AI-Powered RFQ Processing & Quotation Automation for Industrial Manufacturers
Automate RFQ processing, analyse technical documents, and generate accurate quotations in under 30 minutes with Enterprise AI.
Transforming Manual RFQ Processing into an Intuitive AI-Driven Sales Workflow for manufacturers who handle hundreds of technical RFQs (Requests For Quotation) per month, preparing accurate quotations takes hours of manual work. This delays customer responses and limits business growth, where every sales opportunity starts with a timely response.
Through this case study, discover how Iconflux assisted a leading industrial manufacturer in automating RFQ processing, analysing technical documents, and reducing quotation preparation time from 16-18 hours to under 30 minutes. But how did this happen? By implementing an AI-powered quotation workflow, the company increased its RFQ processing capacity, further improving sales productivity and scaling operations without even expanding its engineering team.
Results at a Glance
Quotation Preparation Time:
Approx. 18 hours of work done under 30 minutes (97% reduction)
Manual Document Processing
95% reduction
RFQs Processed
100% of incoming enquiries
RFQ Handling Capacity
4× increase
Quotation Turnaround
90% faster
Technical Consistency
95% improvement
Customer Experience
Faster and more accurate responses
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| What is the Business About? | Manufacturer of engineered industrial products |
| Monthly RFQ Volume | Approximately 200 to 300 inquiries |
| Target Market/Customers | EPC contractors, government organisations, infrastructure companies, PSUs, distributors, industrial enterprises |
| Previous Workflow Structure |
Manual RFQ analysis Specification mapping Pricing lookup and quotation preparation performed by experienced sales engineers |
As the table indicates, the client is one of India’s most prominent industrial manufacturers. They supply engineered products to large enterprises, EPC contractors, infrastructure projects, government organisations, and public sector undertakings.
They receive customer inquiries in a variety of document formats such as emails, PDFs, Excel sheets, technical drawings, Word documents, and engineering specifications. Initially, the sales team was entirely dependent on experienced engineers to manually review each RFQ before preparing quotations.
As inquiry volumes grew, the existing process became increasingly difficult to scale while maintaining response times and quotation accuracy.
Manual RFQ Processing Couldn't Scale
The client received 200-300 RFQs every month, that too, each with detailed technical requirements in multiple file formats and a lengthy manual process. On top of that, Sales Engineers were required to review all attached documents, understand the customer's specifications, identify the appropriate product layout, prepare technical requirement sheets, compare those to internal engineering catalogues, retrieve pricing from master databases, and finally prepare a commercial quotation. Drafting this required 16-18 hours of engineering time.
One can notice that this dependence on manual expertise might've resulted in several operational challenges, some of which are:
Long quote turnaround times
High technical workload
Limited ability to process increasing inquiry volumes
Inconsistent documentation among teams
Delays in responses resulting in the risk of losing potential business.
The business required a solution that could automate the entire RFQ workflow while maintaining engineering accuracy and fluidly integrating with existing business processes.
AI-Powered RFQ Intelligence Platform
Iconflux created and implemented a customised Enterprise AI platform that streamlined the entire RFQ lifecycle, from receiving customer inquiries to generating quotation-ready documents. So instead of replacing the client's current workflow, the solution automated every manual step taken by the engineering and sales teams.
The platform skillfully understands customers' needs, extracts technical specifications from various document formats, compares them to the company's engineering catalogue, retrieves approved pricing, and generates professional quotations for review and approval. This transformed a resource-intensive manual process into a scalable and astute workflow that produced faster and more consistent results.
The Journey of an RFQ Through Enterprise AI
Automated RFQ Monitoring
The AI tool constantly monitored the company’s mailbox and automatically detected any kind of new Request For Quotations (RFQs) and tender inquiries from all over the world.
AI-Driven Document Analysis
The AI tool analysed data from emails, PDFs, Excel documents, Word files, images and engineering files. It identified and extracted all technical aspects needed for quotation creation, further reducing the need for manual document review.
Technical Specification Development
Now, based on the extracted information, AI generated a detailed technical specification sheet in the company’s set format. This streamlined things well, saving hours of manual work effort.
Matched the Product Catalogue
The AI agent cross-referenced customer specifications with the internal product catalogue. This helped in validating configurations, dimensions, engineering parameters and product codes before proposing the best options.
Automated Pricing
The platform recovered the most recent issued prices directly from the business's pricing database after the product configuration was verified.
RFQ Generateds
Eventually, the AI system prepared a detailed quote that was ready for customer submission or review and contained technical details, product configurations, pricing, commercial information, and standard terms.
Manual Process vs AI-Powered Workflow
Before AI
Sales engineers manually track emails and download attachments
After Iconflux AI
AI takes into account the mailbox and automatically detects new RFQs and tender enquiries
Business Value
No inquiries are missed, and processing begins immediately
Before AI
Engineers manually open and review multiple attachments of various formats
After Iconflux AI
AI combines and analyses emails, PDFs, Excel sheets, Word documents, technical drawings, images, and engineering specifications in a single workflow
Business Value
Reduces repetitive document handling and speeds up processing
Before AI
Engineers spend hours reading documents to determine customer requirements
After Iconflux AI
AI retrieves technical specifications, product details, aspects, quantities, and engineering variables automatically
Business Value
Greatly reduces manual effort while increasing consistency
Before AI
Each RFQ requires manual preparation of requirement sheets
After Iconflux AI
AI generates a structured technical requirement sheet using the company's engineering format
Business Value
Saves hours of documentation work and standardises data collection
Before AI
Engineers manually compare customers' needs to internal product catalogues
After Iconflux AI
AI intelligently maps customers' requirements to the most appropriate products based on predefined engineering rules
Business Value
Product selection is faster and more accurate
Before AI
Sales team manually looks up pricing databases or spreadsheets
After Iconflux AI
AI automatically retrieves the most recent approved pricing from integrated master databases
Business Value
It eliminates manual lookups and ensures pricing consistency
Before AI
Quotations are manually generated from templates and copied data
After Iconflux AI
AI generates a complete quotation, including customer information, technical specifications, pricing, and standard commercial terms
Business Value
Reduces quote preparation time from hours to minutes
Before AI
Due to engineering bandwidth restrictions, only a subset of inquiries can be efficiently handled
After Iconflux AI
AI enables a company to process every incoming RFQ while also promoting future growth
Business Value
Large aggregate without increasing manpower
Before AI
Customers frequently wait 16-18 hours or more for quotations
After Iconflux AI
AI enables quotation generation in under 30 minutes
Business Value
Faster responses increase customer satisfaction and win rates
Before AI
Scaling requires hiring additional sales engineers and technical resources
After Iconflux AI
AI scales with increasing query volume while utilising the existing workforce
Business Value
Encourages business growth while keeping operational costs under control
Before AI
Manual processes can result in inconsistent documentation and human errors
After Iconflux AI
AI uses the same validated workflow for each RFQ, resulting in consistent outputs
Business Value
Increased quotation quality and decreased rework
What Were the Operational Improvements After AI Implementation
The AI platform resulted in several noticeable improvements within the operation cycle:
Enterprise AI Capabilities Delivered
AI Email Monitoring
Intelligent Document Processing (IDP)
Multi-format Document Understanding
Technical Specification Extraction
Engineering Rule Engine
Product Catalogue Matching
Automated Pricing Engine
AI-Based Quotation Generation
Workflow Automation
ERP & Master Data Integration
Human-in-the-Loop Validation
Sales Process Automation
Purpose-built Enterprise AI that transforms complex RFQ workflows into scalable sales operations
Iconflux developed a custom Enterprise AI solution that worked smoothly with the client's existing workflows. By combining intelligent document processing, engineering rule mapping, automated pricing, and AI-powered quotation generation, Iconflux delivered a scalable solution that reduced manual effort, accelerated response times, and enabled sustainable business growth.
Delivering measurable operational improvements through Enterprise AI
The execution drastically transformed how the organisation manages one of its most important sales processes. Instead of spending nearly a full working day preparing a single quotation, the company was able to assess detailed technological specifications, generate engineering documentation, obtain accurate pricing, and create professional quotations in less than 30 minutes.
Beyond operational efficiency, the solution increased customer responsiveness, allowed the sales team to seek more business opportunities, and laid the foundation for future AI initiatives such as tender intelligence, CRM automation, proposal optimisation, and AI-powered sales assistants. Therefore, by automating repetitive engineering tasks, the client improved both operational performance and long-term business scalability while maintaining technical accuracy.
The AI-powered RFQ automation platform made some impeccable improvements in the client's sales and engineering operations:
The client noticed a 97% reduction in quotation preparation time, from 16-18 hours to less than 30 minutes.
The transformation reduced manual document processing effort by 95%. This resulted in less repetitive engineering work.
With the help of Iconflux’s AI, businesses enabled the complete processing of incoming RFQs, ensuring that no sales opportunities were missed.
RFQ handling capacity was increased by 4 times without hiring additional engineers.
Surprisingly, the quotation turnaround time also increased by 90%, allowing the sales team to respond to customers much more quickly.
AI increased technical requirement consistency by 95%, yielding more accurate and standardised quotations.
It also increased sales team productivity by freeing up engineers so that they can focus on customer engagement and high-value technical discussions.
AI also delivered a better customer experience by providing faster, more accurate, and consistent quotations.
Ready to Automate Your RFQ & Quotation Process?
If your team spends hours reviewing RFQs, analysing technical specifications, and preparing quotations manually, it's time to simplify the process with Enterprise AI. We help manufacturers automate repetitive sales engineering workflows, improve response times, and increase operational efficiency.
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