A leading speciality chemical exporter serving international markets faced increasing operational complexity due to a rapidly expanding product catalogue.
The company manages more than 5,000 SKUs, including multiple manufacturer makes and product variants used across different industries.
To manage business operations, the organization relies on SAP Business One for ERP processes and Google Workspace (Gmail) for business communication.
Every day, the company receives a high volume of export enquiries via email, where international buyers request information about:
Due to the complexity of chemical product naming and pricing structures, responding to these enquiries required significant manual effort from the sales team.
One of the biggest operational challenges was identifying the correct product from the catalogue.
Customers often referred to the same chemical using different identifiers, such as:
Sales teams had to manually interpret each enquiry, search the product catalogue, and identify the correct SKU.
With over 5,000 speciality chemical products, this frequently caused delays and inconsistencies.
Pricing calculations were not straightforward.
Final pricing depended on multiple layers, including:
Sales representatives had to manually compute the final price for each enquiry, increasing both response time and the risk of pricing errors.
For many customers, pricing decisions relied heavily on historical data.
Sales teams often needed to manually search past records to determine:
This required navigating across multiple systems and databases, making the process slow and inefficient.
Processing a single enquiry involved several manual steps:
For enquiries containing multiple products, the process could take several hours.
In global export markets where response speed directly impacts deal conversion, this created a serious operational bottleneck.
To address these challenges, an Agentic AI-powered enquiry processing system was implemented.
The solution integrates directly with:
Unlike traditional automation tools that rely on rigid workflows, Agentic AI systems can interpret context, make decisions, and execute tasks autonomously. The AI solution was designed to:
The system continuously scans incoming emails in Gmail.
Using AI-based language understanding, it identifies whether a message contains a product enquiry or general communication.
Once an enquiry is detected, the system identifies the sender using the customer database.
If the sender is an existing customer, the system retrieves:
The AI analyzes the enquiry and maps the request to the correct product SKU using multiple references, including:
This enables the system to accurately identify products even when customers use different naming conventions.
After identifying the requested SKU, the system checks real-time inventory availability from SAP Business One.
If the requested manufacturer make is unavailable, the system automatically suggests alternative approved makes available in stock.
The AI applies structured pricing logic depending on the type of enquiry.
Existing Customer with Defined Pricing
The system retrieves predefined pricing rules and discount structures.
Existing Customer Without Defined Pricing
The system searches historical enquiry records to determine the last quoted price.
For new customers, the system applies standard discount rules defined for the product category or manufacturer make.
The AI extracts the requested quantity directly from the enquiry email and calculates the final price automatically.
Pricing is calculated by:
This eliminates manual pricing calculations.
Export enquiries often include multiple product line items.
The system dynamically selects the most suitable response format.
Small Enquiries
For enquiries with fewer items, the response is included directly in the email body using a structured table format.
Large Enquiries
If the enquiry contains many products, the system automatically generates an Excel quotation sheet and attaches it to the response email.
The sheet includes:
Some customers send enquiries as PDF documents.
The AI system processes the document and generates the quotation response in PDF format, ensuring consistency with the original request.
Once all data is processed, the system prepares a ready-to-send response draft containing:
The sales team simply reviews and sends the response, reducing manual effort.
The implementation of AI-powered enquiry automation delivered measurable business impact.
Enquiry response time reduced from several hours to just minutes.
Automated calculations eliminated manual pricing errors.
Sales teams no longer spend hours searching product databases or calculating complex pricing structures.
Faster responses increased the probability of securing export orders.
The system now handles enquiries across 5,000+ speciality chemical SKUs efficiently and accurately.
For speciality chemical exporters managing large product catalogues, complex pricing structures, and high volumes of email enquiries, manual processing can become a major operational bottleneck.
By combining Agentic AI automation with ERP integration, companies can transform enquiry handling into a fast, intelligent, and scalable workflow.
The result is simple but powerful:
A sales team that once spent hours responding to export enquiries can now reply in minutes with accurate pricing, real-time availability, and significantly higher efficiency.
