MARKET RESEARCH

On-demand deep dive that researches a HuggingFace model and publishes a Confluence eval page

Triggered manually with a model ID, an agent pulls the model card and stats from HuggingFace, gathers external context with web search.

CategoryMarket Research
Enginepaperclip
Difficultyadvanced
Triggermanual
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerManual trigger with a model ID
  • ActionFetch model card, stats, and license from HuggingFaceHugging FaceHugging Face
  • ActionSearch the web for third-party benchmarks and issuesPerplexityPerplexity
  • LogicSynthesize capabilities, risks, and a go/no-go recommendation
  • OutputPublish the evaluation page to ConfluenceConfluenceConfluence

What it does

Gives the ML team a one-click deep dive on any specific model. You hand it a HuggingFace model ID; an agent reads the model card, license, benchmarks, and download history, searches the web for independent benchmarks and discussion, then writes a structured evaluation page to Confluence covering capabilities, license fit, hardware needs, risks, and a go/no-go recommendation.

When to use it

Use it when a model crosses your radar and someone needs a thorough, sourced write-up before the team commits eval time, rather than a quick alert. It replaces the manual hour of tab-juggling and note-taking with a finished, shareable page.

How it works

  1. 1A team member triggers the run manually with a model ID.
  2. 2The agent fetches the model card, stats, and license from HuggingFace.
  3. 3It runs Perplexity searches for third-party benchmarks, comparisons, and known issues.
  4. 4The agent synthesizes capabilities, fit, risks, and a recommendation, citing sources.
  5. 5A formatted evaluation page is published to the team's Confluence space.

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 PerplexitySearch-grounded answers with citations.
  3. 3
    Connect ConfluenceSpaces, pages, blueprints.
  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.