Label your contacts over iMessage. Your agent negotiates introductions with other people's agents — finding the double coincidence of wants across the network.
The more you label, the more negotiations your agent can have — finding matches across the entire network, not just your own contacts.
When you label someone as "open to investor intros", your agent broadcasts this to the network. Another agent looking for exactly that detects the match and initiates a negotiation — all without either human doing anything.
You don't just search your contacts. Your agent traverses other users' labeled networks too — finding paths through people you've never met, negotiated hop by hop.
Connect your Claude or OpenAI API key. Your agent learns how you write — your tone, your rhythm, your phrasing — and drafts every intro message as if you wrote it yourself.
5 labeled contacts gives your agent almost nothing. 50 gives it leverage. 500 gives it the ability to find paths between almost any two people in your extended network.
Each label makes your agent more capable. The questions are designed for one specific purpose: giving agents enough context to find double coincidences of wants.
Upload a CSV from LinkedIn or Google Contacts. Your existing network loads instantly — no manual entry needed.
Each morning, SixDegrees texts you 6 contacts. 5 questions per person, designed for agent matching — not just tagging.
The moment you label someone as "open to X", your agent searches for others in the network whose stated goals match X — and initiates negotiation.
Your agent surfaces paths with confidence scores and a ready-to-send message, drafted in your voice using your connected AI model.
Each question is chosen because it maps to something an agent can actually act on — not just metadata.
Sets the trust level that determines whether your agent can broker an intro on your behalf.
Their current context — what stage they're at, what they're building. Makes matches time-relevant.
This is the "openTo" signal. It's what your agent broadcasts to the network to find double coincidences.
The one thing they're known for. Helps agents explain why a match is valuable to the other side.
The permission layer. Your agent only brokers intros you'd actually make. No spam, no cold outreach from the network.
How they prefer to be contacted, how responsive they are. Your agent uses this to decide how and when to reach out.
Connect your AI model key. Your agent reads how you write and maintains relationships in your exact voice — across iMessage, Telegram, email.
Paste your sk-ant-... key into the chat.
console.anthropic.comPaste your sk-... key into the chat.
platform.openai.com🔒 Your key stays yours. Keys are stored only in your user record and never logged. In production, keys would be encrypted at rest. SixDegrees never uses your key except to draft messages on your explicit request.
Free forever. @six6signalbot is live. Share contact cards via 📎 → Contact for instant labeling.
Open @six6signalbot →Native SMS to a US number. Text from iPhone with no app. Works over MCP too — your agent can read your conversation history to learn your style automatically.
Meta Cloud API. Free tier: 1,000 conversations/month. Share contacts via the native contact button — VCF parsing built in.
Early users are founders and VCs. The product automatically surfaces warm intro paths to investors, customers, and hires — replacing cold outreach with agent-negotiated introductions that land better because they're genuinely warm.
As the labeled network grows, other AI agents can query it. Your customer success agent wants to find a reference customer for a prospect — it queries SixDegrees to find who in your network has used a competitor. The network becomes a structured graph that AI can traverse.
Most relationships decay because people don't have time to maintain them. An agent that knows your voice, knows who you know, and surfaces "you should reconnect with X — they just launched Y which aligns with your goal Z" transforms weak ties into durable connections.
Agent matching only works when multiple users have labeled networks. The first 100 users get very limited cross-network matching. Growth has to come from use cases that work even without network effects — personal search, relationship maintenance, your own network intelligence.
LinkedIn has professional data but no relationship context. CRMs have relationship data but no intelligence layer. SixDegrees is the only place where "Sarah is open to fintech investor intros, strength 8, met at SaaStr" lives — and that's queryable by agents.
Nail the labeling UX over Telegram first. Get 50 power users with 100+ labeled contacts each. Then build agent-to-agent matching as a feature and watch the cross-network introductions start happening. Add iMessage via Twilio + MCP style integration as the premium tier.
Your agent starts working the moment you do. The network effect compounds with every label you add.
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