LEAD GENERATION
Dependents Research Agent: Build a Buying-Intent Dossier Per Adopter and File It in Attio
An agent investigates each company depending on your package, reading their repo's usage depth and public footprint.
How it runs
The automated pipeline, trigger to output.
- TriggerManual run with a shortlist of target dependents
- ActionRead each dependent repo's usage depth and activityGitHub
- ActionGather public company context, funding, tech-stack signalsExa
- ActionSynthesize buying-intent dossier with angle and objectionOpenAI
- OutputFile dossier and fit verdict against company in AttioAttio
What it does
Goes beyond a name and email. For each company dependent on your package, an agent inspects how deeply they use it (import surface, version pinned, repo activity), gathers public context on the company, and synthesizes a buying-intent dossier with a recommended outreach angle and likely objection. The dossier is filed against the company in Attio.
When to use it
Use it for high-value enterprise dependents where a generic template won't land and a rep needs real ammunition before reaching out. Best run on a shortlist of large-org adopters rather than the full long tail, since each dossier does meaningful research work.
How it works
- 1A manual run starts with a shortlist of target dependent companies.
- 2The agent reads each dependent repo's usage depth and activity from GitHub.
- 3Exa gathers public company context, funding, and tech-stack signals.
- 4OpenAI synthesizes a buying-intent dossier with angle and likely objection.
- 5The agent files the dossier and a fit verdict against the company in Attio.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect ExaNeural search across the web.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect AttioReal-time CRM with structured data + powerful views.
- 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.
More Lead Generation workflows
Manual Brave keyword sweep into an Airtable research board
On demand, sweeps a topic across Brave Search, clusters the results by buying stage with an LLM, and writes a deduplicated research board to Airtable with company, source URL.
Fast-track hot webinar leads into HubSpot and ping the rep on Slack
After a webinar, identify attendees whose poll answers signal high purchase intent, create or update their HubSpot contact with a lead score.
Webhook-triggered Brave rising-keyword check into a Notion trend queue
When an external trend or alert tool fires a webhook with a keyword, checks Brave for current intent volume and freshness, has an LLM judge whether it's a real warm signal.
Fuzzy-match badge companies to Salesforce accounts and enrich
Resolves messy hand-typed company names from badge scans to canonical Salesforce accounts using domain and fuzzy-name matching, enriches missing firmographics.
Daily rollup of scored webinar leads from Airtable into HubSpot lists
On a schedule, read newly scored webinar leads from Airtable, sync each into the matching HubSpot tiered list (Hot/Warm/Cold).
Instantly triage uploaded badge CSVs and notify the SDR lead
Accepts a badge-scan CSV via webhook, validates and dedupes it on the spot, checks each attendee against HubSpot.
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.