AI that learns your company.
Solves what your team can't.

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Persistent AI teammates that grow smarter with every interaction. Specialist agents that deploy that knowledge to solve problems your team would spend months on.
§ 01 — Our Mission
The most consequential gap
in applied AI today
is not capability —
it is memory.

And memory without action
is just storage.

Project Laplace builds agents that live inside your company. Every task they work on, every decision they observe, every problem they help solve — it all compounds into a knowledge graph that belongs to you. When something hard hits — an engineering failure, a market shift, a technical crisis — specialist agents are called in. They arrive already knowing your company. They debate, collaborate, and work autonomously until the problem is resolved. The longer they work with you, the more powerful they become.

A real employee gets better every year they work with you. They understand the institution, the blind spots, the unwritten rules. No current AI can do this. We are building the infrastructure to change that.

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Context retained
across sessions today
Memory substrate
under development
The ceiling on what
expertise becomes
§ 02 — About

AI teammates that get better
every single day
they work with you.

See the system →

Most AI tools forget everything when the session ends. Project Laplace agents do not. They work alongside your team daily, absorbing your processes, your culture, your institutional knowledge. That knowledge becomes the foundation for everything. When a hard problem needs solving, specialist agents deploy that foundation — collaborating, debating, and working autonomously across days until the job is done. No other AI system can do this because no other system has spent months learning who you are.

Our system operates across four layers: a Memory Substrate that never resets, a Reasoning Engine that deliberates continuously, an Agentic Cohort of specialized collaborators, and a Human Interface built on review primitives rather than chat bubbles.

We work in closed cohorts with a small number of research partners. Each cohort runs for a minimum of twelve months. The agents that emerge from that period carry institutional knowledge no prompt can replicate.

§ 03 — The Team
Naman Raghuvanshi
Naman Raghuvanshi
Founder & Director

Engineer by profession, builder by obsession. I spend most of my time teaching machines to think, designing AI products, and convincing computers to do things they probably shouldn't. Passionate about AI, startups, and building technology that feels a little magical.

Founder, Project Laplace