How to Build an AI Agent to Lead Sales Research

Hosted by Jason Tan

Thu, Aug 6, 2026

10:30 PM UTC (1 hour)

Virtual (Zoom)

Free to join

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What you'll learn

Collect and enrich lead data automatically

Gather and enrich raw contact and company data automatically. Feed the AI agent exact context to process data accurately

Build an evaluation engine for prospects

Build an engine to review headcount and growth metrics. The AI agent evaluates contacts to verify decision makers.

Scale your top of funnel capacity

Run evaluations continuously to process hundreds of leads daily. A 3-person team can execute like a 40-person one.

Why this topic matters

Manual research forces professionals into data entry and caps your pipeline. Building an AI agent removes the grind of inspecting prospects and companies one by one. You will turn a 6 hour task of reviewing 100 prospects into a 20 minute automated process. This drives a 4X capacity increase and frees your team to just talk to customers.

You'll learn from

Jason Tan

Bootstrapped AI Founder | Author & Speaker | AI Product & Business Advisor

I am the Chief AI Officer at Ascendnce. We build AI agents that scale revenue without adding headcount, automating real operations like lead research and email triage.

Previously, I bootstrapped Engage AI to 100,000 users and built pricing systems for major insurers. After 20 years in data science, I prefer execution over theory. I map business workflows to prove financial cases and build actual technology.

In this course, I teach engineers and corporate employees this approach. You will learn to identify expensive bottlenecks, work backwards, and rapidly prototype a functional AI product. You leave with the frameworks and a working AI prototype to become an internal product leader.

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