AI for RFP questions that need more than one contributor

Two requests under one question number

In a hypothetical RFP, or request for proposal, the customer asks, “Where are backups stored, and who approves their deletion?” At the company preparing the proposal, the infrastructure team provides the location information. Under its agreed internal responsibilities, the process owner prepares the part about deletion approval.

Assigning the entire item to “backups” can hide the need for a second contributor. A useful suggestion identifies the passage about location and the passage about approval separately, with a topic assigned to each. The coordinator can see both contributions needed before handing the work to the authors.

Both parts remain linked to the full question and its RFP reference number. The split organizes internal work; the customer's original wording stays visible. During review, the coordinator can check whether the authors have addressed the entire item. Marking the infrastructure contribution complete does not close the part assigned to the process owner.

A category needs to lead to the right person

A model can identify the topic, but assigning a team requires the company's agreed responsibilities. One organization may give an area to infrastructure, while another assigns it to a separate service or process owner. The responsibility list should come from the proposal team and the people authorized to approve that division of work.

It helps to keep topic recognition separate from current assignments. When the person responsible for a process changes, the company updates the assignment. It does not need to retrain the model to recognize questions about deletion approval. The coordinator can still correct a suggestion if a particular RFP requires a different specialist.

This solution helps distribute the work of preparing a response. Authorized people write and review commitments and security answers. A category alone does not establish where the company stores its backups or who actually approves deletion.

What to check before commissioning customization

Start with the current proposal tool. Can it assign several contributors to one item or link individual tasks to the customer's question? If the coordinator correctly identifies the topics but the system records only one author, a change to the workflow or tool configuration may solve the problem.

For recurring questions, a shared topic list with descriptions of responsibilities can also help. If separating requests within long sentences still requires repeated reading, an existing model can be compared with the current method. The model receives clear category definitions, and the coordinator checks whether the suggested split preserves every request from the customer.

Classification means assigning content to defined categories. AWS describes custom document classification through defining classes, training a classifier, and applying it to documents. That general mechanism does not establish how well a solution will handle several topics within an RFP question.

Fine-tuning is one form of model customization: it means further training a model on reviewed examples. It is worth assessing if an existing model repeatedly misses the second request or confuses two areas despite clear category definitions. The team should be able to explain the split that was needed and why. If reviewers themselves disagree about responsibilities, that division of work needs to be settled first.

Does the coordinator have fewer corrections?

The comparison should include RFPs that were not used during customization. The coordinator reviews both items needing several contributors and straightforward questions that belong to one area. They check where a contributor is still missing and where the model unnecessarily divides a single request. Excessive splitting also creates work: someone has to remove tasks that did not need a separate answer.

Compare the result with the current tool and the existing model. Customization needs to justify its place in this work: does the coordinator discover fewer missing topics during the final review, and how many suggestions still need correcting before authors are assigned?

Once the authors are known, collecting their findings and further clarifications is a separate task. Our article on an AI agent for technical tender clarifications covers that work.

Organize questions in the proposal team's tool

We propose an AI application for proposal coordinators where the full RFP question appears alongside suggested parts, topics, and contributors. The coordinator corrects the split and approves the people responsible before assigning the work. The agreed assignments can be connected to the tool the team already uses to prepare responses.

Syntalith works with your team to examine questions that return during final review because part of the request was missed. We compare the current system's capabilities with an existing model and assess customization where errors recur. Your team supplies the approved division of responsibilities and explains difficult questions.

For an initial conversation, describe a question that went to one team even though another team's input was needed. We can establish where that part was lost and how the coordinator would want to see it in their tool. We will agree together on how examples are used. See Syntalith pricing for information about the offer.