The AI that Builds AI

“When AI couldn’t be trusted, we built the system that could.”
Annika Rao-Monari, Founder

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Vision

Our Vision

To power a world where any organisation can turn intent into intelligence — instantly, reliably, and without friction.

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The Architect
of the Technology

Annika founded CleeAI to solve what most missed, AI didn’t just need better models — it needed better infrastructure so it could be deployed faster and for any use case.

Frustrated by slow, fragile pipelines and unexplainable outputs, Annika designed and built the Large Knowledge Model (LKM) - a system that turns enterprise intent into trusted, compliant AI.

"When AI Couldn't Be Trusted, We Built the System That Could Be." - Annika Rao-Monari.

Her vision powers everything we build today.

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Our Mission

We're building AI that builds AI — turning enterprise intent into deployable, explainable, and compliant systems that scale.

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AI That Creates AI

We believe a more intelligent world is a better one. We're building AI that builds AI, but also consider our mission fulfilled if our technology helps others scale intelligence for a better world.

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Faster Time-to-insight

100%

Traceable outcomes

98%

Faster AI Development

87%

Less Engineering Hours

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The Team Behind the Tech

Meet the people shaping trusted AI — driven, diverse, and dedicated to turning vision into reality.

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Annika Rao-Monari

Co-Founder & CEO

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Colin Richardson

Co-Founder & CMO

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Andrew Bryant

Head of Engineering

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Ramesh Bhimji

Chief Financial Officer

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Casey Attebery

Senior Data Scientist

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Yuree Hong

Growth Marketing Manager

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Soumya Kavi

VP Product

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Ali Tavakoli

Data Scientist

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Lauren Lu

Product Designer

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Rob Taylor

Senior Frontend Developer

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Lillian Higgs

User Experience Researcher

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Gabriel Kiss

Frontend Developer

Latest from Our Blog

Explore how the world’s most ambitious teams are building with CleeAI — and what it means for the future of enterprise AI.

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5 Enterprise AI Use Cases You Can Deploy in Days—Not Months

Most enterprise AI projects move at the pace of procurement—not innovation. Here are five high-impact use cases you can actually deploy this quarter—with explainability, compliance, and scale built in from day one.

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How to Build an Enterprise AI Stack That Doesn’t Break in Production

Enterprise AI doesn’t fail in the lab. It fails at rollout. Here’s how to build an AI stack that holds up under real data, real users, and real stakes—without adding another Frankenstein pipeline to your architecture.

Build Enterprise AI - Fast

Turn business use cases into deployable, compliant AI—built in minutes by your team, not months by external vendors.

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