vellum for
Financial services

Intelligent Claims Processing
Automatically analyze claim documents, photos, and supporting materials to accelerate adjudication while maintaining human oversight for complex decisions.
Risk Assessment Automation
Evaluate applications using multiple data sources—credit, IoT, satellite imagery—to improve underwriting speed and accuracy without replacing professional judgment.
Customer service
Deploy AI-powered policy guidance and claims support that provides instant, accurate responses while escalating complex issues to human representatives.
Fraud Detection & Prevention
Identify suspicious patterns across claims data and customer interactions to flag potential fraud while reducing false positives that impact legitimate customers.
Policy Administration Automation
Streamline policy updates, renewals, and modifications through intelligent document processing that integrates seamlessly with existing systems.
Regulatory Compliance Monitoring
Automatically track and report compliance requirements across multiple jurisdictions while maintaining detailed audit trails for regulatory review.
Market Intelligence
Analyze competitor pricing and market trends to optimize product positioning and rate adjustments based on real-time market data.
Customer Risk Profiling
Build comprehensive risk profiles using historical claims, payment patterns, and external data sources to improve portfolio management and pricing accuracy.

Use-cases

Ambient scribing
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Patient navigation
Automate follow-ups, appointment scheduling, and triage so patients get the right care without delays.
Virtual coaching
Deliver personalized, adaptive health guidance through AI chat that learns from each patient’s history.
Charting and EHR Updates
Push clean, structured interaction data directly into EHR systems for easy access and compliance.
HCC Diagnosis Support
Flag potential undiagnosed conditions by analyzing past visits, labs, medications, and symptoms.
Prior Authorization Assistant
Automate gathering, verifying, and submitting documentation for insurance approvals.
Clinical Summarization
Condense long medical histories or chart notes into quick-reference summaries for providers.
Symptom Checker & Intake
Collect structured symptom data from patients before appointments to speed up triage.

Use-cases

Ambient Scribing
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Patient Navigation
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Virtual Coaching
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Fraud detection and prevention
Identify suspicious patterns across claims data and customer interactions to flag potential fraud while reducing false positives that impact legitimate customers.
Policy administration automation
Streamline policy updates, renewals, and modifications through intelligent document processing that integrates seamlessly with existing systems.
Regulatory Compliance Monitoring
Automatically track and report compliance requirements across multiple jurisdictions while maintaining detailed audit trails for regulatory review.
Market intelligence and pricing
Analyze competitor pricing and market trends to optimize product positioning and rate adjustments based on real-time market data.
Customer risk profiling
Build comprehensive risk profiles using historical claims, payment patterns, and other data sources to improve portfolio and pricing accuracy.

Ambient Scribing
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Patient Navigation
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Virtual Coaching
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Charting and EHR Updates
Push clean, structured interaction data directly into EHR systems for easy access and compliance.
HCC Diagnosis Support
Flag potential undiagnosed conditions by analyzing past visits, labs, medications, and symptoms.
Prior Authorization Assistant
Automate gathering, verifying, and submitting documentation for insurance approvals.
Clinical Summarization
Condense long medical histories or chart notes into quick-reference summaries for providers.
Symptom Checker & Intake
Collect structured symptom data from patients before appointments to speed up triage.

Transformation example

Insurance Claims AI Transformation Journey

With Vellum, a claims director can prototype intake, fraud, and adjudication logic in workflows while engineers get access to validated AI ideas, and can execute without wasting engineering resources. Each stage is traceable and measured, showing clear impact in faster processing, higher fraud accuracy, and lower costs. The result is a collaborative process built for maximum ROI.
Claim intake
Process & validate all claim information
Parallel Analysis
Risk, policy, damage & document assessment
External Verification
DMV, property, weather & fraud databases
Adjudication
Final decision with detailed rationale
Output generation
Status, risk score, audit trail & decision
Lisa Chen
Claims Director | 15+ years claims management experience

Defines claims processing logic, fraud detection criteria, and business rules through Vellum's visual interface. Can approve pilots up to $75K; requires CFO approval for large initiatives. Must demonstrate ROI in 24 months and maintain regulatory compliance.

David Rodriguez
AI Engineering Lead | Technical lead

Builds production infrastructure, integrations, and ensures enterprise-grade reliability and compliance. Can architect solutions but requires InfoSec, Compliance, and MRM sign-off. Must maintain 99.9% uptime and complete audit trail compliance.

Ambient Scribing
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Patient Navigation
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Virtual Coaching
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Charting and EHR Updates
Push clean, structured interaction data directly into EHR systems for easy access and compliance.
HCC Diagnosis Support
Flag potential undiagnosed conditions by analyzing past visits, labs, medications, and symptoms.
Prior Authorization Assistant
Automate gathering, verifying, and submitting documentation for insurance approvals.
Clinical Summarization
Condense long medical histories or chart notes into quick-reference summaries for providers.
Symptom Checker & Intake
Collect structured symptom data from patients before appointments to speed up triage.

Transformation example

AI Medical Chatbot: Patient Intake

With Vellum, healthcare teams can prototype patient intake flows, triage logic, and structured search queries in workflows. Clinicians get validated AI ideas, while engineers only build what’s proven to work. Each stage is measurable and traceable, showing impact in faster patient matching, reduced admin burden, and safer outcomes. The result is a collaborative process designed for patient trust and operational efficiency.
Patient Chat Intake
Free-text input or voice query captured in natural language.
Entity Extraction
AI extracts structured data: concern, severity, insurance, provider type, location, emergency flag.
External Verification
Information cross-checked against insurance eligibility, provider availability, and compliance rules.
Routing and Matching
System generates structured query and matches patient with the right provider/service.
Output generation
Structured JSON query, provider match, triage notes, and safe-response messaging.
Dr. Sarah Patel
Clinicial Director | 10+ years patient care experience

Designs intake logic and ensures clinical safety. Defines escalation paths (emergency vs non-emergency) and validates AI prototypes against compliance standards. Requires ongoing consultation with hospital ethics committee and medical staff leadership.

Mark Alvarez
AI Engineering Lead | Technical lead

Builds integrations into EMR systems and ensures secure data handling. Implements production-grade infrastructure for patient data. Must maintain audit logging, uptime, and strict regulatory compliance (HIPAA, SOC-2).

Ambient Scribing
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Patient Navigation
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Virtual Coaching
Turn full patient visits into accurate, structured medical notes, freeing clinicians from manual documentation.
Charting and EHR Updates
Push clean, structured interaction data directly into EHR systems for easy access and compliance.
HCC Diagnosis Support
Flag potential undiagnosed conditions by analyzing past visits, labs, medications, and symptoms.
Prior Authorization Assistant
Automate gathering, verifying, and submitting documentation for insurance approvals.
Clinical Summarization
Condense long medical histories or chart notes into quick-reference summaries for providers.
Symptom Checker & Intake
Collect structured symptom data from patients before appointments to speed up triage.
Compliance and risk foundation

Internal governance before operational deployment

Stakeholder alignment and risk review
  • Lisa Chen, Claims Director: Defines a conservative pilot for personal auto claims in Texas, targeting 8–12% efficiency gains and securing $65K approval with clear success criteria.
  • David Rodriguez, AI Engineering Lead: Builds the compliance-ready foundation using Vellum’s audit trails, monitoring, governance, and data lineage to cut prep time in half and ensure traceability.
Vellum advantage
Comprehensive audit trail capabilities provide the documentation infrastructure needed for compliance efforts, reducing preparation time from 8 months to 4 months
Model risk management and internal approval
  • Maria Santos (Model Risk Management): Uses Vellum’s evaluation, bias testing, and execution tracking to validate models, set performance baselines, and document MRM compliance.
  • James Wong (Chief Risk Officer): Approves a conservative pilot scope with human-in-the-loop validation, weekly performance monitoring, and clear exit thresholds to manage risk.
Vellum advantage
Built-in evaluation frameworks and statistical testing capabilities provide the tools needed for MRM documentation.
Technical integration and security validation
  • Patricia Kim, Information Security Lead: Oversees claims system integration with Duck Creek, implements encryption and access controls, and leverages Vellum’s built-in security architecture to cut custom security work and meet a 6-month integration timeline.
  • Robert Chen, Compliance Officer: Focuses on audit readiness by using Vellum’s audit trails, traceability, and documentation standards to prepare for regulatory examinations and ensure transparent customer communication.
Vellum advantage
Enterprise-grade security architecture built into platform reduces custom security development. Complete audit trail generation supports regulatory examination preparedness
Results

Conservatively scoped, compliance-ready pilot with MRM validation, CRO risk controls, secure system integration, and full audit documentation.

Controlled pilot with strict oversight

Risk and use-case validation with measured learning

Parallel processing with human override
  • Controlled rollout: Gradual AI adoption with human override, moving from full manual decisions to limited autonomy on low-value claims.
  • Performance gains: By month 24, processing time drops 15%, fraud detection improves 6%, and cost per claim falls 10%.
  • Change management impact: Adjuster satisfaction rises from 48% to 65% with structured adoption and oversight.
Vellum advantage
Weekly refinements and 8–12 updates per year, supported by Vellum’s governance guardrails for safe iteration.
Validation and documentation
  • Compliance assurance: Zero AI-related complaints, full audit trails, and bias testing show fairness and transparency.
  • Quality maintained: Error rate steady at 2.3% and customer satisfaction sustained at 71%.
Vellum advantage
Regulatory readiness: Comprehensive documentation prepared with Vellum’s traceability for examination.
Results

6,200 claims processed with $89K annual savings, reflecting a 14% cost improvement. Error rate steady at 2.3% and customer satisfaction sustained at 71%.

Geographic Scaling

Careful scaling with state-by-state adaptation

Multi-State Expansion
  • Expanded to property claims under $15K with 70% workflow reusability and adaptation to regional fraud patterns, reaching 14,000 AI-assisted claims annually by Month 42.
  • Processing time cut to 8.2 days, fraud detection improved to 76%, and annual savings increased to $285K.
Business Impact from Vellum
Workflow reusability framework enables 70% logic transfer vs. starting from scratch.
Second State Expansion (Florida)
  • 6–9 months of adaptation for state regulations, fraud patterns, and local adjuster training, with Vellum’s governance framework supporting compliance and customization.
  • Different legacy system setup, API limitations, and regional performance issues require targeted engineering and optimization.
Business Impact from Vellum
Platform's governance framework transfers while enabling substantial local customization
Results

Multi-state AI claims system delivering faster processing, higher fraud detection, and $285K annual savings in Texas, while adapting workflows and integrations for Florida expansion.

Market Leadership

Competitive differentiation through accumulated intelligence

Adding advanced capabilities
  • Predictive severity modeling, subrogation detection, seasonal damage protocols, and vendor analytics become part of the workflow after 4+ years of Vellum use.
Business Impact from Vellum
Processing time drops to 6.5 days, fraud detection improves to 81%, NPS rises to 58, and costs are 24% lower than baseline.
Leadership and knowledge sharing
  • Publish benchmark reports and whitepapers based on 95,000+ processed claims
  • Collaborate with insurers, healthcare providers, and technology vendors on AI standards
Business Impact from Vellum
Audit trails, workflow transparency, and governance guardrails that make it possible to confidently share benchmarks, collaborate with regulators, and set industry standards
Results

Market-leading claims AI program that delivers faster processing, higher fraud accuracy, lower costs, and industry recognition.

Compliance and risk foundation

Internal governance before operational deployment

Stakeholder alignment and risk review
  • Dr. Sarah Patel, Clinical Director: Defines a conservative pilot for intake queries in California, targeting 8–12% intake efficiency gains and securing $60K approval with clear success criteria.
  • Mark Alvarez, AI Engineering Lead: Builds the compliance-ready foundation using Vellum’s audit trails, monitoring, governance, and data lineage to cut prep time in half and ensure HIPAA traceability.
Vellum advantage
Vellum's audit trail capabilities accelerate the technical documentation component of HIPAA compliance by reducing custom logging development time, while legal and policy components proceed on standard timelines.
Model risk management and internal approval
  • Maria Lopez, Model Risk Manager: Uses Vellum’s evaluation, bias testing, and execution tracking to validate intake models, set performance baselines, and document MRM compliance.
  • James Wong, Chief Risk Officer: Approves a conservative pilot scope with human-in-the-loop validation, weekly performance monitoring, and clear exit thresholds to manage patient safety risk.
Vellum advantage
Vellum's evaluation frameworks provide technical infrastructure supporting MRM documentation requirements, while clinical validation and risk assessment require additional healthcare-specific protocols.
Technical integration and security validation
  • Patricia Kim, Information Security Lead: Oversees integration with the provider directory and EHR, implements encryption and access controls, and leverages Vellum’s security architecture to cut custom security work and meet a 6-month integration timeline.
  • Robert Chen, Compliance Officer: Focuses on HIPAA readiness by using Vellum’s audit trails, traceability, and documentation standards to prepare for regulatory examinations and ensure transparent patient communication.
Vellum advantage
Enterprise-grade security architecture reduces custom development, with audit trail generation that supports regulatory examination readiness.
Results

Compliance-ready pilot with MRM validation, CRO risk controls, HIPAA-secure integration, and full audit documentation. Implementation included 6-month physician training program, ongoing clinical advisory board oversight, and quarterly compliance audits with healthcare legal counsel.

Controlled pilot with strict oversight

Risk and use-case validation with measured learning

Parallel processing with human override
  • Controlled rollout: Gradual chatbot adoption with clinician override, moving from manual triage to limited autonomy for low-risk intake queries.
  • Performance gains: By month 24, intake time drops 15%, misclassification rate improves 7%, and admin cost per intake falls 12%.
  • Change management impact: Clinician satisfaction rises from 52% to 68% with structured adoption and oversight.
Vellum advantage
Weekly refinements and 8–12 updates per year, supported by governance guardrails for safe iteration.
Validation and documentation
  • Chatbot-related complaints reduced to less than 0.5% of interactions, with all complaints resolved within 24 hours through established escalation protocols.
  • Intake accuracy maintained at 96% for routine cases, with complex cases requiring clinical review maintaining separate accuracy metrics.
Vellum advantage
Regulatory readiness with comprehensive documentation prepared through Vellum’s traceability features.
Results

8,500 patient intakes processed with human oversight for 30% of complex cases, achieving $95K annual savings primarily through administrative efficiency gains rather than clinical workflow changes.

Geographic Scaling

Careful scaling with state-by-state adaptation

Multi-State Expansion
  • Expanded to mental health and primary care intake with 70% of core technical infrastructure reusable across states, with significant adaptation required for local provider networks, insurance relationships, and regulatory variations.
  • Intake processing time cut to 6.8 minutes, classification accuracy improved to 97%, and annual savings increased to $310K.
Business Impact from Vellum
Workflow reusability enables 70% logic transfer vs. starting from scratch.
Second State Expansion (Florida)
  • 6–9 months of adaptation for local regulations, insurance networks, and provider availability, with governance supporting compliance and customization.
  • Different EHR setups and API limitations require targeted engineering and optimization.
Business Impact from Vellum
Platform governance framework transfers seamlessly while allowing local customization.
Results

Multi-state AI chatbot delivering faster intake, higher accuracy, and $310K annual savings in California, while adapting workflows and integrations for Florida rollout.

Market Leadership

Competitive differentiation through accumulated intelligence

Adding advanced capabilities
  • Predictive care triage, insurance eligibility verification, appointment optimization, and population health analytics become part of the chatbot workflow after 4+ years of Vellum use.
Business Impact from Vellum
Patient satisfaction with intake process improves from baseline 74% to 82%, with AI-assisted cases showing equivalent satisfaction to human-only intake. Administrative costs reduced 18% while maintaining equivalent clinical outcomes and adding AI governance overhead costs.
Leadership and knowledge sharing
  • Collaborate with healthcare research institutions to publish peer-reviewed studies on AI-assisted intake efficiency, following IRB approval and patient consent protocols for any research publications.
  • Collaborate with hospitals, insurers, and regulators on AI safety standards.
Business Impact from Vellum
Audit trails, workflow transparency, and governance guardrails enable sharing of benchmarks, collaboration with regulators, and industry standard-setting.
Results

Market-leading AI medical chatbot program delivering faster patient intake, higher accuracy, lower costs, and recognized as an industry benchmark.

Ship safer AI faster
Go from idea to production in hours, not months, so clinicians and patients see improvements sooner.
Collaborative Development
Product and clinicians can build and refine AI workflows in the low-code builder, developers keep control in code.
Built-in compliance
Test, evaluate, and monitor every change before release to meet safety and HIPAA standards.
Instant fixes in production
Trace issues in production, replay runs, and redeploy updates instantly without disruption.
sucCCESS STORIES

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Experiment
Engineers, PMs and domain experts can all iterate on AI business logic using our UI and SDK for AI development.
Evaluate
Quantitatively measure the quality, cost, latency and reliability of your AI system across a number of metrics until you reach your desired threshold.
deploy
Decouple your AI updates from application releases with native release management and environments included.
Monitor
Maintain full visibility in production using trace and graph views and quickly identify edge cases for further iteration.
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