AI for custom parts quote preparation

At Syntalith, we propose an AI agent that connects the CRM inquiry with agreed documents and manufacturing engineering replies. Sales sees what the estimate should cover, what the customer has already supplied, and which question remains open. The estimator receives a reviewed brief with the supporting material. Specialists retain feasibility assessment, process selection, and pricing; the proposed tool prepares their work.

Annual demand and the initial production run

Suppose a customer sends a drawing and states annual demand for a thousand parts. Another email says they want a trial run first, without specifying its quantity. The manufacturing engineer asks whether the current estimate concerns the trial or subsequent production. The annual figure does not answer that question.

The agent brings both messages together with the engineer’s note. It proposes a question for sales about the initial quantity and the scope of the quote currently requested. Sales reviews it before sending. When the customer replies, the estimator sees the explanation beside the inquiry, without treating annual demand as a single order quantity.

If a drawing requirement also needs discussion, the specialist identifies the question. The agent can attach that note to the conversation and draft the message. It does not supply tolerances or decide whether the company can manufacture the part. Customer explanations return to the person responsible for assessing their effect on the estimate.

Give the estimator material they can use

Quote preparation can involve several conversations, but an estimator does not necessarily need every thread in full. A useful brief identifies the current estimating scope, relevant explanations, and links to the documents. The specialist can return to the customer’s exact statement when something is unclear. An employee should be able to correct the summary before handing it over.

This differs from assembling a tender clarification for a buyer. Here, sales prepares an internal estimating request before a quote exists. The related work of coordinating several specialists’ answers appears in our article about technical tender clarifications.

Check your existing quote workflow

Microsoft Dynamics 365 Sales supports draft quotes and revisions; activating a quote makes it read-only, while revising it creates another draft. That workflow helps manage the quote itself. If the company also has a structured inquiry form that people consistently complete, a separate agent may be unnecessary.

A connection becomes relevant when estimating inputs still emerge in correspondence and sales repeatedly transfers them between email and the engineering task. Compare the proposed brief with what the estimator actually needs to read. A longer summary alone may not help them begin.

Syntalith proposes starting with one type of inquiry. Your team identifies the material and the specialists who evaluate technical questions. A completed case lets you inspect the proposed view and customer follow-up draft before agreeing to broader connections. Describe the last question that caused an estimator to send an inquiry back to sales. That is enough to start a discussion about an AI agent; collaboration details are on the pricing page.