An independent publicationEvery case sourced, dated & graded A–DGet the weekly Casefile →
Grade BproductionSource date May 7, 2026· Last verified Oct 17, 2026

Can an AI agent build complex sales quotes in a life-sciences company?

BioIVT · Pharma, Biotech & Life Sciences

Header image: A gloved scientist pipetting samples into test tubes

BioIVT, which supplies biological specimens for pharma and diagnostic research, built 'Ivy', an Agentforce quoting agent that reads an opportunity, matches requests to 15,000+ product codes, builds the quote, and routes it to a service rep for review. BioIVT says quoting went from days to minutes, one rep gained 43% more time for high-value work, and Ivy has reached 94% accuracy.

Reported outcomes

quote turnaround
from days to minutes
Source [1] · self-reported
rep capacity
one service rep has 43% more time for high-value tasks
Source [2] · self-reported
agent accuracy
94% accuracy rate
Source [2] · self-reported

Outcomes are reported exactly as stated by the source; we have not independently audited them.

How it works

  1. Standard catalog quote requests are assigned to Ivy as cases; a one-minute pause allows a human to pull a case first.
  2. Ivy reads the opportunity (products, quantities, shipping) and matches against 15,000+ product codes.
  3. It creates the quote; an outbound message fetches customer-specific pricing from the ERP.
  4. A service rep reviews before sending; rep edits are captured to refine Ivy.
  5. Guardrail: Ivy cannot suggest alternative products and escalates when unsure.

Risks & compliance

  • Wrong product match can change scientific outcomes (BioIVT's stated reason for its no-substitution guardrail)
  • Human review before every send

Healthcare cases cover operational and commercial workflows. Nothing here is medical advice or a claim about a device's or drug's efficacy.

Casefile: MedTech angle

Directly transferable to device quoting (kits, implant sets, capital equipment) where catalog complexity is high.

Editor's notes

  • The 43% figure is one service rep's account, as stated in the source.
  • Went live July 2025; built with partner CREO Consulting.
Build this yourself

Tools mentioned & how to build it

Disclosure: Some links may earn us a commission; it never affects grades. Tools are listed by fit to this case, never by payment.

Tools mentioned

  • Agentforce (Salesforce)
    Salesforce's agent platform across service, sales and field service.

Build a version yourself

  • n8n
    Open-source workflow automation with AI agent nodes; self-host or cloud.
  • HubSpot (Breeze agents)
    SMB-friendly CRM with Breeze AI agents for prospecting and support.
  • Make
    Visual no-code automation with AI agents; good for intake, routing and follow-up flows.

All tools by category →

Sources

[1]Salesforce· vendor customer story· May 7, 2026
“With Agentforce, we went from days to minutes.”
How BioIVT built agentic research quoting that gives service reps 43% more time for high-impact work
[2]Salesforce· vendor customer story· May 7, 2026
“She has 43% more time for the high-value tasks that really require her expertise, which is exactly what we hoped to accomplish with Ivy.”
How BioIVT built agentic research quoting (same interview)

Grade rationale: Named organization with quantified outcomes, published on the vendor's customer-story page. Automated check on Oct 17, 2026: 2/2 quotes and 3/3 outcome claims matched the source. Compiled by the Agent Casefile research desk (AI-assisted; see methodology). Spot an error? Request a correction.

Keep reading

Related cases