LEAD GENERATION

Trending HuggingFace model authors to Attio leads

Watches the HuggingFace trending models feed daily, resolves each model's authors and their affiliations via Brave web search.

CategoryLead Generation
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule fires
  • ActionFetch HuggingFace trending models + authorsHugging FaceHugging Face
  • ActionBrave search to enrich author title + employerBraveBrave Search
  • LogicSkip authors already fresh in Attio
  • OutputUpsert enriched leads into AttioAttio

What it does

Every morning this workflow pulls the models climbing the HuggingFace trending charts, identifies the people and orgs behind them, enriches each with a current title and affiliation from Brave, and lands them in Attio as recruiting or BD leads tied to the model that surfaced them.

When to use it

Run this when you recruit ML engineers or sell developer tooling and want a steady stream of builders who are publicly shipping models right now — the strongest possible competence signal — instead of scraping stale conference lists.

How it works

  1. 1A daily schedule fires the run.
  2. 2Query the HuggingFace API for the current trending models and their author handles and org cards.
  3. 3For each unique author, run a Brave web search on their name plus org to recover a personal site, LinkedIn-style title, and current employer.
  4. 4A filter drops authors who already exist in Attio with a fresher touch date, keeping payloads clean.
  5. 5Upsert the survivors into Attio as person records, stamping the trending model name, rank, and HuggingFace URL as the lead source.
  6. 6The final output is a deduped batch of enriched leads in your Attio pipeline.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Hugging FaceModels, datasets, spaces — the open-source hub.
  2. 2
    Connect Brave SearchWeb, news, image, video search.
  3. 3
    Connect AttioReal-time CRM with structured data + powerful views.
  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.

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