MARKET RESEARCH

On-Demand Filing Diff Memo Published to Confluence

On a webhook trigger with a company and filing URL, fetches the document, diffs it against the prior filing.

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook receives company + filing URLHTTP webhook
  • ActionBrave Search finds prior comparable filingBraveBrave Search
  • ActionFetch new and prior filing textOpenAI
  • ActionOpenAI builds structured diff memoOpenAI
  • OutputPublish versioned memo to ConfluenceConfluenceConfluence

What it does

When an analyst submits a company and a filing URL, this workflow pulls the new document, retrieves the prior comparable filing via Brave Search, and produces a section-by-section diff memo highlighting changed risk factors, restated numbers, and new disclosures. The finished memo is published as a versioned Confluence page in the coverage team's research space.

When to use it

Use it when an analyst spots a fresh filing and wants a clean, shareable diff memo in the team wiki rather than a throwaway Slack message. It is ideal for building a durable, searchable archive of what changed and when across covered names.

How it works

  1. 1A webhook receives the company name and the new filing URL.
  2. 2Brave Search locates the prior comparable filing for the same issuer and filing type.
  3. 3An action fetches both the new and prior filing text.
  4. 4OpenAI generates a structured diff: changed risk factors, restated figures, new line items, and a plain-English so-what.
  5. 5The memo is published to Confluence as a new page under the issuer's folder, preserving page history for audit.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect Brave SearchWeb, news, image, video search.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect ConfluenceSpaces, pages, blueprints.
  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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