AI Workforce Platform that optimizes AI systems with human feedback data sourced and verified from a community of domain-experts.
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🚀 Introducing JoinClaw — your own private OpenClaw, powered by your private data.
Run Agentic AI without exposing your personal machine or sacrificing control.
Built for builders, teams, and organizations that want more control, privacy, and ownership over their AI systems.
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Hot take:
By 2027, “we have evals” will sound like “we have tests.”
Table stakes.
The teams building eval infrastructure now will own the next decade.
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Be honest — how does your team evaluate AI today?
100%
Vibes ✨
0%
Public benchmarks
0%
Internal QA
0%
Structured human evals
1 votes • Final results
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85% of business data is unstructured.
85% of AI projects fail before production.
These two facts are related.
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Joinable by the numbers:
→ 1,400+ AI Builders
→ 400+ AI systems
→ 1,000,000+ verified contributions
The last mile, crossed at scale.
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Fine-tuning a private LLM on your documents?
The model learns your data.
Humans verify it learned the right things.
Skip the second step and you ship the first step’s mistakes.
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Software can A/B test its way to quality.
Robots can’t A/B test their way to safety.
Embodied AI needs human evaluation before deployment — not after incidents.
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Internal AI assistants fail differently:
Wrong answer to a customer = bad review.
Wrong answer to your CFO = bad decision.
HR, legal, finance, support — evaluate accordingly.
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Your RAG app is only as good as its worst retrieval.
Automated metrics miss what humans catch:
wrong context, confident nonsense, subtle staleness.
Human evals close the gap.
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Proof-of-human-work:
Verifiable evidence that real, qualified people evaluated your AI.
The receipts — on-chain.
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“Where did this training data come from?”
If your vendor can’t answer that, you have a problem.
If it’s on-chain, you have an answer.
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Trust in AI data shouldn’t require trust in a vendor.
Every Joinable contribution is recorded on-chain:
who · what · when · verified
Audit trails > promises.
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AI bug bounties:
Point our tester community at your AI app.
They break it.
You fix it.
Before your users find out.
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Calling all domain experts 📣
Lawyers. Doctors. Engineers. Analysts.
Your judgment is training data — and AI needs what you know.
Get paid to make AI better. Link in bio.
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Not all human feedback is equal.
Joinable contributors are verified, ranked, and reputation-scored.
Quality in → quality out.
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Behind every reliable AI system is a network of humans:
testing · scoring · correcting · verifying
1M+ verified contributions and counting.
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AI systems don’t fail loudly.
They fail quietly — one wrong answer at a time.
Continuous human evaluation is your smoke detector.
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You can’t fix what you can’t see.
Observability for AI:
→ Log every output
→ Score every output
→ Route failures to humans
→ Feed corrections back
That’s the loop.
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Accuracy is a snapshot.
Reliability is a track record.
Your users experience the track record.
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