A defined payer operating result.
Agree on the baseline, target, operating value, owner, and evidence that will guide the investment.
Payers · Custom AI Solutions
Put lab benefit policy into daily operations.
Connect missing-order follow-up, benefit requirements, provider and laboratory coordination, prior authorization, clinical review, and claims. Gistia defines the operating approach, implements the software and AI, and supports it in production.
- 01Set directionPriority + result
- 02ImplementProof + production
- 03Operate and improveReliability + value
What you get
One connected benefit operation. One accountable team.
Build around approved policies, clear decision rights, connected evidence, and the systems used by your payer, provider, and laboratory teams.
A working system in production.
Configure the software, AI, integrations, evidence records, and review controls around the benefit workflow and the people responsible for it.
A team that stays after launch.
Monitor reliability, resolve issues, measure performance, and improve the capability as rules and operations change.
Where Custom AI can help
Start where lab benefit policy meets daily work.
Choose one test category, order population, or laboratory relationship. Define the owner, the current workload, and the evidence needed to measure improvement.
Close the missing-order and documentation gaps.
Track incomplete requisitions, clinical records, provider requests, and confirmed handoffs across the ordering and laboratory teams.
Apply approved requirements before testing.
Connect plan and formulary criteria, documentation needs, prior authorization preparation, and authorized clinical review.
Connect downstream problems to the order.
Link available order, authorization, and claim records to understand recurring rework, appeal needs, review effort, and operating trends.
Strategy, implementation, and support
From operating priority to reliable production.
Each stage produces a decision backed by operating evidence. The work proceeds, changes direction, or expands only when the case supports it.
01Strategy
Define the result and ownership.
Frame the priority, operating value, future workflow, authority, data, risk, and investment decision.
Proceed when the opportunity is material, measurable, and owned.02Implementation
Prove the capability and launch it.
Design the workflow, connect systems and data, test representative work, validate controls, prepare users, and harden production.
Production follows operating evidence, not demo enthusiasm.03Support
Operate, improve, and extend.
Monitor quality and reliability, resolve issues, govern releases, measure results, and prioritize controlled improvement.
Extend when measured results support the next investment.Built for production
AI must fit the operation around it.
The model is only one component. A dependable capability also needs connected systems, human authority, production controls, and continuing ownership.
Fit the real operation.
Design around existing roles, work states, exceptions, approvals, and downstream actions.
Connect the operating environment.
Integrate the sources, applications, identity, and data required for the capability to work.
Keep judgment explicit.
Define what AI prepares, what people decide, and how exceptions and escalations move.
Own reliability after launch.
Monitor performance, security, releases, support, adoption, and measurable operating value.
Payer Solutions CatalogIs the operation already defined?
Explore the Solutions Catalog Explore Order Completion, Prior Authorization, and the Payer Review Portal for a defined part of the lab benefit workflow.
Where should your lab benefit operation improve first?
Bring the missing-order backlog, benefit requirements, provider coordination, review workload, or order-to-claim gap you want to address.