Reported impact
Business outcome
BioIVT moved standard quoting from days to minutes and gave service reps 43% more time for high-value work by automating the repeatable parts of quote assembly.
- Productivity Improvement
- Speed to Market
SalesforceHealthcareSales AutomationData PlatformERP / CRMGenerative AI / LLMProductivity ImprovementSpeed to Market2026 SalesforceSF#00a1e0HealthcareUnited StatesBioIVT had to prepare more than 25,000 complex research quotes a year while balancing quote creation with regulatory documentation, shipment tracking, and customer support.15,000 product codes in the Data 360 catalogMay 7, 20266Sales AutomationAgentforce · Data 3600 2026-05-07 6
BioIVT
Sales Automation
BioIVT had to prepare more than 25,000 complex research quotes a year while balancing quote creation with regulatory documentation, shipment tracking, and customer support.
15,000 product codes in the Data 360 catalog
25,000 quotes per year
43% more time for high-value tasks
From days to minutes
Solution
BioIVT started its agentic AI rollout in quoting, where service teams already process more than 25,000 complex requests each year for research specimens with specific disease states, donor counts, and shipping constraints. The company built Ivy on Agentforce as a task-oriented quoting agent that reads each opportunity, interprets the requested products and fulfillment requirements, and compares them against more than 15,000 product codes held in a Data 360 catalog. For standard catalog quotes, a case is assigned to Ivy, a short pause allows human intervention if needed, and then the agent selects the right items, adds them to the opportunity, creates the quote, and routes it to customer service for a final check. Because the agent works from a unified catalog and existing Salesforce opportunity context, BioIVT moved quoting from days to minutes and freed reps to spend far more time on exceptions and high-value customer work.
Data flow
Customer requirements enter the opportunity, Agentforce parses products, quantities, and shipping details, Data 360 supplies the catalog context, the quote is generated automatically, and customer service receives the finished quote for review and release.
Solution architecture
- Storage
- Data 360 Unifies enterprise and behavioral data so teams can read opportunities, assemble catalog quotes, and route them for review with current context.
- Orchestration
- Agentforce Runs the AI agent workflows that read opportunities, assemble catalog quotes, and route them for review.
Architecture clues
- Ivy pauses for about a minute before acting so staff can pull a case from the queue if needed.
- Standard catalog quotes are auto-generated and then routed to customer service for review.
- The quoting agent works against a 15,000-product Data 360 catalog.
Evidence from the source
15,000 product codes in the Data 360 catalog
25,000 quotes per year
43% more time for high-value tasks
From days to minutes
From idea to reality in four months
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value90/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth25/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity20/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact15/251 metric describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence94%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability25/2512 of 12 key fields link to a named source.
- Direct evidence20/205 direct source quotes retained.
- Date provenance10/10The publication date comes from the source page or publisher.
- Source transparency9/102 source references document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity10/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.salesforce.com/customer-stories/bioivt-larae-bennett-interview/SalesforceFirst-party
BioIVT customer story
Supports- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
- Publication date
- https://www.linkedin.com/company/bioivtLinkedInIndependent secondary
BioIVT | LinkedIn
Public company page lists headquarters Woodbury, New York; page JSON-LD reports addressCountry "US" and numberOfEmployees value 468.
Supports- Region
- Company size
Date evidence
- Published on source page May 7, 2026 · Salesforce · First-partyOpen date source
Not separately sourced Industry. Treat these normalized attributes as lower-confidence until a dedicated source is added.
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