EngineeringNewVerified Real deployment at a named or precisely described company, with a measured result from a primary source.

AI reads customer tenders and specification packages clause by clause and builds the deviation list (ROBEL, Bosch Manufacturing Solutions)

Added 2026-10-19 · Last updated 2026-10-19

Role

Engineering (application and sales engineering: requirements review at RFQ) · Typical users: application engineer, sales engineer, bid or proposal manager, project engineer, engineering department leads

The problem

Machine builders and engineer-to-order manufacturers receive tenders and RFQ specification packages that run to hundreds of documents and thousands of pages: technical requirements, safety certifications, referenced standards, environmental criteria, compatibility with the customer's equipment. Engineers list the documents in Excel, split them between departments, collect deviations and open points in a central list, and consolidate it before quoting, often within a few weeks. It costs hundreds of hours per project, not every page gets read in depth, the same questions get answered again and again, foreign-language tenders must be translated first, and a missed requirement surfaces after the order is won.

How AI helps

The team uploads the whole tender or specification package. The AI extracts each requirement, pre-evaluates it against internal engineering standards and the answers given on past projects, highlights what differs from previous projects with the same customer, flags deviations, risks and open questions clause by clause, and assigns each requirement to the right department. Referenced norms are matched against the actual requirements. Engineers review only their part, in parallel, and decide; the AI then drafts sub-supplier RFQs and first drafts of proposal documents such as technical summaries and test plans.

Step by step

1. Measure the baseline on two or three recent tenders: hours spent on the requirements review, number of departments involved, and requirements missed (found after the order or during the project).
2. Gather what the AI must compare against: your standard product specifications, internal engineering standards, and past deviation lists and answers for repeat customers.
3. Pilot on one live tender alongside the usual process: the AI extracts requirements, proposes compliant / deviation / question for each, and assigns an owner department.
4. Each department reviews only its requirements and confirms or corrects every status; the bid manager signs off the consolidated deviation list before anything goes to the customer.
5. Compare with the manual review: requirements the AI missed, false flags, and hours saved; feed confirmed answers back as the reference for the next tender.
6. Extend to sub-supplier RFQs and first drafts of proposal documents once the requirement extraction is trusted.

Tools

• Atira (sales engineering agents for tenders): used at ROBEL
• BoWatt (AI requirements management for RFQ specifications): used at Bosch Manufacturing Solutions
• Other tools to evaluate: requirements and proposal tools that shred RFPs into compliance matrices, or a document-reading assistant in your existing PLM or requirements tool
• Any LLM (ChatGPT, Claude, Copilot, Gemini) with the prompt below, on one specification document and your standard offer, for a first test

As reported by the source; most figures are vendor or self-reported and not independently verified.

Human review: cautions

• Every status (compliant, deviation, question) is confirmed by the responsible engineer before the offer goes out; a missed requirement becomes a contractual commitment.
• Referenced standards are often not in the tender: the AI must check them against the actual text of the standard version you hold, not from memory.
• Tender documents and customer specifications are often confidential: use an approved enterprise tool and check the customer's confidentiality terms.
• The figures are vendor-published, for two German machine builders.

You are an experienced application engineer reviewing a customer specification before we quote.

I will paste: (1) the customer's specification or tender section [text]; (2) our standard product specification and options [text or table]; (3) our internal standards or past deviations for this customer, if any [text].

Do this:
1. Extract every requirement as a numbered list, quoting the clause number and the exact wording.
2. For each requirement, mark Compliant / Deviation / Question / Not applicable against our standard specification, with the reason and the line of our specification you relied on.
3. List every standard or norm the specification references, and what we would need to check for each.
4. Assign each requirement to a department (mechanical, electrical, controls, safety, quality, documentation, commercial).
5. Draft the deviation list and the questions to the customer in a table, ready for each department to confirm.

If our specification does not cover a requirement, mark it Question, not Compliant. Do not invent standards or product capabilities.
Use only the data I paste in; if something is missing, write 'not found' or list it as a question instead of guessing. Do not send, order, post or change anything in any system: produce drafts for my review and approval.

Related cases

• AI quoting from drawings and RFQ emails
• Automatic feasibility check of customer drawings at RFQ intake
• AI supplier contract review and renewal tracking
• AI proposes material formulations so R&D runs fewer lab experiments (Resonac, formerly Showa Denko)

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Sources

• https://atira.ai/customers/robel
• https://www.bowatt.com/resources/customer-success-story-bosch-manufacturing