterministic control, and IT/OT convergence are eliminating the silos that held industrial data captive.

02 — Approach

Attack the physical AI infrastructure gap. Sequenced by market readiness.

Industrial organizations are spending aggressively on digital transformation, but the binding constraint is foundational infrastructure. We invest across the full stack — funded where the market is ready.

50–60%

Phase 1 · Foundation

System migration · OT security · Edge networking · Modern historians · Data brokers
Spending now. Non-discretionary.
Allocation
30–35%

Phase 2 · Intelligence

Knowledge graphs · AI inference · Edge orchestration · Connected Worker 2.0
Growing. Accelerating as Phase 1 matures.
10–15%

Phase 3 · Autonomy

Multi-agent AI · Robotics · Autonomous ops · Digital twin + reasoning
Early-stage. High optionality.

The vast majority of industrial organizations are still in Phase 1. Those attempting to skip ahead are failing.

03 — The edge

Operational diligence no generalist can match.

Industrial decisions are driven by reliability, safety, and total cost of ownership — not feature velocity. Companies that cannot speak the language of operational technology get blocked at the plant gate.

/ 01

We walk the plant floor

We assess technology stacks, evaluate OT integration, and pressure-test commercial models against real operator requirements — 50+ combined years of hands-on industrial experience.

/ 02

We stay disciplined

A rigorous scoring model derived from field intelligence. We invest only where foundational infrastructure readiness supports the use case. No hype-cycle bets.

/ 03

We invest early, across the lifecycle

Among the first investors at pre-seed and seed, with follow-on reserves for top performers and continuation rights through a growth vehicle.

/ 04

We carry exit relationships

Direct relationships with strategic acquirers — Honeywell, ABB, Siemens, Schneider Electric, Emerson, Shell, BP, Republic Services — across a 5–7 year industrial M&A horizon.

04 — Target sectors

Aging infrastructure, labor pressure, and data trapped at the edge.

Five verticals that share the same structural pattern — and the same opening for physics-aware AI.

01

Energy & Utilities

Grid intelligence · predictive maintenance · demand forecasting

02

Manufacturing & Automation

Autonomous factories · robotics intelligence · IIoT analytics

03

Chemicals & Advanced Materials

Catalyst design · pyrolysis optimization · carbon recovery

04

Industrial Safety & Sensing

Gas detection · thermal anomaly · toxic exposure monitoring

05

Circularity & Waste-to-Value

Recycling automation · materials recovery · emissions reduction

Portfolio

Building conviction in the companies shaping the industrial stack.

Fund I's portfolio is in formation.

05 — The team

Operators who have built, scaled, and exited industrial technology.

Prabhu Soundarrajan
Co-General Partner

Prabhu Soundarrajan

  • 20+ years automation leadership
  • Honeywell, $700M P&L
  • 2024 President, ISA (17,000 members)
  • Operating Partner, Kingston Capital
  • 30 patents in industrial technologies
Steve Toteda
Co-General Partner

Steve Toteda

  • 30+ years communications & industrial systems
  • CEO / President / VP-GM scaling roles
  • Exits: Komodo, Dust Networks, Cooper Industries
  • Fortune 100 industrial OT network
  • Existing R42 advisor & operator
Dr. Ronjon Nag
Founder & GP, R42 Group

Dr. Ronjon Nag

  • Founder exits to Motorola, BlackBerry, Apple
  • Silicon Valley Engineering Hall of Fame
  • 40-year innovation pedigree
  • Cambridge PhD · MIT MS
  • Stanford Distinguished Fellow
Exit DNA

A return to what drove the strongest exits — AI applied to physical systems.

Speech & handwriting recognition
→
Motorola
Speech recognition platform
→
Apple
Cradlepoint — 4G / 5G
→
Ericsson
HD maps for autonomous systems
→
Luminar
Predictive supply chain
→
E2open
Perspectives

Field intelligence from the plant floor.

We publish what we learn — from the ARC Forum, from diligence, from operators who run the assets. Followed by the people building and buying industrial AI.

Thesis

Industrial AI is not a software category.

It is an infrastructure investment thesis. The binding constraint inside the plant is not the model — it is the network, the data fabric, and the edge underneath it.

Read on LinkedIn May 2026
Diligence

Why most AI gets blocked at the plant gate.

Industrial buyers decide on reliability, safety, and total cost of ownership — not feature velocity. Founders who cannot speak operations never make it past the pilot.

Read on LinkedIn Apr 2026
Field notes

The companies skipping Phase 1 are the ones stalling.

Most industrial organizations are still funding foundational infrastructure. Selling autonomy into a plant that is not ready is how good technology dies in procurement.

Read on LinkedIn Mar 2026
Follow the fund on LinkedIn
06 — For founders

Building at the intersection of AI and industry? Tell us.

We invest at pre-seed, seed, and early Series A in companies applying AI to physical industrial operations. If that is you, send us the essentials. Every submission is reviewed by a partner.

Submissions are treated as confidential. We aim to respond within two weeks.

Thank you — we have it.

Your submission is in front of the partners. If there is a fit with the fund's thesis and current pipeline, one of us will be in touch directly.

Get in touch

Backing the companies building the industrial stack.

Co-General Partner
Steve Toteda
steve@r42industrial.com
Co-General Partner
Prabhu Soundarrajan
prabhu@r42industrial.com
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R42 Industrial Ventures · R42 Industrial AI Fund I, LP