We audit medical claims for self-insured employers and health plans.

๐–๐ก๐ฒ ๐ฐ๐ž ๐›๐ฎ๐ข๐ฅ๐ญ ๐ญ๐ก๐ข๐ฌ: I (Angel) have had three knee surgeries since my mid-teens and was billed more than $250K for care that should have cost a fraction of that. Fighting those inflated charges was so painful that we set out to build a consumer-facing AI agent to do it for others. In less than five months, we helped sixty patients erase or reduce over $300K from their medical bills. This inspired us to fix the problem farther upstream: stopping bad payments before the patient ever sees a bill. So we launched payment integrity, machine-learning models that audit every medical claim for self-insured employers and health plans in real time. ๐“๐ก๐ž ๐๐ซ๐จ๐›๐ฅ๐ž๐ฆ: โ€ข Self-insured employers waste $60 B+ each year on claims that never should have been paid. Healthcare is the 2nd largest company expense after payroll. โ€ข Manual audits are slow and partial: Reviewers focus only on high-dollar claims, letting millions more slip through unnoticed. โ€ขย Existing audit software is static: Decades-old rule engines canโ€™t keep pace with evolving codes, contracts, or billing tactics. โ€ข Incentives are misaligned: Third-party administrators are paid to process claims, not to police them, so accuracy checks are minimal. ๐Ž๐ฎ๐ซ ๐’๐จ๐ฅ๐ฎ๐ญ๐ข๐จ๐ง: Our models audit medical claims before and after payments have been issued. We catch nuanced billing, coding, and contract errors to save 3-7% on annual claims spend. We work with self-insured employers and health plans. ๐€๐›๐จ๐ฎ๐ญ ๐”๐ฌ: Angel Onuoha (CEO) and Ahmad Shehu (CTO) have worked together for 4 years. Before Avelis Health they built Zuvy, a Lagos-based fintech company that provided invoice factoring to small businesses. Zuvy was acquired by The BAS Group in 2025.

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Total Open and Closed Positions

Total open positions, and positions newly closed since the previous update

Department Headcount Over Time

Open positions per department ยท top 6 at any point in the window

Newly Opened and Closed Positions

Position Churn Rate

Positions closed within 14 days of opening ยท a high rate suggests posting instability โ€” duplicates, pulled listings, or roles filled through internal or off-market channels

Time-to-Fill Distribution

Days from open to close ยท closed positions only

Salary Trend Over Time

Monthly median base salary ยท USD ยท annualized ยท p25/p75 dashed

Salary Range by Department

Employment Type

Technical vs. Non-technical

Open positions ยท by department

Top Roles by Department

Seniority Mix

Derived from job title keywords

Equity Range by Department

Top Skills

Top Tech Stacks

Skills Trend

Change in share of postings ยท recent 3 months vs. prior 3 months

Tech Stack Evolution

Positions opened per month ยท top 5 technologies