EvolutionIQ · AI product · Senior · 45 to 60 minutes

How should EvolutionIQ win its first carrier?

EvolutionIQ builds AI software for insurance carriers to help claims teams turn messy medical and claims data into actionable guidance. Answer this product management case and get it graded line by line against a weighted rubric.

Product strategy
AI product thinking
Enterprise B2B
Metrics design
Prioritization

The situation

It is early 2019, and EvolutionIQ has interest from insurance executives who like the idea of using AI to help adjusters handle disability and bodily injury claims more effectively. Tom, the technical founder, asks you, the first senior PM, to recommend the company’s initial product and market entry strategy before the team commits engineering time and starts a formal fundraising process. The tension is severe. Carriers want proof of value before they will share sensitive claims data or put a new tool into frontline workflows, but the team cannot prove value without real data, workflow access, and a live customer environment. The buyer universe is small, enterprise sales are relationship driven, and the wrong early choice could trap the company in bespoke services or burn one of the few credible prospects. Assume the company has 12 months of runway and can support only one deeply involved pilot at a time. You need to decide where to focus first, what to build first, how to measure impact, and how to sequence learning into a repeatable business.

What to produce

Write a 2 page strategy memo.

Your answer must

Recommend the initial target customer and claims workflow, with a clear rationale and explicit non goals.
Define the MVP product scope, including what the AI should do, what humans should still do, and why.
Propose a plan to win a first design partner, including what EvolutionIQ should ask for in exchange for pilot work.
Specify how you would measure customer value and product performance during the first pilot, with leading and lagging metrics.
Lay out a sequencing plan for the next 12 months that shows how one pilot could turn into reusable product, reference value, and better data advantages.

Constraints

The product must operate in a heavily regulated insurance environment with sensitive health and financial data.
Potential buyers are few, risk averse, and likely reluctant to be a first customer.
The team can support only one high touch pilot at a time and cannot afford to become a pure services shop.
Any plan must create evidence a carrier would trust, not just internal model metrics.

Format

Use sections for wedge selection, MVP, pilot structure, metrics, and risks.

How EvolutionIQ actually played it

The founding team of a vertical AI insurance startup shares how they found fit, measured impact for buyers and built a business that was later acquired. Good for PMs building AI in regulated industries.

Pick a domain where the AI impact can be measured
Vertical depth is a defensible position

Built from EvolutionIQ's Playbook For Building an Enduring AI Business by First Round Review.