Less Tooling. More Building.

Low friction, high impact, no bullsh*t, practical agent tooling for pragmatic engineering teams.
$ claude "Let's build something amazing!"
→ Using zeeq to find relevant canonical guidance...
→ Identified key guidance: 2 documents, 7 sections, 4 code snippets, 15 memories
→ Combobulating your feature following guidance...
→ Your new feature is ready ✓
→ Using zeeq code review with guidance...
→ Reviewer findings: 1 CRITICAL, 1 MAJOR, 2 MINOR. Here are the recommendations...
→ All findings addressed! ✓
→ Session telemetry recorded! ✓
Manage code review findings: https://app.zeeq.ai/web/code-reviews
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Trusted by high velocity, agent-first engineering teams

Chander Ramesh
Gary Chao
Charles Chen
Tom Österlund
Lefan Tan

Chander Ramesh

CTO at Motion

I'm  a  believer  because  I've  experienced  it.    This  is  a  boiling  frog  type  situation  -  your  code  quality  will  slowly  get  worse  over  time  and  it'll  be  terrible  without  it. 

A low ceremony toolset for agentic teams.

Zeeq plugs into existing workflows and thrives in heterogeneous environments with different models, harnesses, and agent surfaces to lift code quality, consistency, and observability. No change in workflow, no special harnesses; just low-friction, high impact results.
  • Indexed, chunked, searchable knowledge base
    Use a shared knowledge base that grounds both code review and code generation, ensuring that agents are following best practices and enterprise standards.
  • "Closed loop"", mixture-of-experts code reviews
    Use out-of-the-box and easy to tune agent code reviewers that are grounded in the same knowledge base and used consistently in your coding loop and in your PR.
  • Targeted retrieval
    Efficient, targeted, semantic retrieval of only the relevant sections of knowledge and code snippets that improve agent adherence and performance.
  • High visibility and observability of outcomes
    See that text in your corpus is actually shaping agent output and your codebase to keep your team aligned with best practices.
  • Iteratively self-learning
    Compiles a deep, semantic understanding of your product, your features, your code as it reviews code so agents actually know what to build
  • Built for teams
    Designed to be low-ceremony, easy to adopt, and operate in agentic teams that are using heterogenous agent harnesses, AI-enabled runtimes, and LLMs

Frequently asked questions

What if everyone on your team could ship code like your most senior engineers?

Zeeq is the tool that lets agents write smarter code that bridges a semantic understanding of your product with a technical understanding of your codebase and your enterprise ecosystem so every member of your team can ship confidently with AI.
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