AI AGENTS
Draft RFP clarification questions from ambiguous requirements
Scans an RFP for vague, conflicting, or underspecified requirements, drafts precise clarification questions for the issuing agency.
How it runs
The automated pipeline, trigger to output.
- TriggerNew RFP file added to Dropbox folderDropbox
- ActionFlag ambiguous and conflicting requirements with OpenAIOpenAI
- LogicKeep only items above the ambiguity bar
- ActionDraft a clarification question per item with OpenAIOpenAI
- ActionPackage questions into an Outlook Q&A emailOutlook
- OutputConfirm draft ready in SlackSlack
What it does
Every RFP has requirements that are ambiguous, internally contradictory, or missing a measurable bar. This workflow finds them, drafts a sharp clarification question for each, and assembles a ready-to-send Q&A email. It distinguishes genuine ambiguities worth asking about from minor wording so you submit a focused question list, not noise, before the agency's Q&A cutoff.
When to use it
Use this in the days after an RFP drops, while the official question window is open. It ensures you surface every clarification that could change your bid strategy or pricing rather than discovering the ambiguity mid-draft.
How it works
- 1A new RFP file in the watched Dropbox folder triggers the run.
- 2OpenAI extracts requirements and flags those that are ambiguous, conflicting, or unmeasurable.
- 3A logic step keeps only items meeting the ambiguity bar.
- 4OpenAI drafts a precise clarification question for each kept item.
- 5The questions are packaged into a formatted Outlook email addressed to the contracting officer.
- 6A Slack note confirms the draft is ready for review before sending.
Set it up
What you configure once, before turning it on.
- 1Connect DropboxFiles and folders.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect OutlookMail, calendar, contacts.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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