A government and non-profit case management software platform came to Armakuni for generative AI to collapse 6-month manual client onboarding to weeks, and natural language analytics to surface compliance and fraud exposure before payer audits.
The challenge
Government and non-profit Health and Human Services case management platform came to Armakuni with two structural barriers to growth: a client onboarding process taking 6-7 months and a data layer its own staff could not query without an engineering ticket. Armakuni delivered a two-phase engagement funded largely by AWS, each phase validating a distinct AI capability positioned for full production.
Scale: Serves government agencies and non-profit organizations across counties and states managing case records, therapy visits, billing, and regulatory compliance.
What we built
Armakuni delivered generative AI to collapse 6-month manual client onboarding to weeks, and natural language analytics to surface compliance and fraud exposure before payer audits. The engagement ran as two parallel fixed-scope SOWs: Form and Checklist Onboarding Automation (Phase 1) and AI Report Insighter and Auditor (Phase 2). AWS funded the work at $11,550.
The outcomes
6 measurable outcomes shipped across the engagement. The ones that moved the business the most:
80-90% of form onboarding effort is now automated. An implementation that once took months of hand-configuration is now a pipeline run plus a human review, with the remaining 10-20% the edit and approval step built to keep a human in the loop.
Professional services cost is targeted to fall by 70% or more. Implementation moves from a margin-compressing engagement to a near-automated deployment, making every new county or state the platform signs substantially more profitable than the last.
Go-to-market timeline compressed from roughly six months to weeks. A vendor that can onboard a new government client in weeks instead of half a year turns its implementation cycle from a competitive liability into a differentiator and stops losing deals on timeline.
Staff can ask plain-English compliance questions and see answers in seconds. This replaces a workflow that required SQL expertise, ticket filing, and days of waiting, letting every supervisor, billing manager, and compliance officer query their own data without engineering.
Fraud and compliance exposure is now detectable before payer audits. Ten pre-built monitors cover the highest-risk billing scenarios, catching overlapping visits, unrealistic travel distances, and duplicate claims as they occur rather than when a payer flags them in arrears.
Analytics became a monetizable capability, not just an internal compliance tool. The conversational query layer can be surfaced to the platform's own clients as a product feature, creating a revenue pathway from the same infrastructure built for internal use.
Built on AWS
The production environment runs on 18 first-party AWS services. Delivered under our AWS AI Services, Data Analytics competencies.
What's next
Full production implementation of both phases. Potential integration of the analytics layer into Government and non-profit Health and Human Services case management platform's client-facing product as a monetizable feature.