Stellar Group receives customer enquiries that can include multiple products, specifications, finishes, and quantities. Preparing a quotation or proforma invoice meant interpreting those requirements, matching each item to the product master, and checking the price that applied to the customer.
CRMFolks implemented an AI-assisted solution using Claude AI, Zoho CRM, Zoho Creator, and Zoho Catalyst. Sales staff can now start a quotation or proforma invoice from a single natural-language prompt, and incoming order emails can automatically create Deals and Quotations in Zoho CRM. The sales team can review uncertain product matches and verify prepared proforma invoice details before generating the document.
A customer enquiry at Stellar Group could include several products, each with its own code or reference, specification, finish, and quantity. Some customers used product codes, while others described what they needed in their own words. Before preparing a quotation or proforma invoice (PI), the sales team had to interpret each line, identify the corresponding product in the product master, and check the applicable customer price list.
Product identification and pricing were closely linked. A product could be correctly identified and still carry the wrong price if the team used a different customer’s price list. An unclear finish or product reference could also affect which item was selected before pricing even began. The team then had to organize the verified customer, product, quantity, and pricing information into a format suitable for document preparation.
Orders arriving by email added another manual step. The sales team had to read the order, identify the customer and products, and create the corresponding Deal and Quotation in Zoho CRM. Stellar Group wanted to automate that work while retaining a way to review uncertain product matches and validate PI details before generation.
CRMFolks integrated Claude AI with the Zoho environment to turn natural-language enquiries and order emails into structured information the sales team could use. The workflow connects the extracted requirements to the product master and customer price lists, then uses the resulting information to prepare a sales document or create CRM records, depending on how the request entered the system.
| Role in the implementation | |
|---|---|
| Claude AI | Interprets natural-language instructions and customer order emails. Extracts customer references, product codes, descriptions, specifications, finishes, and quantities for downstream processing. |
| Product master and customer price lists | Provide the product information used for matching and the applicable price for the identified customer and product. |
| Zoho CRM | Centralizes customers, leads, enquiries, notes, and follow-up activities. Receives Deals and Quotations created through the email workflow. |
| Zoho Creator and Zoho Catalyst | Support the custom application components, backend business logic, data processing, and integrations connecting Claude AI and the Zoho applications. |
| Challenge | How CRMFolks addressed it |
|---|---|
| Customers described products in different ways. An enquiry might contain an exact product code, a customer reference, or a description with a particular finish. | Claude AI extracts the available details from each product line. Matching uses multiple attributes from the product master, and uncertain matches can be flagged for review. |
| The correct price depended on both the customer and the product. Manual preparation required the sales team to identify the item and check the relevant customer price list. | CRMFolks incorporated customer-specific price retrieval after customer and product identification. The applicable price is assembled with the corresponding product and quantity for document preparation. |
| Extracted enquiry details had to be usable for a sales document. A free-text interpretation alone would still leave the team to organize the customer and line-item information. | The workflow assembles customer details, products, quantities, and prices into a structured format. The sales team can validate the prepared PI information before generating the document. |
| The two entry points required different outputs. A sales prompt can request a quotation or PI, while an incoming order email needs a Deal and Quotation in Zoho CRM. | CRMFolks implemented two workflows that use AI interpretation and product identification, then route the information to the appropriate document or CRM record creation step. |
| The AI output had to connect with Zoho records and business logic. Interpreting the enquiry was only one step in a workflow that also needed matching, pricing, and record creation. | Zoho Creator and Zoho Catalyst support the custom processing and integrations that connect the extracted information to the downstream Zoho workflows. |
| Before implementation | What the deployed solution enables |
|---|---|
| Sales staff manually interpreted and organized customer enquiries. | Claude AI structures the enquiry into customer and product details for further processing. |
| Staff had to identify products from varying codes, references, and descriptions. | The workflow assists with product identification using the product master and can flag uncertain matches for review. |
| Staff checked customer price lists while assembling sales documents. | Applicable pricing is retrieved as part of the workflow and included with the prepared line items. |
| Quotation and PI preparation required the team to assemble information across several steps. | Sales users can start either document from a single prompt and review the prepared PI details before generation. |
| Customer order emails had to be translated into Deals and Quotations manually. | The email workflow interprets order details and automates creation of the corresponding Deal and Quotation in Zoho CRM. |
After deployment, Stellar Group reviewed the solution against its business requirements and provided positive feedback that it was working correctly and supporting the intended workflow. The project record specifically documents client validation of enquiry interpretation, product identification, customer-specific price retrieval, and structured PI preparation.
The documented outcomes are qualitative. The source case study records the deployed capabilities and client feedback. It provides no measured turnaround times, product-match accuracy rates, or hours saved.
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