Overview
NeenOpal’s RFQ automation solution is an AI-powered RFQ processing automation platform designed to eliminate manual quote handling and SLA delays. Built on AWS Bedrock and Amazon OpenSearch, it intelligently classifies incoming RFQs, extracts requirements, semantically matches products, and generates accurate quotes with human-in-the-loop control. By combining AI-powered RFQ automation with deterministic business rules, the platform accelerates automated quote generation while ensuring pricing accuracy, auditability, and enterprise-grade scalability.
Key Use Cases
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Automated RFQ Intake & Classification
AI classifies RFQs from emails with over 95% accuracy, instantly identifying intent, urgency, and routing requirements.
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AI-Driven Requirement Extraction
Extract specifications, quantities, and constraints from unstructured RFQ emails using AI-powered quote intelligence.
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Semantic Product Matching
Use vector search to match RFQs with the most relevant products based on meaning, not exact keywords.
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Faster Quote Generation & Approvals
Automatically generate quotes and route approvals using rule-based workflows with complete audit trails.
Transform RFQ Emails into Approved, Accurate Quotes in Minutes
Automate RFQ processing, generate accurate quotes faster, and meet SLAs using AI-powered RFQ automation.
Business Outcomes
RFQ automation transforms quote operations by replacing manual email parsing and spreadsheet-driven workflows with AI-powered RFQ processing automation. Sales and operations teams respond faster, reduce SLA breaches, and scale quote volumes without increasing headcount. Built on AWS Bedrock and OpenSearch, the AI quote intelligence platform delivers high accuracy, governance, and transparency, helping enterprises standardize quoting processes while maintaining pricing precision and human oversight.
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01.
Faster Quote Turnaround
AI-powered RFQ automation reduces quote preparation time from hours to minutes without compromising accuracy.
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02.
Improved SLA Adherence
Automated prioritization and SLA timers ensure faster responses and fewer missed commitments.
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03.
Higher Operational Throughput
Teams process three times more RFQs using automated quote generation and intelligent routing.
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04.
Governed, Auditable Workflows
Rule-based approvals and pricing logic ensure compliance, traceability, and accurate calculations with zero errors.
Frequently Asked Questions
Everything you need to know about AI-powered RFQ automation and quote intelligence.
What is RFQ automation?
RFQ automation uses AI to classify, extract, match, and generate quotes from RFQ emails automatically.
How does AI-powered RFQ automation work?
AI extracts requirements, while rules handle pricing, approvals, and SLA tracking to ensure accuracy and governance.
What role does AWS Bedrock play?
AWS Bedrock powers scalable AI models for email classification, requirement extraction, and quote intelligence.
How is pricing accuracy ensured?
All pricing calculations adhere to deterministic business rules, ensuring accurate and error-free arithmetic and governance.
Can the system handle unstructured RFQ emails?
Yes, AI accurately extracts specifications, quantities, and intent from unstructured emails.
Is there human approval in the process?
Yes, every quote follows a human-in-the-loop model where AI assists, but humans approve final quotes.
How does OpenSearch improve RFQ processing?
OpenSearch enables semantic product matching and retrieval of similar RFQs using vector similarity.
Is this RFQ automation solution enterprise-ready?
Yes, it is built with AWS-native security, observability, scalability, and full code ownership.