Confluence Labs

Confluence Labs is a San Francisco AI research company (Y Combinator Winter 2026, backed by Paul Graham) focused on learning efficiency — building machine learning systems that learn from limited data and few experiments. Founded by Brent Burdick and Niranjan Baskaran, the lab works on hypothesis generation (using AI to design maximally informative experiments) and data-efficient modeling (combining large language models with discrete program search) to accelerate breakthroughs in data-sparse domains such as drug design, materials engineering, hardware, and physics discovery. The team reported state-of-the-art performance on the ARC-AGI-2 reasoning benchmark using LLM-driven program synthesis and open-sourced their solver on GitHub. Confluence Labs currently publishes no public API, developer portal, SDK, or OpenAPI surface; this profile captures verified company identity for the API Evangelist network.

Confluence Labs is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Machine-Learning, AI Research, and Program Synthesis.

Confluence Labs’ developer surface includes engineering blog and 2 more developer resources.

🌐 Visit website 📡 Source on GitHub

5.8/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

0 APIs

Company Artificial Intelligence Machine-Learning AI ResearchProgram SynthesisData Efficiency

Kin Score

Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0

Composite quality — 5.8/100 · minimal

Contract Quality 0.0 / 25

Developer Ergonomics 0.5 / 20

Access Clarity 0.0 / 20

Operational Transparency 0.3 / 13

Contract Governance 0.0 / 12

Discoverability 5.0 / 10

Agent readiness — 0/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/confluence-labs: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Resources

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: confluence-labs
name: Confluence Labs
description: Confluence Labs is a San Francisco AI research company (Y Combinator Winter 2026, backed by Paul Graham) focused
  on learning efficiency — building machine learning systems that learn from limited data and few experiments. Founded by
  Brent Burdick and Niranjan Baskaran, the lab works on hypothesis generation (using AI to design maximally informative experiments)
  and data-efficient modeling (combining large language models with discrete program search) to accelerate breakthroughs in
  data-sparse domains such as drug design, materials engineering, hardware, and physics discovery. The team reported state-of-the-art
  performance on the ARC-AGI-2 reasoning benchmark using LLM-driven program synthesis and open-sourced their solver on GitHub.
  Confluence Labs currently publishes no public API, developer portal, SDK, or OpenAPI surface; this profile captures verified
  company identity for the API Evangelist network.
url: https://raw.githubusercontent.com/api-evangelist/confluence-labs/refs/heads/main/apis.yml
deliveryModel:
  model: unknown
  open_source: false
  commercial: false
  callable_host: false
  label: Delivery model not determined — needs a product licence on record
  confidence: low
  source:
  - none
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://confluence.sh/logo-accent-dark-512.png
x-type: company
x-source: vc-portfolio
x-backed-by:
- y-combinator
- paul-graham
x-yc-batch: W2026
x-founders:
- Brent Burdick
- Niranjan Baskaran
x-tier: identity
x-tier-reason: research-lab-no-api
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
tags:
- Company
- Artificial Intelligence
- Machine-Learning
- AI Research
- Program Synthesis
- Data Efficiency
tags_raw:
- Company
- Artificial Intelligence
- Machine Learning
- AI Research
- Program Synthesis
- Data Efficiency
apis: []
common:
- type: Website
  url: https://confluence.sh
  name: Confluence Labs
- type: Blog
  url: https://confluence.sh/blog/introducing-confluence-labs
  name: Introducing Confluence Labs — SOTA on ARC-AGI-2
- type: GitHubOrganization
  url: https://github.com/confluence-labs
  name: confluence-labs on GitHub
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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