Healthtech · Payers & Benefits · 50–200 · North America #b035_24

Context

We build an AI assistant that answers employee questions about their health benefits, sold to employers, brokers and administrators.

Industry

Healthtech · Payers & Benefits

Size

50–200 employees

Region

North America

Tools budget

$1K–5K per month

Needs

LLM evaluation & testing. Our assistant must answer coverage questions correctly for each plan, and we lack automated checks across plan variations.

Today: a data scientist assembles model orchestration and checks for a multilingual benefits assistant · Urgency: this year

Document AI & extraction. Analysts read plan documents by hand to load benefit details, slowing every new customer onboarding.

Today: benefits analysts read and re-key plan documents into structured data and validate by hand · Urgency: this year

Who decides

cto · security review

Expects from suppliers

Extraction tuned for insurance plan summaries; Regression testing for assistant answers; Support across distributed engineering teams

Not a fit

Generic OCR without validation; Expensive enterprise minimums

Stack

LLM APIs in production, cloud: AWS-class hyperscaler

Buying triggers

AI adoption push, new market or product launch