Aegis predicts the reasonable cost of every claim in UGX, flags suspicious billing patterns from hospitals across Mulago, IHK, Mbarara and Lacor, and explains every recommendation in plain language. The AI never auto-denies. Humans always decide.
Free 14-day evaluation · No credit card · Approved within 1 business day
Aegis plugs into your existing claims pipeline. No need to change how providers submit data.
Drop in a CSV from your TPA or HMIS export. Aegis preprocesses, deduplicates, and validates every row.
A cost-prediction model produces an expected UGX range. An anomaly engine flags outliers and assigns a 0–100 risk score.
Your team sees flagged claims with plain-English explanations and approves, adjusts, or escalates them.
Six capabilities working together to protect every shilling your members contribute.
Per-claim predictions calibrated against peer providers in the same region — Central, Eastern, Western, Northern, West Nile, Karamoja.
IQR cost outliers, length-of-stay percentiles, provider over-billing patterns, and duplicate-claim detection — combined into one risk score.
Every flag ships with the reasons in plain English so your reviewers can act in seconds, not hours.
See which hospitals consistently bill above peer rates and where your cost growth is concentrated.
Total claimed vs. predicted reasonable, monthly trends, risk distribution — all in one view for management.
Reviewers, analysts and administrators each get the right view. Every decision is recorded for audit.
Every safeguard your compliance officer will ask about — designed in, not bolted on.
Every plan ships the same AI engine. Pick how much production data and how many reviewers you need.
See Aegis run on synthetic Ugandan claims with one of our engineers. No setup required.
Full reviewer access in a private sandbox loaded with synthetic claims from Ugandan facilities.
For insurers ready to deploy Aegis on live claims volume across multiple regions.
Request access now — your administrator typically approves new accounts within one business day.