A visualization of how my Rogo Intelligence has grown over the last month. Rogo builds and maintains a profile for each entity. It pulls from your email, CRM, files, and meeting notes, plus third-party data, your activity on the platform, and its own research. Those profiles capture high-value insights that wouldn’t live within the rigid schema of a CRM. For example, when a sponsor bids $500m for a company, that purchase price ends up in the banker’s CRM. What probably doesn’t make its way to the CRM is the sponsor’s valuation rationale. Why couldn’t they stretch to $600m in a competitive process? What about the business gave them pause? The banking team could undoubtedly tell me, but the CRM usually can’t. Rogo Intelligence solves that. The entity profiles usually contain two types of info as a result: (1) Client-defined: Clients tell Rogo what to track for each entity. Many investment firms have already codified the highest signal datapoints in their evaluation process. Rogo puts collecting that data on autopilot. (2) Model-inferred: LLMs are exceptionally good at synthesizing massive amounts of information and interactions to unearth patterns that people would rarely observe themselves. By allowing the model to populate each profile with information it deems relevant to you, you take full advantage of the data at your disposal. The combination establishes Intelligence that can be searched and proactively surfaced to make you smarter on the next deal or investment.