5 minutes read
Reclaiming Margins with AI: A Smarter Approach to Pharma & MedTech RFQs
In today’s high-stakes health-sector procurement landscape, speed and precision are no longer optional—they are commercial imperatives. Yet a persistent drain on time, resources, and revenue often goes unnoticed: the relentless influx of unstructured Request for Quotations (RFQs) inundating commercial teams daily.
Mid-tier and low-value RFQs—often received via email, PDF, or fragmented digital portals—drain bandwidth and deliver limited returns. The issue extends beyond volume; the real challenge lies in identifying relevance, improving responsiveness, and optimising resource allocation. Many organisations remain tethered to outdated workflows: manual copy-pasting, laborious SKU matching, and drawn-out communication loops—all contributing to missed deadlines and eroded margins.
This operational drag continues to slow execution and dilute strategic focus. But AI is now transforming this process—decisively.
Unmasking the Strategic Blind Spot
Pharma, MedTech, and Biotech companies have invested heavily in platforms optimised for large-scale tenders. Yet these systems often fall short when handling the high-frequency RFQs issued by decentralised hospitals, regional buying groups, and local health systems. As a result, commercial teams are forced to spend disproportionate time on basic intake and filtering—diverting attention from response quality and margin optimisation.
This is the critical blind spot. The cumulative impact of numerous smaller, overlooked RFQs can equal—or even exceed—the commercial value of a major tender.
Without automation, teams are compelled to prioritise selectively, often leaving potential revenue and market responsiveness untapped.
AI-Powered Transformation: Beyond Simple Automation
The next evolution in procurement transcends digitisation. It is intelligent automation. Healthcare-trained AI now delivers powerful capabilities to:
- Extract and structure RFQ content from diverse formats with high precision
- Filter out irrelevant requests, spotlighting commercially viable opportunities
- Match items to internal SKUs using advanced, ontology-driven logic
This is the core of Vamstar’s RFQ Fasttrack Engine—a modular, out-of-the-box solution for healthcare supply chains, requiring no complex integration.
What this looks like in action:
- AI-powered Triage: Automated parsing of RFQs from diverse sources (emails, PDFs, documents), extracting critical fields, such as deadlines, lots, SKUs, and quantities with >90% accuracy.
- Strategic Filtering: Sector-specific large language models (LLMs) assess RFQs for commercial relevance, ensuring teams focus only on high-value prospects.
- Instant SKU Mapping: Seamless mapping of requested items to internal product families and catalogues—eliminating time-consuming manual reconciliation.
- Margin Visibility: Built-in calculators use pricing history and win-loss data to validate profitability before bids are submitted.
- Scalable Workflows: A flexible framework that allows organisations to begin with triage and expand to catalogue mapping, margin analysis, or full response workflows—fully compatible with CRM systems like Salesforce.
Turning Cost Centres into Profit Catalysts
Early adopters are already seeing a 2–3x increase in mid-tier RFQ response rates and significant reductions in manual triage time. More importantly, AI is reshaping how RFQs are perceived—from operational clutter to a stream of qualified commercial opportunities.
Intelligent automation enables lean tendering teams to scale output, enhance bid quality, and improve commercial precision—without additional headcount.
Modular AI That Fits Your Pace
One of the most significant advantages of modular AI deployment is flexibility. You don’t need to rip and replace your current systems. With Vamstar, teams can start with AI-powered triage and expand into catalogue mapping, margin validation, and full workflow automation based on their needs and maturity.
This isn’t about short-term efficiency gains. It’s about a long-term shift to data-driven, scalable commercial excellence.
Looking Ahead: Agentic Commercial Operations
The next frontier is agentic workflows—where AI not only supports decision-making but autonomously executes actions within defined parameters. In RFQ management, this means AI that:
- Recommends pursuit strategies
- Suggests pricing based on historical success
- Compiles and submits quotes—fully auditable and compliant
This capability is no longer conceptual—it is fast becoming reality. And organisations that move early will be best positioned to lead this transition, both strategically and operationally.
