Real AI, CX and automation use cases — filter by service, industry and platform.

Problem. High call volume for routine scheduling ties up patient-access agents and drives long queues.

Approach. Natural-language voice bot on Amazon Connect + Lex, integrated with EHR scheduling APIs and healthcare-grade auth.

Outcome. Self-service containment on scheduling calls with warm transfer to a human agent when clinical questions arise.

Problem. Claim-status calls flood member services and are highly repetitive.

Approach. Genesys + Kore.ai IVA fronting the claims platform with knowledge-grounded responses and secure auth.

Outcome. Members self-serve status, EOB questions and denial reasons; agents focus on appeals.

Problem. Complex product mix drives long AHT and inconsistent responses from newer agents.

Approach. NICE Enlighten + Azure OpenAI copilot with RAG over product, policy and compliance content.

Outcome. Next-best-action prompts, live compliance checks and auto-summary at wrap.

Problem. FNOL calls are long, structured and expensive; adjusters get incomplete intake data.

Approach. Five9 IVA + Kore.ai bot collects loss details, uploads photos, sets severity and books the adjuster.

Outcome. Structured, adjuster-ready FNOL packages delivered before the first human touch.

Problem. WISMO and returns account for the majority of contact volume during peak seasons.

Approach. Agentforce service agents backed by Commerce Cloud + OMS APIs; voice fallback via Amazon Connect.

Outcome. WISMO and returns fully deflected from live agents across web, app and voice.

Problem. Traditional QA samples 1–3% of calls, missing risk and coaching signal at scale.

Approach. AI QA scoring every voice and digital interaction with client-specific scorecards and dispute workflow.

Outcome. 100% coverage, faster coaching cycles and defensible client reporting.

Problem. Billing, coverage and payment-plan questions require agents to navigate 4–6 systems.

Approach. Grounded copilot surfaces balance, plan eligibility and script-safe payment options in real time.

Outcome. Faster resolution and consistent, compliance-safe messaging.

Problem. Member experience drivers are buried in unstructured call and chat data.

Approach. Enlighten + custom topic models surface Stars/CAHPS drivers and coaching moments.

Outcome. Targeted coaching against measurable Stars/CAHPS drivers.

Problem. Early-stage collections outreach is expensive and inconsistent with FDCPA/UDAAP rules.

Approach. Retell AI voice agent with policy-grounded scripts, hot transfer to human on hardship signals.

Outcome. More right-party contacts at lower cost, with full audit trail.

Problem. Self-pay and balance-after-insurance accounts are expensive to reach while staying compliant with patient-billing regulations.

Approach. Voice and SMS bot with healthcare-grade authentication, payment-plan offers and warm transfer on hardship signals.

Outcome. More payments and plans without adding FTEs, with full audit trail.

Problem. Patients navigate scheduling, billing, portal help and referrals through disconnected phone lines and portals.

Approach. One conversational front door grounded on EHR, RCM and knowledge content with seamless agent handoff.

Outcome. Single-contact resolution for common patient requests and fewer repeat calls.

Problem. Retail banking customers expect to check balances, transfer funds and dispute transactions through digital channels without calling.

Approach. Kore.ai SmartAssist digital assistant with secure authentication, transactional APIs and warm handoff to live agents for fraud or complex requests.

Outcome. Customers complete everyday banking tasks in chat while risk cases route to specialists with full context.