We partnered with Agentive to design an agentic platform that explores markets, tests hypotheses, and surfaces revenue opportunities automatically—so teams can focus on decisions, not research.
Agentive didn’t need another dashboard. They needed a way to make an entire agentic AI ecosystem feel approachable, trustworthy, and useful to real revenue teams. We came in not just to “skin” a product, but to co-design how autonomous agents would expose their thinking, surface opportunities, and earn human trust over time. We worked as an extension of the founding team—iterating on concepts, models, and UX in parallel. Every prototype was powered by real agentic output, tailored to each test company, so feedback wasn’t theoretical. It was visceral. Stakeholders saw opportunities about their real markets, their real buyers, their real positioning—and reacted accordingly. That tight loop between intelligence, UX, and real customer context meant we weren’t just validating screens. We were validating the entire operating model of an autonomous revenue engine, and shaping the product’s core behavior long before launch.
Agentive’s vision was bold: a fully agentic revenue engine that could explore markets, analyze signals, map accounts, and surface opportunities without waiting for human prompts. But the first challenge wasn’t technical—it was human. If the system looked like a black box, nobody would trust it. If it exposed too much complexity, nobody would use it. The early thinking made sense to AI insiders, but not to the sales leaders, founders, and operators who would actually live with the product every day. We needed to turn a multi-agent system—crawling the world for patterns and opportunities—into a mental model people could grasp quickly: what is this thing doing for me, why should I trust it, and what do I do next?
We also couldn’t rely on static data. Everything in Agentive changes as markets move and agents learn. That meant traditional IA patterns weren’t enough. We had to design a front end that could keep pace with constantly evolving insights, conflicting signals, and shifting hypotheses—without feeling chaotic. The core problem was not just “how do we show output,” but “how do we let humans explore and steer an evolving map of opportunities in a way that feels grounded, legible, and worth their time?”
We grounded the product in a clear purpose, mapped the agentic workflows, and defined how opportunities should be discovered, evaluated, and expressed to humans.
Target Market Interviews
Opportunity Typology Definition
Experience Narrative
Rapid & Iterative Prototyping
We designed interactive prototypes wired to live agentic output so every test session reflected a company’s real market, accounts, and opportunities—not sample data.
High-Fidelity Prototypes
Agentic Output Integration
User Testing with Real Companies
Insight Feed Experiments
Trust & Explainability Patterns
We codified the mine-of-opportunities mental model into a scalable design system—defining patterns for feeds, detail views, comparisons, and next-step actions.
Full product visual design
Style guide and Asset Library
High Fidelity Prototype
Dev Handover
Agentive now presents its intelligence as a stream of well-structured opportunities, not a wall of analysis. Each card explains what the system sees, why it matters, and how confident it is—so humans can quickly decide to explore, act, or ignore. A swipeable, prioritization-first feed keeps focus where it belongs: on choosing the next best move. Under the surface, multiple agents are still exploring markets, testing hypotheses, and refining models. On the surface, users see a calm, opinionated interface with clear paths into deeper context when they need it. The design reinforces trust without dumbing down the intelligence—it simply frames it in human terms: “Here’s what we found, here’s why it matters, and here’s what you can do now.”
Early customers praised how quickly they could grasp complex AI-driven insights, validating the core model and positioning Agentive as an emerging leader in agentic revenue intelligence.
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