AI AGENTS

Vendor Scorecard Assembler from Proposals

On a schedule, the agent pulls vendor proposals for an open procurement request, scores each against weighted criteria, and posts a ranked scorecard to Slack with a recommendation.

CategoryAI Agents
EngineSim + Paperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule checks for requests ready to evaluate
  • ActionRead vendor proposals for the requestAirtableAirtable
  • ActionScore each vendor against weighted criteriaOpenAI
  • LogicRank vendors and check decision threshold
  • ActionWrite scores back for audit trailAirtableAirtable
  • OutputPost ranked scorecard and recommendationSlack

What it does

Builds a side-by-side vendor scorecard automatically. For each open procurement request, the agent gathers the submitted vendor proposals, scores every vendor against your weighted criteria (price, fit, support, security, timeline), and assembles a ranked comparison with a clear recommendation.

When to use it

When you have three or more vendor proposals to compare and want a consistent, defensible scoring instead of gut-feel spreadsheets. Ideal for recurring sourcing cycles where evaluations must be auditable.

How it works

  1. 1A daily schedule triggers the run for any request marked ready-for-evaluation.
  2. 2The agent reads vendor proposal rows from Airtable for that request.
  3. 3OpenAI scores each vendor against the weighted criteria and writes a short rationale per dimension.
  4. 4A logic step ranks vendors and checks whether the top score clears the decision threshold.
  5. 5The agent writes the computed scores back into Airtable for the audit trail.
  6. 6Output: a formatted, ranked scorecard with the recommended vendor posted to the procurement Slack channel.

Set it up

What you configure once, before turning it on.

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

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.