Intenti.co

A client may announce expansion plans, leadership changes, regulatory issues, funding activity, or new strategic priorities, but those signals are easy to miss unless someone is actively watching. Even when salespeople find relevant news, they still have to judge whether the event matters, which account it affects, and whether outreach makes sense.

AI supported the product vision, and it also played a real role in the design process: speeding up early wireframing, summarizing competitive patterns, exploring use cases, and checking whether the product could generate useful signals from real industry activity.

We recorded the functional and business backlogs at the very start, which gave us a list of standard and edge cases that AI had not generated. That list proved essential for validation, since AI was far less useful for edge cases.

To understand the landscape, I used AI to build a feature-overlap model across major CRM and sales intelligence products, then grouped features by depth, maturity, and usage pattern. From there we identified a typical industry journey: the baseline experience users would expect before Intenti.co could stand apart.

AI meant working faster, but it still needed oversight and direction. It was good at attaching probabilities to events, but judgment still had to come from people. The research also narrowed the opportunity: not another CRM, feed, or intent-data layer, but a focused tool that connects industry signals to specific accounts and a next step.

The first step was defining the difference between generic news aggregation and sales intelligence people could act on. Salespeople did not need another feed. They needed a filtered view of client-relevant activity, one that moved past headlines and explained the link between an outside event and a potential business need.

Competitive patterns made the gap clear: news-heavy dashboards showed too much raw information, intent platforms scored events without explaining them, and CRM tools tracked accounts without explaining timing. The design opportunity was to combine signal detection with plain-language reasoning.

The interface centered on a signal dashboard, backed by account-level detail pages and prioritized action cards. Each card carried a plain-language summary of the event, the affected account, the signal category, why it might matter, a suggested next action, confidence indicators, source links, and options to save, dismiss, assign, or act.

It had to be useful without feeling like a black box. Salespeople needed enough explanation to trust a recommendation, but not so much that reading it took longer than acting on it.

The work defined a product experience that turned scattered industry news into a focused sales workflow. Instead of asking users to search, scan, and interpret on their own, Intenti.co hands them the event, the account it affects, and a suggested next step.