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R / 00Research

Four fields, one practice.

We pick problems where software, data and AI meet — and work on them until they hold up in production.

01

Software

Production-grade systems built to be read, audited and maintained for years, not demos.

  • Developer tooling
  • APIs & SDKs
  • CLI & agent interfaces
02

Data systems

Storage, indexing and retrieval that keep structure, ownership and access boundaries intact.

  • Vector retrieval
  • Hierarchical data
  • Ingestion pipelines
03

AI technologies

Applied machine intelligence that is scoped, observable and provider-independent.

  • Retrieval-augmented generation
  • Model orchestration
  • Agent tooling
04

Experimental tools

Small instruments and prototypes that test an idea fast and end up shaping the next system.

  • Prototypes
  • Interfaces
  • Open experiments

§ 01Open questions

What we're working on.

  1. Q1

    How should AI retrieval respect the access boundaries of a real organization?

  2. Q2

    How can agents use private knowledge without stepping around permissions?

  3. Q3

    What does it take for an AI system to stay independent of any single model provider?

  4. Q4

    How small can a tool be and still change the way a team works?

Have a problem worth researching?

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