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Experiment
Trusted by product-led companies, global enterprises & major service providers
What consumer retail companies build with Vellum
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
What consumer retail companies build with Vellum
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
What consumer retail companies build with Vellum
Demand forecasting and planning
Turn complex market signals into accurate demand predictions that procurement and planning teams can continuously optimize based on supplier performance and seasonal patterns.
Supplier risk and performance management
Automate supplier evaluation, risk assessment, and relationship scoring so procurement teams can make data-driven decisions while incorporating qualitative factors.
Inventory optimization
Deliver intelligent safety stock and reorder point recommendations that warehouse supervisors can adjust based on facility capabilities and demand variability.
Transportation and route optimization
Push optimized routing and carrier selection directly into TMS systems while enabling logistics coordinators to adjust for service commitments and performance data.
Supply chain and visibility monitoring
Flag potential disruptions by analyzing supplier performance, transportation delays, and inventory levels so operations teams can act proactively.
Procurement Intelligence
Automate spend analysis, contract compliance monitoring, and sourcing recommendations while enabling procurement professionals to incorporate strategic relationship factors.
Warehouse Operations Enhancement
Streamline pick path optimization, labor allocation, and space utilization through AI that warehouse supervisors can fine-tune based on operational knowledge.
Cross functional planning
Coordinate demand, supply, production, and logistics planning through integrated AI workflows that balance trade-offs across all supply chain functions.
Use-cases
What consumer retail companies build with Vellum
Demand forecasting and planning
Predict customer demand across channels and optimize inventory allocation based on trends, seasonality, and local market insights.
Personalized product recommendations
Deliver tailored product suggestions that balance customer preferences, inventory availability, and business objectives.
Dynamic pricing & promotions
Automate pricing decisions and promotional strategies based on competitive positioning, inventory levels, and customer behavior.
Customer service automation
Route inquiries intelligently and provide instant, accurate responses while maintaining brand voice and escalating complex issues.
Supply chain and vendor coordination
Streamline supplier communications, automate purchase orders, and optimize logistics based on demand patterns and delivery requirements.
Store operation automation
Optimize staffing schedules, task allocation, and store layouts based on customer traffic patterns and sales forecasts.
Customer experience optimization
Track customer interactions across touchpoints and optimize the shopping experience from discovery to purchase to support.
Market intelligence and competitive analysis
Monitor competitor pricing, analyze market trends, and identify opportunities for product positioning and promotional timing.
Use-cases
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
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.
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.
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.
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.
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).
What consumer retail companies build with Vellum
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
Vellum for Supply Chain: Crisis-Driven AI Transformation Journey
With Vellum, supply chain teams can prototype supplier monitoring workflows, risk detection logic, and escalation triggers in a controlled environment. Procurement leaders get validated AI signals before making sourcing decisions, while engineers only integrate models and systems that prove reliable. Each stage is measurable and auditable, showing impact in faster assessments, earlier warning of supplier stress, and fewer disruption costs. The result is a collaborative process built for risk visibility, regulatory compliance, and long-term supplier trust.
Supplier Data Collection
Pulls financials, credit ratings, and stability scores, along with quality and compliance metrics.
Signal Extraction
AI structures inputs into clear indicators: financial health, performance trends, and news sentiment risk flags.
Cross Verification
Signals validated against external data sources, benchmarks, and compliance rules to ensure accuracy.
Risk Scoring and Recommendations
System generates a numerical risk score, detailed assessment, and tailored mitigation actions.
Output generation
Structured report with risk score, recommendations, and assessment notes ready for procurement and compliance teams.
Primary personas
Oversees sourcing strategy and supplier stability. Approves solutions up to $250K with council review and sets standards for risk detection updates. Must balance early warning adoption and maintaining supplier relationships.
Architects AI solutions with 10+ years in enterprise systems and 4+ years in supply chain. Designs workflows within SAP while ensuring audit compliance. Requires approvals from InfoSec, Legal, and Compliance before deployment.
Critical Stakeholders with Veto Power
Executive sponsor with quarterly board reporting
Final validation on risk methodology and escalation
Data governance and system integration approval
Regulatory requirements and supplier communication protocols
Domain expert who lived through Zentech crisis.
What consumer retail companies build with Vellum
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
Vellum for Retail: Pricing AI Transformation Journey
With Vellum, a merchandising manager can prototype pricing logic, competitive response, and promotional strategies 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 improved pricing response, better margin management, and reduced operational costs. The result is a collaborative process built for maximum ROI.
Product Data Validation
Verifies product inputs such as SKU, cost, and current price, calculates margins, and checks inventory status.
Market Intelligence
Researches competitor pricing and market trends to provide insights that guide pricing strategy.
Pricing Evaluation
Analyzes validated product data and market inputs to generate optimal pricing options with rationale.
Pricing recommendation
Delivers recommended price, strategy details, and reasoning for business review and adoption.
Output generation
Structured report with recommended price, strategy notes, and supporting insights ready for retail and pricing teams.
Primary personas
Primary business champion with 15+ years pricing expertise. Defines pricing logic and competitive response rules through Vellum's visual interface.
Technical architect building production infrastructure and integrations. Ensures enterprise-grade reliability and compliance.
Supporting team
What consumer retail companies build with Vellum
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
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.
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
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
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.
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.
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.
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.
Market-leading AI medical chatbot program delivering faster patient intake, higher accuracy, lower costs, and recognized as an industry benchmark.
Compliance and risk foundation
Internal governance before operational deployment
Stakeholder alignment and risk review
- Rachel Thompson, Senior Director of Strategic Sourcing: Defines a conservative pilot with 8 critical electronics suppliers ($45M spend), targeting a 40% reduction in assessment time from the current 35–40 hours while maintaining decision quality. Secures $285K approval with strict success criteria and exit conditions.
- Michael Singh, Lead AI Engineer: Builds foundation architecture using Vellum’s pre-built orchestration and audit trail to cut setup time from 8 to 4 months. Designs monitoring with full workflow transparency, establishes governance documentation, and implements data quality validation as a key differentiator from custom builds.
Vellum advantage
Pre-built workflow orchestration and audit trail capabilities provide the infrastructure needed for enterprise compliance efforts, reducing architecture development time from 8 months to 4 months
Model risk management and internal approval
- Dr. Sarah Kim, Chief Risk Officer: Defines conservative pilot scope limited to electronics suppliers, with 12 months of human validation alongside AI. Leverages Vellum’s evaluation and statistical validation frameworks for risk documentation, monitors performance with built-in analytics, and enforces exit thresholds to protect supplier relationships.
- Jordan Martinez, IT Security Director: Reviews SAP supplier master data integration with a 6-month timeline for production readiness. Uses Vellum’s enterprise-grade security architecture to reduce custom development, implementing encryption and access controls through built-in governance frameworks.
Vellum advantage
Built-in evaluation frameworks and statistical validation capabilities provide the tools needed for risk methodology documentation. Enterprise-grade security architecture built into platform reduces custom security development requirements.
Technical integration and security validation
- Lisa Wang, Legal & Compliance Director: Prioritizes audit readiness over regulatory pre-approval, relying on Vellum’s audit trails and decision tracking for compliance preparedness. Defines supplier communication and transparency protocols, and sets documentation standards using the platform’s traceability features.
- 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
Complete audit trail generation and decision tracking supports compliance examination preparedness.
Compliance-ready pilot with CRO-defined risk controls, InfoSec-secure SAP integration, and full audit documentation. Implementation included 12 months of parallel human validation, governance and data quality frameworks, and quarterly reviews with legal and compliance leadership.
Controlled pilot with strict oversight
Conservative validation with measured learning
Parallel processing with human override
- Controlled rollout: Gradual AI adoption with human override, shifting from full manual validation to AI-flagged high-risk suppliers while traditional assessments run in parallel for comparison.
- Performance gains: By month 16, workflow refinements move from quarterly to monthly cycles, with conservative success metrics tracked through Vellum’s monitoring and evaluation tools.
- Change management impact: Stakeholders align on updates monthly, with weekly parameter reviews ensuring realistic pace and trust in AI-assisted supplier assessments.
Vellum advantage
Monthly workflow refinements vs. quarterly updates for traditional systems, enabled by platform's built-in governance guardrails
Validation and documentation
- Historical testing confirmed AI performance against three supplier failures, with the Zentech case showing stress signals 3–4 months before bankruptcy though not all indicators were captured.
- Live monitoring continued across eight suppliers under manual oversight, with results emphasizing the need for human interpretation and supplier relationship context in risk assessments.
By month 16, supplier assessment time dropped from 38 hours to 18–22 hours (42–53% improvement), with detection accuracy ranging 68–74% and a 12% false positive rate under manual review. The pilot covered eight suppliers, documented one case of disruption prevention, and maintained supplier satisfaction through enhanced communication protocols despite initial concerns.
Geographic Scaling
Knowledge transfer with local customization
Electronics Category Expansion
- Gradual supplier expansion: Additional 8 electronics suppliers (16 total under AI assistance)
- Supplier diversity: Different business models require parameter customization (contract manufacturers vs. component suppliers)
- Volume management: Enhanced monitoring for 16 suppliers representing $78M annual spend
Business Impact from Vellum
Workflow reusability framework enables 60-70% logic transfer vs. starting from scratch for each supplier
Cross-Category Knowledge Transfer
- 6-8 months adaptation time for chemicals category with different risk patterns
- Category-specific requirements: Chemical suppliers have different financial stress indicators and regulatory considerations
- Local business logic: Elena's electronics expertise provides foundation but requires chemistry category manager input
Business Impact from Vellum
Platform's governance framework and workflow structure transfer while enabling substantial category customization
Processing time improved from 18 to 12 hours per assessment (33% gain), with risk detection accuracy reaching 73–78% and false positives stabilizing at 10–14% after adjustments for supplier relationship sensitivity.
Competitive differentiation
Strategic capabilities with realistic advantages
Adding advanced capabilities with Vellum
- Portfolio risk modeling: Cross-supplier risk assessment for concentration analysis
- Predictive relationship management: Early warning system for supplier performance degradation
- Market intelligence integration: Industry trend analysis through supplier performance aggregation
- Strategic planning support: Risk-adjusted supplier development investment recommendations
Business Impact from Vellum
By month 42, assessment time fell to 8 hours, with 78–84% accuracy in detecting supplier stress 2–5 months early. Quarterly reviews combined predictive insights with human judgment, giving the organization a 12–18 month competitive edge in supplier risk management.
Knowledge sharing and recognition
- Industry participation: Rachel speaks at procurement conferences on practical AI implementation
- Knowledge sharing: Contribute to industry supplier risk management best practices (not proprietary technology licensing)
- Operational leadership: Enhanced supplier risk management capabilities recognized by industry peers
- Talent development: Procurement professionals with AI-assisted analysis experience command market premiums
After 48 months, the organization builds institutional intelligence from accumulated supplier data, develops advanced business logic on Vellum’s platform, adapts risk models in weeks instead of months, and gains credibility through responsible AI use in supplier management.
Pre-Vellum foundation
Business case established and technical requirements defined
Business case definition
- Jennifer has mapped 47 manual pricing decision points and 3-5 day competitive response cycles
- Executive sponsorship secured with $800K budget and 18-month ROI expectations
- Pilot categories selected (consumer electronics, 500+ SKUs) with success criteria defined
Defined technical requirements
- David completed ERP integration assessment with 6-month implementation timeline
- Robert established governance framework and compliance requirements
- Data quality issues identified with competitor intelligence accuracy benchmarks
Organizational readiness
- Change management strategy approved with user training protocols
- Cross-functional team assembled with defined roles and responsibilities
- Risk management and approval workflows documented
Executive backing secured with $800K budget, pilot categories defined, ERP and governance requirements scoped, and organization prepared with training, team alignment, and risk workflows.
Rapid implementation
Translating documented processes into production-ready AI workflows
Business logic translation
- Jennifer builds validated pricing scenarios directly in Vellum workflows
- Week 2: Holiday crisis tests AI-assisted competitive response in 6 hours vs. traditional 5 days
- Month 3: Amanda validates workflows through real pricing decisions with transparency building trust
Vellum advantage
Jennifer's 15+ years of pricing expertise gets captured in reusable workflows during implementation rather than lengthy discovery phase.
Accelerated technical development
- David implements ERP integrations using pre-defined requirements
- Month 4: Production deployment with comprehensive monitoring and rollback capabilities
- Robert validates governance controls through actual pricing decision audit trails
: Production-ready AI pricing system with validated business logic and enterprise controls, processing 1,000+ pricing decisions monthly.
Knowledge acceleration
Institutional learning that scales faster than individual expertise
Cross-category scaling
- Month 6: New category manager Tom inherits Jennifer's validated workflows
- Tom achieves 1.8% margin improvement in Month 1 vs. 3-month traditional learning curve
- Month 8: Electronics insights automatically inform home appliances pricing strategies
Business Impact from Vellum
Repurposed agent artifacts cut the time needed to scale into new categories, letting managers inherit validated workflows instead of starting from scratch.
Engineering Leverage Multiplier
- David's infrastructure enables daily business logic refinements without engineering tickets
- Month 9: Business teams handle 85% of pricing optimizations independently
- Engineering focus shifts to strategic capabilities rather than maintenance requests
Business Impact from Vellum
AI-driven market intelligence delivers early visibility into competitor moves, such as detecting Walmart pricing patterns weeks in advance. Insights are captured as shared organizational assets, with proprietary databases giving teams an edge competitors can’t replicate.
Organizational learning velocity exceeding individual expertise - 6 categories with sustained 2.1-2.8% margin improvements.
Competitive advantage
Market leadership through accumulated institutional intelligence
Cross portfolio intelligence network
- Month 12: Portfolio optimization using 12+ months of coordinated pricing decisions
- Electronics promotions predict accessories demand patterns with 6-week lead time
Business Impact from Vellum
Cross-category strategies improve total portfolio margin by 1.6%.
Institutional intelligence moat
- Month 15: 200,000+ pricing decisions create proprietary competitive intelligence
- Predictive competitor behavior analysis enabling proactive rather than reactive pricing
Business Impact from Vellum
Market trend identification 3 months ahead of traditional research methods
Innovation velocity as strategic asset
- Month 18: Pricing strategy deployment in 4-6 hours vs. industry average 3-5 days
- Crisis response capabilities proven through multiple market disruptions
Business Impact from Vellum
New pricing strategies build on accumulated foundation rather than starting from scratch
Market-leading pricing capabilities with $8-12M annual value through margin optimization and competitive intelligence advantages that competitors cannot replicate through technology purchase alone.
Customer stories
Success stories
5-7x
increase in business impact per engineer and PM
Resulting in 20-40% cost reduction on AI investment
“Vellum has been a force multiplier for our AI efforts; their test-driven approach helps us catch regressions early and iterate quickly. In a space where accuracy and security assurance are critical, Vellum gives us the infrastructure to move fast without compromising performance and deliver AI-powered features that our customers can trust."
Vellum AI agent template
Retail pricing optimizer agent
This workflow creates a retail pricing optimization tool that analyzes product data and market conditions to recommend optimal pricing strategies. It helps businesses set competitive prices while ensuring profitability and compliance with business rules.
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sucCCESS STORIES
Success stories
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Agentic features that power reliable retail agents
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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Secure agent platform with cross-team collaboration
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.
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