AI Workforce Platform that optimizes AI systems with human feedback data sourced and verified from a community of domain-experts.
San Francisco
Joined December 2024
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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.
The future enterprise AI stack:
Enable the knowledge.
Build the agents.
Run them under your controls.
That’s the architecture we’re building at Joinable.
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The same AI question can have different answers depending on who asks it.
Not because the truth changes.
Because permissions do.
Enterprise AI needs to understand that distinction.
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AI governance shouldn’t be something you bolt on after the answer.
Governance should happen before knowledge ever reaches the agent.
Authorization first.
Reasoning second.
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Enterprise knowledge changes constantly.
The security runbook gets updated.
The policy changes.
The escalation path moves.
AI shouldn’t reason from last quarter’s copy.
Knowledge needs to stay synchronized with the source.
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At Joinable, we call them Data Cards.
Small, structured units of institutional knowledge that retain their context, provenance and permissions.
Not another pile of documents for an AI to figure out.
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There’s a huge difference between:
“Here are 10 documents.”
and
“Here is the exact approved fact, its source, permissions, relationships and confidence.”
That difference matters when AI starts acting.
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RAG helped AI find company documents.
The next step is harder:
Can the agent tell what’s current?
Who is allowed to see it?
Where did it come from?
Can we audit what happened?
That’s the layer Joinable is building.
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A chatbot can answer a question.
An enterprise agent may actually take action.
That changes the requirement.
Before agents become more powerful, the knowledge underneath them needs to become more trustworthy.
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Enterprise AI needs more than retrieval.
It needs:
→ Permissions
→ Provenance
→ Validation
→ Freshness
→ Auditability
That’s what makes knowledge agent-ready.
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Most companies have an AI problem disguised as a data problem:
Their most important knowledge was written for humans, not agents.
Propagator turns that knowledge into something AI can safely reason from.
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AI agents shouldn’t have to guess how your company operates.
They should know.
Your policies.
Your procedures.
Your permissions.
Your institutional knowledge.
That’s the idea behind Joinable.
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The next enterprise AI breakthrough isn’t another model.
It’s making the knowledge underneath the model trustworthy.
That’s what we’re building at Joinable.
Your company already has the knowledge your AI needs.
The problem?
It’s buried in PDFs, emails, tickets, Slack threads and spreadsheets.
Joinable turns that scattered information into governed knowledge AI agents can actually use.
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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 1
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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.
