An agentic CRM that works in both directions

Relationship businesses run on who you know and how well you follow up, and most CRMs make both harder. This one works in two directions. Inbound, it starts from the smallest possible input — a name, or a name and an email — and does the rest: enriches the record from public sources and the team's own history, runs a psychometric assessment protocol I built to read how the person communicates and decides, and matches them against live deals and incubations. Outbound, you ask it questions. “Who in our network might want this deal?” cross-references active industry, geography, the investment history we know of, relationship warmth, and investment patterns, and returns a priority-weighted list of people to approach, with outreach drafted for each one's deal structure and industry. Built for a venture team first; the framework generalizes to any business or team that runs on a list of contacts.

• Inbound from the smallest input: a name, or a name and an email — from a phone, a text, or a chat — and the record builds itself.
• Agentic enrichment with a human check: background, role, affiliations, and interaction history pulled together, reviewed before it's saved.
• A psychometric assessment protocol per contact — communication style, decision drivers — so outreach reads as if it was written for them, because it was.
• Ask the book, not just the record: natural-language search, intelligent filtering, and cross-matching across the whole CRM.
• “Who would want this deal?” Industry, geography, known investment history, relationship warmth, and investment patterns, weighted into a priority list — then outreach drafted per deal structure and industry, in the sender's own voice.
• 2,047 profiles enriched so far, which also seeded the pre-meeting brief agent that runs on the same records.
• The venture examples are the first use; the framework fits any team that lives by its contact list.