Build a research profile on a contact before a meeting

Builds a one-page research summary on a contact's background, communication style, and public records before you meet them.

How the work actually flows

It branches. Every path runs; all paths must finish before it continues.

Pattern: Parallel Split (2) ยท Synchronisation (3)

flowchart TD trig(("contact submitted for research")):::human s0["gather contact details"]:::task s1["combine into summary report"]:::task trig --> s0 gx{"+ which data sources to check"}:::gate s0 --> gx p00["check public profiles"]:::task gx -->|"profile check"| p00 p10["find verified email"]:::task gx -->|"email lookup"| p10 p20["search public records and news"]:::task gx -->|"records search"| p20 jn{"+ all data combined"}:::gate p00 --> jn p10 --> jn p20 --> jn jn --> s1 out[/"one page research report produced"/]:::out pay{{"walks into meetings fully prepared"}}:::pay s1 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
A stepA personEvery pathWaits for allResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Agents & Autonomous SystemsKnowledge Base & RAG
Connects
HunterCourtListenerLegiScanSerperOpenRouter

The problem it solves

Before an important call or meeting, you want to know who you're talking to, how they communicate, and whether anything relevant shows up in public records. Pulling that together from separate sites takes time you don't have right before the meeting.

Who it fits

Sales, recruiting, or research teams preparing for a meeting with a new contact.

How it works

  1. A contact's name and company are submitted
  2. Public profiles are checked for communication style and preferences
  3. A verified professional email address is found
  4. Public records and recent news mentions are searched
  5. AI combines everything into a single summary report
What you get

Context you walk into every meeting already knowing

You arrive at every meeting already knowing who you're talking to, how they communicate, and what's publicly on record about them.

What you get

A one-page research report summarizing the contact's background, communication style, and public activity.

What you need

Accounts with several research and data API providers.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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