ProcAI Product
AI-Powered RFQ Intake Automation
Transform how your team processes incoming RFQs. From email to structured CRM record — fully automated.
Book a DemoHow It Works
Read Emails & RFQs
Monitors your inbox in real time for incoming requests
Detects Spam & Viruses
Filters malicious and irrelevant messages automatically
Classifies Customer, Brand, Products
AI extracts and matches data against your database
Synchronizes with CRM/ERP
Pushes structured data into your systems instantly
Email-Based RFQs
The bot reads emails from multiple mailboxes and extracts RFQ data from text, attachments, and images.
Online Forms
Capture RFQs from your website contact forms and process them through the same automated pipeline.
Who It's For
Built for B2B companies that receive high volumes of product inquiries via email
Best fit if you:
- Sell industrial or technical equipment online
- Receive 100+ RFQs per day
- Manage a catalog with 10,000+ SKUs
The Problem
Manual RFQ processing slows teams down, erodes margins, and creates costly errors at every step.
Current Reality
The Manual Workflow Your Team Repeats Daily
RFQ Intake Platform
From incoming email to structured record – fully automated.
From Email to CRM — Fully Automated
Read Email
Monitors inbox in real time
Identify Intention
RFQ, spam, follow-up, PO, or other
Classify & Extract
Customer, brand, and product
Sync with CRM/ERP
Structured data pushed automatically
Every Email Type — Handled
The bot understands text, attachments, images, and follow-ups
Spam Email
The bot automatically detects and filters bulk promotional or irrelevant emails — before they reach your team.
Text RFQ Email
Items, brands, and quantities are extracted directly from the email body text with AI-powered parsing.
Email with Attachments
PDF, Doc, and Excel attachments are parsed automatically — extracting structured product data from tables and lists.
Image Attachment
OCR technology reads nameplate photos, product labels, and scanned documents attached to emails.
Follow-ups & Doubles
Follow-up emails and duplicate requests are detected and linked to the original RFQ — preventing double processing.
Under the Hood
Email Intention Detection
The bot automatically classifies every incoming email – determining whether it's a legitimate RFQ, marketing spam, or a message containing malicious content.
RFQ
A genuine quote request from a customer
Spam
Bulk promotional or irrelevant emails
Virus / Malicious
Emails containing harmful attachments or links
Customer Data Extraction & CRM Matching
The bot automatically extracts customer details from every incoming email and matches them against your CRM database.
Extract Customer Data
Name, company, email address, and phone number
Match Against CRM
Finds the existing customer record or creates a new one
Sync in Real Time
All matched data is pushed to CRM automatically
Brand & Product Matching
AI-powered matching against your product catalog with human-in-the-loop fallback.
Extract
Pulls brand names, part numbers, and product details from the email
Match Against Database
Finds the best candidate in the product catalog
Human in the Loop
If no confident match, the bot flags the item for a manager
CRM & ERP Synchronization
Once the RFQ is processed, the bot syncs all extracted data directly into your CRM or ERP system.
Auto-Sync Results
Pushes structured RFQ data in real time
No Manual Entry
Eliminates copy-paste errors and saves hours
Works with Major Platforms
Salesforce, SAP, Dynamics, NetSuite, and more
Key Metrics
99%
Spam detection accuracy
+5–10%
More RFQs captured
60–70%
Emails filtered automatically
~30 min
Manual data entry daily time
Handling Cost
$15–25 per day for 1,000 emails
What affects cost:
- Email length and complexity
- Number and size of attachments
- Number of products per RFQ
The Logic Under the Hood
The system uses a combination of large language models with carefully engineered prompts for each task.
Prompts
Carefully crafted prompt chains for each processing step
GPT (OpenAI)
Used for natural language understanding and extraction
Claude (Anthropic)
Used for complex reasoning and document parsing
Integration Process
Discovery (2–3 days)
Schedule a call, clarify requirements, and collect use cases.
First Version (1–2 weeks)
Present the first version and adapt to your business processes.
Integration
Connect the solution into your existing systems and workflows.
Maintenance
Add support for new use cases and continuously improve.
Book a Discovery Call
A short conversation to identify how AI can automate your RFQ processing.