MARKET RESEARCH
Agent-Driven Earnings Read-Through with Cross-Source Validation
An agent reads a competitor's earnings transcript, validates the guidance claims against Perplexity and analyst coverage, drafts a reasoned thesis on what the changes mean.
How it runs
The automated pipeline, trigger to output.
- TriggerManual run names target company and call
- ActionFirecrawl scrapes the transcriptFirecrawl
- ActionAgent extracts guidance and forms hypothesesOpenAI
- ActionPerplexity validates claims against analyst coveragePerplexity
- LogicReconcile sources and assign confidence levels
- OutputPublish reasoned read-through to ConfluenceConfluence
What it does
Goes beyond extraction: an agent reads the earnings transcript, identifies the guidance changes, then independently checks those claims against outside coverage and analyst reaction before forming a reasoned view on what the shift means for your competitive position. It produces an analyst-style read-through, not just a summary.
When to use it
When you need judgment, not just facts — a strategy or corp-dev team wanting a defensible interpretation of a competitor's guidance change, with sourcing and counterpoints, ready to circulate for internal debate.
How it works
- 1A manual run names the target company and its just-released call.
- 2Firecrawl scrapes the transcript text.
- 3The agent extracts guidance changes and forms initial hypotheses.
- 4Perplexity gathers external analyst reaction and market context to validate or challenge each claim.
- 5The agent reconciles sources, drafts a thesis with confidence levels and counterpoints.
- 6The finished read-through is published to a Confluence space for team review.
Set it up
What you configure once, before turning it on.
- 1Connect FirecrawlCrawl, scrape, structured extract.
- 2Connect PerplexitySearch-grounded answers with citations.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect ConfluenceSpaces, pages, blueprints.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.