Avelis Health

Avelis Health discovered that self-insured employers and health plans hemorrhaged millions annually through billing errors and fraudulent claims that went undetected. ​​‌‌‌‌‌‌‌​‌‌​​‌​​​​​​‌‌​‌‌‌​​​‌‌The problem hit hardest for mid-market and large employers managing thousands of employees, where manual claim auditing proved impossible at scale. The financial impact was measurable and severe—Angel's personal experience revealed a single patient could face $250K in overcharges, and across a plan of thousands, these errors compounded into massive losses. Existing alternatives were fragmented: some employers hired claims auditors, but these teams worked reactively and caught only a fraction of errors. Others relied on basic automated filters that lacked sophistication. Early validation came quickly when Avelis's initial consumer-facing approach helped sixty patients eliminate over $300K in charges within five months, proving both that the problem was real and that AI-driven detection worked. This success signaled that the same technology could scale dramatically when applied upstream to entire claims populations rather than individual patients, validating their pivot toward the enterprise market.