LEAD GENERATION

Issue Authors With Buying Pain to Research Packet

Triggers on new GitHub issues, uses an LLM to classify whether the author is describing a paid-tier or enterprise pain point, enriches qualified authors.

CategoryLead Generation
Enginesim
Difficultyintermediate
Triggerevent
Steps7
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew issue opened on repoGitHubGitHub
  • ActionFetch issue body and author profileGitHubGitHub
  • ActionClassify commercial intent with LLMOpenAI
  • LogicBranch on paid-tier/enterprise pain
  • ActionEnrich author and employer via ExaExa
  • ActionCreate tagged lead in AttioAttio
  • OutputSend packet to Slack with angleSlack

What it does

When someone opens an issue on your repo, it reads the issue body, decides whether the author is hitting a limit that your paid product solves (scale, SSO, support, compliance), and only then enriches and routes them as a warm lead.

When to use it

Use this when your issue tracker doubles as a demand signal — power users filing detailed issues are often the ones ready to pay. It filters bug reports and typo fixes from genuine commercial intent so sales only sees the real signals.

How it works

  1. 1A new issue opened on the repo fires the trigger.
  2. 2Fetch the issue body, labels, and the author's profile.
  3. 3An OpenAI classification step rates commercial intent and tags the pain category.
  4. 4Branch: only issues flagged as paid-tier or enterprise pain continue.
  5. 5Enrich the author and their employer with Exa.
  6. 6Create the lead in Attio tagged with the pain category.
  7. 7Send the packet to Slack with the issue link and a tailored angle.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect ExaNeural search across the web.
  4. 4
    Connect AttioReal-time CRM with structured data + powerful views.
  5. 5
    Connect SlackChannels, DMs, threads, mentions.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    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.