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Turn healthcare complexity into consumable decisions.

Connect claims, eligibility, benefits, clinical, provider, member and operational context. Yellowfirst turns healthcare complexity into explainable, role-specific next-best actions — with evidence, confidence and human approval.

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AI recommends. Humans decide. Every recommendation carries its evidence, its confidence and its approver.

Member Benefits AI

One member call, end to end

Live call

Identity verified. Coverage understood.

AI guides HIPAA identity verification, then retrieves the member's current eligibility and relevant benefit rules.

HIPAA verification completeIdentity checks completed
YF
MEMBER COVERAGEMedical PPO
✓ Securely verified
MEMBERIdentity matched
STATUSActive
EligibilityActive
NetworkIn-network
Deductible left$1,250
Coinsurance20%
Identity + authorization verificationCoverage confirmed ✓

“I may need heart surgery. Am I covered, what could I pay, and can I use my cardiologist?”

AI assists the service agent through one conversation, gathering the right context before any protected benefit information is disclosed.

Member CallMember 360EligibilityBenefitsProviderPolicy
CALL LIVEMember needs benefit guidance
6 SYSTEMSContext orchestrated
AI ASSISTHuman agent remains in control

What could the member pay — and is the provider connected?

AI combines plan accumulators, benefit rules and network data to give the agent a consumable answer, while clearly labeling cost as an estimate.

EST.Not a guarantee of final member responsibility
  • DEDDeductible remaining$1,250
  • COINIn-network coinsurance after deductible20%
  • PROVCardiologistIN
  • FACSelected facilityIN
  • BENCardiac surgery benefitCOVERED

Prior authorization requirement detected.

AI checks the procedure, benefit and medical-policy context and prepares the next workflow instead of asking the member to start over.

Recommended action: Start Prior Authorization

Member, eligibility, benefit, provider and procedure context pre-populated for review
Evidence
7 sources assembledEligibility · benefits · provider · policy · member context
Confidence
94%Authorization rule and plan context agree
AI task
Prepare PA requestForm created on behalf of the member for agent review

Agent approved. Prior auth workflow started.

MustExplain benefits and tell the member to contact the provider separately.
BetterConfirm benefits, network and authorization requirement in the same call.
BestPrepare the prior-auth workflow with known context so the agent can review and start it now.
Approved by
Member Service Agent
Benefits Support · Live call
✓
APPROVED to Start Prior Authorization
Human decision recordedAudit trail · Benefits Call

One member question. Multiple systems. One consumable answer. CALL-20418

Not another dashboard. A decision layer.
  • Reads every connected system
  • Names the action
  • Shows its working
  • Waits for a person

Healthcare payer decision intelligence

From quote to card — one connected decision context.

What does a healthcare Decision Intelligence Layer connect?
It connects commercial, member, clinical and operational context across the payer lifecycle: group and census data, underwriting rules, rating and product configuration, quotes, enrollment, eligibility and benefits, claims, prior authorization, provider networks, care management, member interactions, clinical data, renewal history, policies, documents and X12/EDI transactions — while leaving systems of record in place.

Commercial lifecycle · Growth, pricing & retention
01◎

Group / Prospect

Employer, broker, census, geography, segment & product interest

02◈

Underwriting

Risk assessment, census validation, history, rules & evidence

03▦

Rating

Product, geography, age bands, plan design, contribution & pricing rules

04▤

Quote / Proposal

Plan options, premiums, benefit comparisons & scenario modeling

05✓

Enrollment

Group setup, member eligibility, elections, effective dates & plan selection

06↻

Renewal

Experience, utilization, rate change, retention risk, plan migration & outreach

Commercial decisions become member coverage context↓
Member & care lifecycle · Service, utilization & outcomes
07◉

Coverage

Eligibility, effective dates, plan status & coverage tier

08▤

Benefits

Copay, deductible, coinsurance, limits & accumulators

09▧

Claims

History, status, adjudication, payment & member responsibility

10◇

Authorization

PA requirements, criteria, status, evidence & turnaround context

11◎

Provider

Network, directory, specialty, contracting & access context

12♡

Care

Care management, utilization, open needs, gaps & interventions

13▣

Member

CRM history, contact-center interactions, preferences & prior actions

14✚

Clinical

FHIR, HIE/EHR, labs, encounters & relevant clinical context

15≡

Evidence

Policies, documents, rules, X12/EDI, provenance & freshness

16⚡

Action

Evidence-backed next-best action with confidence and human approval

Existing systems stay in place
CRM / Broker PortalUnderwriting PlatformRating EngineEnrollmentFacets / Core AdminMember 360Prior AuthCXoneCare MgmtDocuments
✦
YELLOWFIRSTDecision Intelligence LayerCONNECT · UNDERSTAND · REASON · RECOMMEND
Standards & exchanges
FHIRX12 / EDIREST / APIsDocumentsHIE / EHRWebhooksBatch / SFTP
✓ Evidence-backed✓ Source traceability✓ Confidence scoring✓ Policy-aware✓ Human approval✓ Audit trail

Group / Prospect → Underwriting → Rating → Quote → Enrollment → Coverage → Benefits → Claims → Authorization → Provider → Care → Member → Clinical → Evidence → Action → Renewal ↺

The decision loop

Nine stages, one closed loop.

Your systems of record stay where they are. Yellowfirst reads them, decides, hands the call to a person, then learns from what happened.

Stage 1 of 9

Connect and unify

Unify eligibility, benefits, accumulators, claims, prior authorization, provider, care management, member, contact-center, clinical/FHIR, document and EDI context without replacing systems of record.

Closed-loop intelligence. Every outcome makes the next decision smarter.

MINDMAP

Enterprise AI Customization

From business need to continuous learning — a practical, governed, and impactful approach.

AI with Human Control.
UX with Human Impact.
✦01
DEFINEFrame the Intelligence
▤02
PREPAREBuild the Trusted Foundation
◆03
CUSTOMIZEEngineer the AI System
⌕04
EVALUATEProve Quality, Safety & Reliability
☁05
DEPLOYOperationalize with Control
↻06
LEARN & IMPROVETurn Experience into Better AI
            
Enterprise AI
CustomizationBuild. Operate. Learn.
Create real value.
Business ProblemsUse CasesUser RolesTasks & DecisionsExpected OutputsSuccess MetricsRisks & Autonomy
Collect Data (Systems, Docs, APIs)Clean & DeduplicateNormalize & LabelStructure & Create MetadataSemantic Model / OntologyGovernance, Security & AccessEstablish Data Lineage
Context EngineeringAdvanced RAG (vector, keyword, graph)Prompt & Behavior EngineeringFew-Shot ExamplesTools & APIs IntegrationAgents & WorkflowsModel Routing & OptimizationFine-Tuning (when appropriate)
Gold DatasetAutomated EvalsAccuracy & GroundednessHallucination TestsRed TeamingEdge CasesSME ValidationRegression Testing
Version & Release ManagementPermissions & GuardrailsDeploy (Cloud / On-Prem)Observability & MonitoringAuditability & ComplianceCanary / A-B TestingRollback Capability
Capture User FeedbackLog Expert CorrectionsTrack Real-World OutcomesAnalyze Failures & GapsCurate & Label Training DataRe-evaluate & OptimizeFine-Tune / Retrain (when needed)Re-deploy Improvements
Turning complexity into human progress.REAL PROBLEMS   +   REAL PEOPLE   +   REAL IMPACT

Healthcare payer intelligence

One AI layer across the member journey.

Benefits, claims, prior authorization, onboarding, policy, payment and renewal decisions — connected through the same member, plan, provider and clinical context.

CALL MIX

Where member-service demand is coming from

100% ALL CALLS

Total member-service calls

HIGH-VALUE STARTING POINT 65% of calls are Benefits + Claims

Your call-mix signal makes these the highest-value place to start: answer faster, calculate correctly, explain clearly and trigger the next workflow while the member is still on the call.

BenefitsClaimsNext-best actionHuman approval

65% is presented as the supplied Benefits + Claims hero signal. The donut shows the separate call-mix breakdown you provided: Benefits 34.71%, Claims 19.32%, Billing 5.29%, Policy Management 5.70%, and Other 34.98%.

Medical

Benefits · claims · prior auth · care · provider · cost

Dental

Coverage · frequency · accumulators · network · estimates

Vision

Eligibility · allowances · network · frequency · member liability

Pharmacy

Formulary · benefit · drug coverage · cost · authorization signals

Built for different lines of business — without rebuilding the intelligence layer.Example LOB mix from your supplied call-volume chart
Commercial · 53%Government Programs · 25%ASO · 17%FEP / FEHB · 5% Medicare AdvantageMedicaid / CHIPQHP / ExchangeEmployer Groups

One intelligence layer

One context. Decisions for every role.

The member journey crosses plans, enrollment, service, authorization, clinical review, claims, providers, payments and governance. Yellowfirst keeps the context connected — then gives each role the evidence, permissions and next-best action they need.

01

PLAN & GROW

ProductSales / AccountUnderwriting
02

ENROLL & SERVE

EnrollmentEligibilityMember ServiceContact Center
03

AUTHORIZE & CARE

PA SpecialistUM ManagerClinical ReviewerMedical DirectorCare Manager
04

CLAIM & PAY

Claims ExaminerClaims ManagerPayment IntegrityFinance
05

PROVIDER & PHARMACY

Provider ServiceNetwork ManagerPharmacy / PBM
06

RESOLVE & GOVERN

Appeals & GrievancesComplianceQuality / Risk
07

LEAD & OPTIMIZE

COOCIOCMOExecutive
Same evidence→Role-specific context→Right permissions→Next-best action→Human decides

Intelligence for the person who owns the decision.

Twelve agents, one per role. The same signals produce a different decision for each of them, and accountability stays with the business.

01 — Finance

Finance AI

Surfaces medical cost, utilization and payment decisions that need attention.

02 — Planning

Eligibility & Benefits AI

Explains eligibility, benefits, accumulators and coverage context before action.

03 — Operations

Prior Authorization AI

Assembles policy, clinical evidence and member context to recommend the next authorization step.

04 — Provider Ops

Claims AI

Finds claims risk, exceptions, edits and next-best actions before they become rework.

05 — Commercial

Provider Service AI

Brings provider contract, network, claim and service context into one decision.

06 — Care Navigation

Care Navigation AI

Prioritizes care gaps, outreach and navigation actions as member context changes.

07 — Member Service

Member Service AI

Gives service teams the next best answer or action with evidence and confidence.

08 — Channel

Underwriting AI

Combines group, risk, census and rating context into explainable underwriting decisions.

09 — Leadership

Executive AI

Reduces operational noise to the decisions healthcare leaders need now.

10 — Quality and regulatory

Compliance AI

Applies policy guardrails, auditability and explainable decision history.

11 — Customer service

Contact Center AI

Answers from live member and plan context, or escalates when confidence is insufficient.

12 — Enablement

Appeals & Grievances AI

Organizes case history, policy and evidence to support appeals and grievances workflows.

Finance AI

Finance AI

Finance

Surfaces medical cost, utilization and payment decisions that need attention.

Eligibility & Benefits AI

Planning

Explains eligibility, benefits, accumulators and coverage context before action.

Prior Authorization AI

Operations

Assembles policy, clinical evidence and member context to recommend the next authorization step.

Claims AI

Provider Ops

Finds claims risk, exceptions, edits and next-best actions before they become rework.

Provider Service AI

Commercial

Brings provider contract, network, claim and service context into one decision.

Care Navigation AI

Care Navigation

Prioritizes care gaps, outreach and navigation actions as member context changes.

Member Service AI

Member Service

Gives service teams the next best answer or action with evidence and confidence.

Underwriting AI

Channel

Combines group, risk, census and rating context into explainable underwriting decisions.

Executive AI

Leadership

Reduces operational noise to the decisions healthcare leaders need now.

Compliance AI

Quality and regulatory

Applies policy guardrails, auditability and explainable decision history.

Contact Center AI

Customer service

Answers from live member and plan context, or escalates when confidence is insufficient.

Appeals & Grievances AI

Enablement

Organizes case history, policy and evidence to support appeals and grievances workflows.

CAQH · Healthcare Industry Benchmarking

How automated is healthcare administration today?

The latest CAQH benchmarks show a split market: some transactions are nearly fully electronic, while others still depend heavily on manual workflows. That gap is where the largest automation opportunities remain.

Latest published CAQH benchmark figures
2024 Index / 2025 CAQH industry updates

Eligibility & Benefits

A mature administrative workflow
Medical · 2024
Transaction modeMedicalDental
Fully electronicASC X12N 270/271
96%
82%
Partially electronicWeb portals / IVR
4%
15%
Fully manualPhone / mail / fax / email
0%
3%

Medical eligibility is now close to fully electronic, showing what standardized transactions can achieve at scale.

Attachments

A major remaining automation gap
Medical · 2024
Transaction modeMedicalDental
Fully electronicASC X12N 275 / HL7 CDA
32%
37%
Fully manualPhone / mail / fax / email
68%
63%

Attachments remain predominantly manual, making them one of the clearest opportunities for workflow redesign, interoperability and automation.

Eligibility automation opportunity$12.28B

Combined medical + dental savings opportunity from moving remaining manual/portal eligibility checks to fully electronic workflows.

Medical$11.7B

Potential industry savings.

Dental$580M

Potential industry savings.

Source: CAQH Index® and CAQH CORE 2025 industry update materials. Percentages are industry benchmarks, not Yellowfirst customer results. CAQH.org ↗
OMNICHANNEL CONTINUITY

Channels change. Context shouldn’t.

DECISION INTELLIGENCEONE CONTEXT
☎Phonecalls
→
▣Web Portalself-service
→
▯Mobile Appdigital actions
→
◌Chatconversation
→
✉Emailthreads + attachments
→
SMSSMSmessages
→
▤Physical Mailcorrespondence
→
FAXFaxyes, still
→
Portal→Chat→Email + Docs→Call→ONE CONTEXT
Healthcare integration landscape

Connect to the tools teams already use.

A practical connector map for payer operations: verified public APIs where available, healthcare transaction standards for core workflows, and governed integration paths for proprietary/internal systems.

Member & Call Operations

CX
NICE CXoneCalls, email, agent sessions, routing, real-time & reporting data
REST / OAuth
F
TriZetto FacetsEligibility, benefits, claims and core administration data
REST / SOAP
EDI
Healthcare EDIEligibility, claims, claim status, remittance and prior-auth transactions
X12

Knowledge & Collaboration

SP
SharePoint / E-SourceReference content, guides, files and enterprise knowledge
Graph / REST
T
Microsoft TeamsTeams, channels, collaboration and workflow context
Graph API
O
Microsoft OutlookEmail, calendar, contacts and notifications
Graph API

Enterprise & Payments

WD
WorkdayWorker, schedule and enterprise workflow integration
REST / SOAP / Graph
CS
CybersourcePayment authorization, capture and secure payment services
REST
FHIR
FHIR Interoperability APIsPatient, provider, payer-to-payer and prior-authorization workflows
HL7 FHIR

Known Internal / Client Systems

R
RTPO LaunchpadCall notes and follow-up workflows
Integration path
360
Member 360Member context and general information
Integration path
SE
Service EstimatorService-cost estimates by service codes
Integration path

Provider & General Information

SC
Sapphire Care SelectProvider details and care-network lookup
Integration path
TSG
TSG Command Comm CentralID-card verification workflow
Integration path
WS
WebStationDaily task scheduling
Integration path

Standards & Connector Layer

API
API Gateway / Integration LayerAuthentication, orchestration, transformation, logging and policy enforcement
Governed
FHIR R4RESTSOAPOAuth 2.0OpenID ConnectX12 EDIWebhooksSFTP / Batch
Connector readiness: “API” labels above are based on publicly documented interfaces. Internal/proprietary tools from the supplied workflow map are intentionally labeled Integration path until their tenant-specific API, database, export, RPA or vendor interface is confirmed. This avoids claiming an API where public documentation does not establish one.

One layer. Different decisions.

The model does not change by industry. The decisions do.

Prior Auth

  • Prior Auth
  • Quality
  • Care Mgmt
  • Claims

Predict, prioritize, act

Healthcare

  • Member
  • Claims
  • Prior authorization
  • Underwriting

Predict, prioritize, act

FinTech

  • Risk
  • Service
  • Operations
  • Growth

Predict, prioritize, act

Provider Ops

  • Claims
  • Routing
  • Delivery
  • Exceptions

Predict, prioritize, act

Retail & CPG

  • Availability
  • Store
  • Channel
  • Trade

Predict, prioritize, act

Asset operations

  • Integrity
  • Inspection
  • Care Mgmt
  • Compliance

Predict, prioritize, act

Every recommendation can show why, how sure, and who approved it.

Human control is not a setting you switch on later. It is where the layer ends: a decision with an owner, a record, and a way to say no.

Decision governance

  • Evidence trace
  • Confidence score
  • Human approval
  • Policy guardrails
  • Audit history

Yellowfirst in one minute

Yellowfirst is a decision intelligence layer: software that sits above claims, eligibility, benefits, clinical, provider and operational systems and converts their signals into one specific recommended action. Every recommendation arrives with the evidence behind it, a confidence score, a policy check and a named human approver. It adds a layer over your existing systems without replacing any of them.

  • Its output is a decision, not a chart. The difference is that someone can act on it without interpreting it first.
  • It is additive: Claims Core, CRM / Member 360, Prior Auth, FHIR / Clinical, Care Mgmt, data lakes, documents and APIs all stay where they are.
  • Every recommendation carries four things — the evidence, a confidence score, the policy check and a named approver.
  • Twelve healthcare agents support role-specific decisions across finance, eligibility, prior auth, claims, provider, care navigation, member service, underwriting, compliance and operations.
  • The principle is fixed: AI recommends, humans decide, and the audit trail records both.
  • Engagements start with one decision, proven end to end, before anything expands.
Yellowfirst decision intelligence layer at a glance
CategoryDecision intelligence layer for healthcare payers
Deployment modelSits above existing systems; integrates over secure APIs and event streams
Connects toClaims Core, CRM / Member 360, Prior Auth, Contact Center and FHIR / Clinical, Care Mgmt, data lakes, documents, internal APIs
Core capabilitiesSemantic context, business rules, models and agents, decision memory, policy
OutputRole-specific next-best action with evidence, confidence score and approval gate
Agents availableFinance, Eligibility & Benefits, Prior Authorization, Claims, Provider Service, Care Navigation, Member Service, Underwriting, Executive, Compliance, Contact Center, Appeals & Grievances
Industries servedPrior Auth, healthcare, fintech, supply chain, retail and CPG, asset operations
GovernanceEvidence trace, confidence score, human approval, policy guardrails, audit history
Operating principleAI recommends. Humans decide.
ProviderYellowfirst Experience LLC, Texas, United States

Questions people ask before the demo

What is a decision intelligence layer?
A decision intelligence layer is software that sits above systems of record such as claims, eligibility, benefits, clinical, provider and operational platforms and converts their signals into a specific recommended action. Unlike a reporting tool, it produces a decision rather than a chart: the action, the evidence behind it, a confidence score and a named human approver.
How is Yellowfirst different from a BI dashboard?
A dashboard shows the current state and leaves interpretation to the viewer. Yellowfirst completes the interpretation. It names the risk, assembles the supporting evidence, scores its confidence, proposes the action, routes it to the person accountable for that decision, and records what was approved and what resulted.
Do we have to replace our core administration, prior authorization or data warehouse?
No. Yellowfirst is deliberately additive. It sits between existing healthcare systems and the people who act on them, reading from and writing to those systems through secure APIs and event streams. Systems of record stay where they are and keep their existing ownership, licensing and security model.
What does role-specific mean?
The same underlying signals produce different decisions for different people. A prior authorization nurse sees the clinical criteria and missing documentation. A finance leader sees the cost and utilization impact of that same case. Each role gets the context, language and approval rights that belong to their job.
Can the AI act on its own without approval?
Not where it matters. The operating principle is that AI recommends and humans decide. Recommendations pass through a human gate where the accountable owner can approve, modify or reject them, and policy guardrails constrain what can ever be proposed. Every decision leaves an audit trail.
What systems does Yellowfirst connect to?
claims, eligibility, benefits, provider data, clinical and FHIR sources, pharmacy, CRM / Member 360, contact-center platforms, data lakes and warehouses, unstructured documents, and internal APIs. Connections run over secure APIs and event streams, so the layer reads live operational context rather than a nightly export.
Which roles get their own agent?
Twelve agents ship today, one per role: Finance, Eligibility, Prior Auth, Claims, Provider, Care Navigation, Member Service, Underwriting, Executive, Compliance, Support and Training. Each assembles the context that one role needs and recommends action in that role's language, so medical management, member service and finance leaders see different decisions drawn from the same signals.
How do you prove value before a full rollout?
By scoping a single decision. Yellowfirst maps the systems involved, the context required, the recommendation, the human approval step and the measurable outcome, then proves the loop on that one use case before anything is expanded across functions.
How is a decision intelligence layer different from an AI agent?
An agent performs a task. A decision intelligence layer decides which task is worth performing and who should authorise it. Yellowfirst runs twelve role-based agents underneath the layer, but the layer is what assembles cross-system context, ranks the options, attaches evidence and confidence, and routes the call to an accountable human.
What technology is the Yellowfirst decision intelligence layer built on?
It runs on Google Cloud. Data and analytics use BigQuery, Dataflow and Pub/Sub over a data lake; the AI and ML layer uses Vertex AI covering models, LLMs and retrieval-augmented generation; a semantic layer holds context and knowledge; and security and governance run on IAM, KMS and VPC with full audit and compliance.
Who inside a business actually uses it?
The person accountable for the decision, not an analyst preparing a report. In practice that is claims leaders, prior authorization teams, underwriting, member service, provider operations, care management, compliance, finance and executives. Each gets a role-specific agent that recommends in their own language.
What happens when a recommendation turns out to be wrong?
Two things catch it. The human approval gate means a person can modify or dismiss any recommendation before it executes, so a wrong call rarely becomes a wrong action. Then the outcome stage measures what actually happened against what was predicted, and that result feeds decision memory so the same mistake is less likely next time.

What should your data help someone decide tomorrow?

We map the systems, the context, the recommendation, the human approval and the measurable outcome — then prove it on one use case.

This opens an email to karna@yellowfirst.com with your two answers already filled in.