Healthcare billing platform uses an AI billing assistant to cut query resolution time by 70%

The client

The client runs billing operations for healthcare organizations, work that spans a wide range of states and a distinct set of rules for every client contract it manages.

What was breaking

Every state the client operated in and every contract it managed carried its own billing rules, spread across thousands of pages of static policy documents. Field teams and junior analysts fielded a growing volume of billing questions, and many required an answer buried in an obscure section of policy that only a few people could track down. The organization leaned on that small group of experts to resolve anything non-trivial.

That concentrated operational risk in a handful of people left the rest of the team waiting on their availability to resolve queries. New billing specialists took more than 90 days to reach basic proficiency, a curve steep enough to limit how fast the team could grow. Fragmented operations, inconsistent policy interpretation and long onboarding time carried financial and compliance impact the client could not absorb as its client roster expanded.

Why thinkbridge

The client's default response to a growing query volume would have been to add staff, and it considered that option. Hiring more people would not have solved the underlying problem.  The knowledge those queries required sat locked inside documents that took a new hire months to absorb, and more hires would only deepen the organization's dependence on the same small group of experts it needed to relieve.  

thinkbridge built an AI agent into the existing knowledge portal, using the client’s own workflow documentation as the context layer. The agent did not require the client to learn a new process or retrofit its processes, and it could also be used to onboard new billing specialists. That gave the confidence for the client to partner with thinkbridge.

What thinkbridge built

thinkbridge built an AI-enabled billing policy assistant and embedded it in the client's existing knowledge portal, using the thinkOne methodology. The system retrieves the client's own policy documents and combines that retrieval with a generative language model, so an answer draws on the specific state and contract rules that apply to that customer. It breaks a multipart question into its smaller, component parts before answering, which lets it handle the layered questions billing staff actually ask.  

The assistant cites the source document behind every answer, so a user can check the answer, and an auditor can trace it back to policy, removing a manual check in the process. The same system doubles as a training tool: new billing specialists work through real questions at their own pace instead of shadowing a senior analyst until judgment transfers by repetition.

What changed

70% reduction in average time. 80% decrease in queries. 50% cut in onboarding time.

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