Build a Ruthless AI Researcher to Evaluate 108 Customer Support Software
Build an AI researcher to evaluate customer support software quickly and consistently, so decisions are driven by evidence instead of weeks of manual comparison.
What you'll learn
Clear outcomes, practical examples, and a workshop structure designed to help teams understand how the system actually works.
Break software selection into clear requirements, scoring logic, and research prompts so the agent can assess tools against the same standards every time.
Reduce manual browsing, note-taking, and spreadsheet reviews by using an AI researcher to pull together evidence faster and more consistently.
Replace opinion-driven shortlists with a structured evaluation workflow that helps teams compare options objectively and move sooner.
Why this topic matters
Why this workshop matters in the real world, and what operational problem it helps teams solve.
Software selection often turns into weeks of fragmented research, inconsistent note-taking, and subjective debate. A ruthless AI researcher gives teams a repeatable way to evaluate tools against clear criteria, so they can compare options faster and make better decisions with less manual effort.
Event details
Everything you need to know before registering, laid out clearly so the listing is easy to scan.
Speaker
Learn from an operator who builds AI systems inside real businesses, not just slide decks.
Jason Tan
Chief AI Officer at Ascendnce | Speaker
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.
Subscribe for practical frameworks on building AI products.
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