AI AGENTS

Assign RFP gap items to owners as Linear tasks

Takes the requirements an RFP gap analysis flagged as Partial or Gap, maps each to the right internal owner by domain, and opens a Linear issue per gap with the requirement text.

CategoryAI Agents
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerGap matrix marked Reviewed in NotionNotionNotion
  • LogicFilter rows to Partial and Gap items
  • ActionClassify each gap by domain with OpenAIOpenAI
  • ActionCreate a Linear issue per gap with owner and due dateLinearLinear
  • OutputPost created-issue digest to SlackSlack

What it does

Once an RFP's requirements are scored, the Partial and Gap items are the real work. This workflow reads the gap matrix, filters to only the items that are not fully met, classifies each by domain (security, integration, compliance, delivery) with an LLM, and creates a Linear issue assigned to that domain's owner. Each issue carries the verbatim requirement, the response due date, and a link back to the source section.

When to use it

Run this right after a gap analysis so every unmet requirement becomes a tracked, owned task instead of a row in a spreadsheet nobody actions. Proposal managers use it to spin up the response work plan in seconds.

How it works

  1. 1A completed gap matrix in Notion (status set to Reviewed) triggers the run.
  2. 2Rows are filtered to Partial and Gap items only.
  3. 3OpenAI classifies each item by domain and maps it to the owner table.
  4. 4A Linear issue is created per item with requirement text, owner, due date, and source link.
  5. 5A digest of created issues posts to Slack for the proposal manager.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect NotionPages, databases, comments.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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