Healthcare · PE portfolio company · clinical data intelligence

A Claude-assisted market assessment for a clinical data company entering risk adjustment

Thirty years in the provider market, about 4,000 clients, and a board mandate to sell a risk adjustment product to payers the commercial team had never sold to. Claude ran the segmentation; a two-person team ran what had historically taken six to eight.

52 targets
from about 4,000 clients in 8 weeks; $60M opportunity identified
Claude in production
Claude Cowork and Claude Code; Claude Sonnet for the segmentation; Claude Opus for the executive materials
Timeline
Phase I December 2024 to July 2025; Phase II to January 2026; follow-on to March 2026
Data engine
Aequalis Payer Insights Platform
The takeaway
  • About 4,000 client relationships were matched against public Medicare Advantage, ACO, Medicaid and ACA plan data and narrowed to 52 named risk-bearing targets, 24 of them top priority, in 8 weeks.
  • $60M of new-business opportunity identified for the payer line; the board approved the roadmap after 7 deliverables and 2 board updates.
  • A two-person team ran an engagement that had historically taken 6 to 8 people, and the sales-to-customer-success handoff fell from 4 to 6 weeks to 2.

The problem we took

The client had sold clinical data software to health systems for 30 years and had about 4,000 clients. It wanted to sell its risk adjustment product to value-based care buyers: provider-sponsored health plans, payviders and payers. The commercial team had no ranked target list for these buyers, no tested value proposition and limited payer experience. Leadership and the board wanted targeted outreach to start in the first quarter of 2025.

What the client already had

Three differentiators: data source modularity across EHRs and claims, 4,000+ provider relationships, and in-workflow integration of the product. Its own product, growth and sales teams, plus 15 voice-of-customer interviews reached through the 3Pillars network, VP to board level. The sales team kept and shaped the growth enablement kit.

What we built

A top-down and bottom-up market assessment, with Claude running the segmentation and the drafting. The top-down view filtered the payer market to the lines of business where workflow-embedded risk adjustment creates measurable value. The bottom-up view matched the client book against public plan data and kept the clients that run risk-based lines of business with more than 1,000 members. Claude Sonnet did that segmentation inside Claude Cowork and Claude Code, with the Aequalis Payer Insights Platform as the data engine. Around it: county-level risk adjustment use cases, profiles of 10+ competitors, persona messaging, account-level revenue sizing, buyer maps and board updates. Claude drafted the executive-facing materials, which is how two people ran the work of six to eight.

The build stood up the two motions the client did not have: a systematized outreach engine for payer buyers, with humans owning every external touch and AI drafting behind them, and a Pilot Support Program so customer success could catch a signed contract clean. A second phase ran on Claude Cowork beside the customer success team and was built in real time: client-ready materials, customized sales materials, automated KPI and metric reporting, customer-facing HTML dashboards for the client’s own customers, training for end users and the sales team, a change management playbook and value metrics at pilot sites.

52
named targets, 24 top priority, ~20 PSPs in the first wave
8 weeks
Dec 16, 2024 to Feb 6, 2025
2 vs 6–8
people on the engagement

What it returned

$60M of new-business opportunity identified. A board-approved roadmap. A sales-to-customer-success handoff cut from 4 to 6 weeks to 2. At one pilot site in Q2 2025, 22 of about 600 providers accepted 62 suggestions across 48 problem lists, an estimated 0.47 RAF per list with accepted suggestions; after training, 6 providers reviewed more than a quarter of suggestions, up from 3.

The client has not been asked to be named publicly. Its customers are not named here.

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