Production AI agent programs for enterprise leaders

Problem. Patient access capacity is consumed by routine booking traffic, capping the volume a health system can serve without adding headcount.

Agent design. Voice agent on Amazon Connect and Lex authenticates the patient, reasons over provider availability and scheduling rules, and writes the booking directly into the EHR — escalating to a human the moment a clinical question appears.

Outcome. Scheduling work completes end to end in the call, with clinical and exception traffic routed to patient-access staff with full context.

Acts in. EHR scheduling · Patient identity · CCaaS

Problem. Repetitive claims-status demand consumes member-services capacity that regulated appeals and grievance work needs.

Agent design. Agent authenticates the member, retrieves claim and EOB detail from the claims platform, explains denial reasons grounded in plan documents, and hands appeals to a specialist with the case assembled.

Outcome. Members resolve status, benefit and denial questions in channel; specialists work only the cases that need judgement. Appeals, grievances and eligibility disputes escalate to a licensed specialist with the case assembled.

Acts in. Claims platform · Member portal · Plan documents

Problem. A complex product mix drives inconsistent guidance and long handle times, and new advisers take months to reach proficiency.

Agent design. Assist agent reasons over product, policy and compliance content in real time, proposes next best action, checks the adviser's wording against disclosure rules and writes the wrap summary into CRM.

Outcome. Every adviser answers like the best adviser, with a compliance-checked record of what was said. The adviser reviews and sends every recommendation; nothing reaches the customer unapproved.

Acts in. CRM · Product and policy knowledge · Compliance rules

Problem. First-notice-of-loss intake is long and expensive, and incomplete data pushes rework and cycle time into the adjuster's queue.

Agent design. Agent conducts structured loss intake across voice and digital, collects photos and documents, validates coverage against policy admin, sets severity and books the adjuster.

Outcome. Adjusters open complete, coded claims instead of chasing the customer for missing facts. Coverage disputes, injury and suspected-fraud indicators escalate to an adjuster immediately.

Acts in. Claims system · Policy admin · Document capture

Problem. Order-status and returns demand triples at peak, forcing seasonal hiring that never pays back.

Agent design. Agentforce service agents call OMS and commerce APIs to track, cancel, reship and refund within policy limits, with voice fallback on Amazon Connect and a single context handoff to a human.

Outcome. Order and returns work is completed by the agent across web, app and voice — not deflected to a form.

Acts in. OMS · Commerce platform · Payments

Problem. Sampling 1–3% of interactions leaves client risk unmeasured and makes quality claims impossible to defend in a QBR.

Agent design. Scoring agent evaluates every voice and digital interaction against client-specific scorecards, with calibration sets, confidence thresholds and a dispute workflow the client can audit.

Outcome. Defensible per-client quality reporting on full volume, and the scoring foundation quality-aware routing builds on. Low-confidence scores route to a human reviewer, and clients can dispute any score.

Acts in. Interaction recording · QA scorecards · Coaching workflow

Problem. Billing and coverage conversations require staff to reconcile four to six systems live, which slows resolution and creates compliance exposure.

Agent design. Assist agent retrieves balance, coverage eligibility and script-safe payment-plan options in real time and proposes the compliant next step for the representative to confirm.

Outcome. Consistent, compliance-safe financial conversations resolved on the first contact. The representative approves every financial commitment before it is offered.

Acts in. Billing / RCM · Eligibility · Payment plans

Problem. Star and CAHPS performance carries direct revenue consequence, yet the drivers sit unread inside unstructured member conversations.

Agent design. Analysis agent classifies every interaction against Stars and CAHPS driver models, links themes to measure impact and pushes coaching moments into quality workflows.

Outcome. Member-experience investment is targeted at measures that move revenue, with evidence per driver. Quality leaders review and approve driver findings before coaching plans change.

Acts in. Interaction analytics · Quality management · Member survey data

Problem. Early-stage collections is high-volume, low-margin work where regulatory error is more expensive than the balance recovered.

Agent design. Voice agent works policy-grounded scripts within FDCPA and UDAAP guardrails, takes payments and arrangements inside limits, and hot-transfers on any hardship or dispute signal — every turn logged.

Outcome. More balances resolved per dollar spent, with a complete audit trail for compliance review.

Acts in. Collections platform · Payments · Consent and compliance log

Problem. Prior auth is payer-specific, multi-step work that consumes clinical time and delays both care and reimbursement.

Agent design. Multi-agent system: an intake agent assembles the clinical packet, a payer-rules agent applies the right criteria, a submission agent files it, and a follow-up agent tracks status — clinicians approve before submission.

Outcome. Submission and chasing run autonomously; clinical staff review exceptions only.

Acts in. EHR · Payer portals · Utilization management

Problem. Periodic refresh across a large customer book is a fixed regulatory cost that scales only by adding analysts.

Agent design. Agents pull entity and ownership data, screen adverse media and sanctions, reconcile discrepancies and produce a refresh packet with a reasoning trace for analyst approval.

Outcome. Analysts approve evidence-backed packets rather than assembling them, and refresh cycles stay inside regulatory windows.

Acts in. CRM · KYC / AML platform · Screening providers

Problem. SMB submissions are too low-margin to staff properly, so carriers decline business or lose it to slower turnaround.

Agent design. Underwriting agent extracts submission data, runs appetite and eligibility checks, prices tiers against the rating engine and drafts the quote for underwriter approval.

Outcome. Straight-through submissions are quoted same day with the underwriter retaining the bind decision.

Acts in. Policy admin · Rating engine · Submission inbox