Definition

Relationship intelligence for Web3 and AI.

Relationship intelligence is the data layer that maps people, companies, events, and trusted connections in Web3, then tells you the right person to meet, the right room to enter, and the right message to send — before the opportunity is public.

01 / The shift

AI made reach cheap. Trust became the bottleneck.

In the last era, the scarce resource was information. LinkedIn gave you names, a CRM stored them, and a good operator could build a list. In the AI era, a model can generate a thousand personalized messages in minutes — which means the scarce resource is no longer access. It is trust.

Trust in Web3 moves through rooms: dinners, side events, Telegram groups, introductions from someone who was already trusted. Relationship intelligence captures those rooms, the people in them, and the signals that make one room more valuable than another.

02 / The definition

What relationship intelligence is.

Relationship intelligence is a system that combines public signal data (funding, mainnet deploys, job changes, hiring, GitHub activity, event attendance) with a relationship graph of who knows whom, then scores both to surface the highest-leverage move for a deal team.

It is not a CRM. A CRM records what you already know. Relationship intelligence tells you what you should know — and who can introduce you to it.

Signal graph

Funding rounds, mainnet and testnet deploys, job changes, key hires, GitHub activity, and event attendance — every discrete event that changes who is worth talking to.

Warm-path layer

Your team's existing relationships, co-investors, past clients, alumni, and shared event history mapped against every target account so the shortest trust path is scored automatically.

Heat score

A composite priority score. One signal is noise. Two is interesting. Three converging on the same account is the person your team should call this week.

Agent-native

An MCP server lets Claude and other AI agents query the graph, rank leads, log meetings, and draft outreach in plain language — with your rules and your context.

03 / Why Web3 and AI need it

The best deals happen before the announcement.

Web3 markets move on chain and off chain at the same time. A mainnet deploy, a fresh raise, a champion changing jobs, or a team buying dinner tickets are all signals that a window is opening. By the time the news is public, the best people have already talked.

AI makes the follow-up fast, but it cannot fake context. Relationship intelligence gives AI the trust graph and the signal history to draft messages that feel like warm intros, because they are grounded in real shared context.

04 / Use cases

Who uses it, and for what move.

Founders

Find the partner at a fund, not the info@ address, and the warm intro through a founder they already backed.

BD teams

Call the protocol the week it deploys to mainnet, closes a round, or loses a CTO — before the RFP exists.

Investors

See which companies your portfolio founders are talking to, where they are meeting, and which signals are firing before the deck lands.

Service providers

Catch audits, legal, and infrastructure needs from mainnet deploys, raises, and key hires before the procurement process starts.

FAQs

Questions, answered.

What is relationship intelligence for Web3 and AI?

Relationship intelligence is a system that combines public signal data — funding, mainnet deploys, job changes, hiring, GitHub activity, and event attendance — with a relationship graph of who knows whom, then scores both to surface the highest-leverage move for a deal team.

How is relationship intelligence different from a CRM?

A CRM records what you already know. Relationship intelligence tells you what you should know next — the person, the room, and the message — and who can introduce you to it.

Why does Web3 need relationship intelligence?

Web3 markets move on chain and off chain at the same time. By the time a raise, mainnet, or hire is public, the best people have already talked. Relationship intelligence catches the signal before the announcement.

What signals does relationship intelligence use?

Mainnet and testnet deployments, fresh funding rounds, job changes and champion moves, key hires, GitHub activity, event attendance, and a composite Heat score that surfaces when several signals converge on one account.

How does AI fit into relationship intelligence?

AI automates outreach and ranking, but it needs trusted context to sound human. An MCP server gives agents like Claude access to the relationship graph and signal history so they can draft warm intros, score leads, and log meetings in plain language.

Get into the right rooms.

Private beta, onboarding deal-driven Web3 teams. Book a demo and we'll get back to you directly.