Distributed Micro Technology Ltd (DMTL) distributes capacitors and a wider range of electronic components. Preparing accurate and competitive quotations is central to its sales process. Its sales advisers must respond quickly to customer enquiries, offer a price with a strong probability of winning the order and maintain an appropriate margin. DMTL identified an opportunity to use AI to bring its commercial data together and give advisers better information when deciding what price to offer.

DMTL’s advisers prepared quotations manually, moving through multiple areas of its systems to find and assess the information they needed. This involved reviewing previous quotations and orders, customer purchasing history, current and historic costs, exchange rates, minimum order quantities and pricing achieved for similar products and customers. Gathering and interpreting this fragmented data took time. It also made it difficult to consider every relevant factor consistently while providing customers with a prompt response.

One Beyond developed an AI-assisted pricing agent using Anthropic’s AI technology, enabling DMTL’s advisers to prepare quotations up to three times faster. Integrated directly into DMTL’s sales system, it analyses the company’s commercial data and recommends a price that balances the probability of winning the order with an appropriate margin. Recommendations consider previous offers and orders for the specific part, the customer’s purchasing and pricing history, changes in purchase cost and exchange rates, minimum order quantities and quantity breaks, successful pricing for similar products and customers, and relevant account, project and design-registration activity. Advisers receive a suggested price and margin range with a concise explanation. The agent can also suggest relevant products, manufacturers or buying opportunities to support the wider sales conversation, while the adviser retains control of the final quotation.

By bringing relevant commercial information together at the point of quotation, the solution enables DMTL to reduce the time advisers spend gathering and assessing information, respond to customer enquiries more quickly and make more informed, consistent pricing decisions. Clear evidence behind each recommendation helps advisers balance competitive pricing with appropriate margins and improve the likelihood of converting quotations into orders. Advisers can also provide feedback on the AI’s recommendations, helping DMTL assess their usefulness, understand how they are being used and continually refine the solution. By tracking quote-conversion rates and achieved sales margins alongside adviser feedback and time savings, DMTL can assess the integration’s wider commercial impact and return on investment.