An AI-assisted system could prepare B2B requests for review while preserving sources, missing information and decisions owned by the team.
A company submits a request to equip a workspace. It attaches a document, mentions a deadline and asks for an estimate. Required details are split between the message and attachment. One colleague copies them into a spreadsheet, another notices a missing dimension, and the customer receives questions across several emails.
Required details sit in the message and the attachment, and questions reach the customer across several emails.
WHAT WE WOULD TESTA brief that separates the customer’s statements from interpretation, with a source for every quantity, dimension and date.
The message asks for two areas; the document describes three.
WHAT WE WOULD TESTConflicts between the message and attachment remain visible until resolved. The system does not pick the version that makes the brief look complete.
Some fields do not change the current evaluation.
WHAT WE WOULD TESTEach proposed question has a reason. A field that does not change the evaluation does not delay the response.
Real requests, preparation and correction time, recurring questions and differences between services.
Repeated data, conflicting sources and how responsibility is assigned.
The person requesting a quote may need approval from others. A useful brief preserves requirements and helps explain the eventual proposal to those decision-makers.
What is missing stays visible.
CREATIVE PROPOSAL / ILLUSTRATIVE EXAMPLEWe would start with an internal preparation and review system. AI would extract information, identify questions and propose a summary. A person would validate the brief and the outgoing message. This stage can be useful without a public chatbot: the customer-facing entry point can remain the existing form or email, with the improvement taking place in how the team prepares its response.
Dimensions are attached and installation is requested. The demonstration attachment describes three areas, one with no width.
The message says two; the document says three. Installation requested, location missing, and the relative deadline needs confirmation as an exact date. Feasibility and price have not been assessed.
One message asks for the areas, the installation location, the intended completion date and the third area’s width, if it is part of the project. It is sent only after approval.
Fields, sources and rules, the intake connection, assisted extraction and the review checklist.
The review interface and CRM handover, with documentation for operation, manual recovery and changes to the form or service offering.
Incoming documents are treated as information to examine. Instructions inside a document cannot grant additional access or authorize a quote to be sent.
Every stage has a usable output and an owner.
| Stage | Useful output | Responsibility |
|---|---|---|
| Receipt | An identified request with its sources retained | The integration verifies recording and duplicates |
| Preparation | Extracted facts linked to a message or document | AI proposes; unverified fields remain marked |
| Clarification | A concise list of missing or conflicting information | An owner checks whether the questions matter |
| Validation | A brief accepted for commercial and technical review | The team confirms the data and next step |
| Quoting | A proposal with deliverables, terms and dependencies | Authorized people approve the quote |
| Follow-through | Actual status, questions and a documented decision | The sales team updates the opportunity |
Conceptual scenario. Fictional data.
A verifiable brief for commercial and technical assessment.
Demonstration. Fictional data. Simulated actions. Scripted responses, with no connected AI, personal data, or real operations.
MESSAGE / PARAGRAPH 1
We need equipment for two areas by the end of next month. Please provide a quote including installation.
DOCUMENT / ROWS 1, 2, 3
Fictional sources. No documents are uploaded or sent.
Sources and question
Choose a situation and follow what the system can verify, what stays unknown, and when a person needs to step in.
Choosing another situation restarts the demonstration.
Test cases would include a complete request, missing information, a contradiction, an unreadable file and a repeated submission. Each would have an expected outcome and a named next owner before testing begins.
If requests are already standardized, an improved form and ordinary rules may remove most copying. If each project requires expertise that is difficult to verify, AI could be limited to organizing documents and questions.
Establish what an indicative estimate needs and what is confirmed after technical review.
Assisted extraction, a review checklist, human approval and CRM handover.
The direction should reduce total effort while preserving the quality of information used to build the quote.
An illustrative sequence; timing and investment follow the real context.