AI hype meets
industrial reality.
The world is flooded with AI hype. Impressive demos and polished consulting decks often fail when they encounter legacy systems, fragmented data, and real industrial operations.
In brick-and-mortar industries, software that “mostly works” isn't good enough. Managing $100M+ in revenue demands systems that integrate deeply with workflows, infrastructure, and data.
Not generic software. A custom execution layer built for real operations, deployed, measured, and owned by your team.
Laurus Labs:
compliance,
reimagined.
In life sciences, compliance isn't optional. It's the foundation of trust. Yet most Quality teams still battle disconnected systems and manual reviews that slow progress.
Laurus Labs partnered with us to automate their entire QC documentation workflow. We unified data across their systems and built inspection-ready pipelines aligned with FDA and global GxP, turning compliance from a burden into a competitive advantage.
Strategy meets
execution.
A focused discovery sprint pinpoints the biggest levers. Then we move: connecting systems, deploying models, operationalizing insights. Our goal is lasting capability in your team, not dependence on us.
Break data silos
Most companies don't lack data. They lack connectivity between systems.
Operational data lives across siloed databases, products, and spreadsheets. We build the integration layer that transforms fragmented data into usable intelligence for real decisions.
Target high-leverage bottlenecks
The largest inefficiencies live in repetitive workflows and fragmented decisions.
We focus on problems where automation and AI deliver immediate financial value: repetitive workflows, manual reporting and fragmented decision-making.
Deploy, not just advise
Our Forward-Deployed Engineers work directly inside your operations.
We integrate with real systems, real data, and real workflows. Instead of producing recommendations, we build and deploy production systems that solve problems generic software cannot.
Research pedigree.
Operator discipline.
Ravi operates at the intersection of frontier research and industrial-scale execution. As a founding engineer at Common Sense Machines (acquired by Google DeepMind), he architected foundational AI models and led the core products that scaled to more than half a million global users.
His research pedigree includes cutting-edge publications applying AI to small-molecule drug discovery, alongside specialized work in Reinforcement Learning developed with Doina Precup (Google DeepMind) at McGill.
As founder of Industrial IQ, Ravi leverages this technical and business mastery to deploy AI-driven automation that unlocks measurable competitive advantages for complex industries.
Ready to bring data and AI into your operations?
We are partnering with future-thinking industrial leaders to turn AI into measurable business outcomes.