Monitor a website, extract text and links, navigate to subpages with potential profiles, and store social profile data in Supabase for outreach.
The AI agent starts with a target URL and crawls the site to collect visible text and all links. It identifies patterns that indicate social profiles, follows promising subpages, and aggregates found profiles. Finally, it stores results in Supabase with context and provenance, ready for outreach, enrichment, or CRM integration.
Concrete actions the agent takes to gather and organize social profile data.
Crawl target pages to collect text and links.
Identify social profile URL patterns across pages.
Follow discovered links to subpages likely to contain profiles.
Parse and normalize extracted data into a consistent schema.
Store results in Supabase with source URLs and timestamps.
Notify downstream systems when new data is found or updated.
The agent turns scattered web content into a structured dataset, enabling reliable outreach and enrichment. It reduces manual site-by-site checks and ensures consistency across profiles.
A simple 3-step system to go from URL to usable data.
Enter a target website URL and initialize the crawl with configured prompts and parsing rules.
Extract page text and all links, identify social profile patterns, and navigate to candidate subpages.
Normalize data, push results to Supabase, and trigger downstream workflows or alerts.
A realistic scenario showing task, time, and outcome.
Scenario: A marketing team wants to build a list of public social profiles from a partner site. The agent ingests the homepage, crawls 15 pages in 6 minutes, discovers 9 social profile links, and stores 9 entries in Supabase with sources and timestamps. Outcome: A ready-to-use outreach list appears in the database, with metadata for each profile and its source page.
Roles that gain concrete value from automated social-link discovery.
Build a verified social profile list from target domains for outreach campaigns.
Enrich CRM records with public social handles to improve contact context.
Locate public professional profiles to support talent outreach and branding.
Assemble client social presence data for audits and campaigns.
Assess brand mentions and social footprints across a site to inform strategy.
Verify data sources and ensure usage aligns with terms and policies.
Core tools that enable data capture, storage, and access.
Stores input URLs and crawl results; provides a query layer for downstream apps.
Extracts visible text from pages to surface signal for profile extraction.
Extracts all links from a page to discover subpages with potential profiles.
Concrete scenarios where automated social-link discovery shines.
Common questions about how this AI agent works and what to expect.
The agent collects page text, discovered links, and social profile URLs, along with source URLs and crawl timestamps. It stores results with metadata to support traceability and auditing. Data is kept in a structured format suitable for export to downstream systems. If needed, you can adjust the data schema via prompts to collect additional fields.
All results are written to Supabase for centralized access. You can query by domain, page, or profile URL, and you can export a dataset for CRM or enrichment tools. Access controls can be configured per project to limit who can view or modify data. The ingestion process timestamps each record to maintain a clear data lineage.
Yes. You can tailor the extraction prompts and parsing rules to prioritize specific platforms or patterns. The agent can be configured to ignore non-target domains and to treat certain subpages as primary data sources. Customization can be applied to a per-site rule set to reduce noise and improve precision.
The agent relies on the visible text and links available during crawl; if a page blocks access or loads content dynamically, results may be partial. You can adjust wait times, retry policies, and fallback rules to improve chances of capturing meaningful data. In cases of persistent blocks, you can provide alternate pages to test.
The agent retrieves publicly available information from websites and follows standard data usage practices. Compliance depends on the site’s terms of use and applicable regulations. It’s recommended to maintain an opt-in workflow where possible and to review collected data before deployment in outreach campaigns.
You configure access keys and database endpoints in your project settings. The agent writes crawl results to defined tables and exposes endpoints for downstream tools to import data. You can switch storage backends if needed, but you may need to adjust data schemas and prompts accordingly.
Yes. The stored data can be exported as CSV or JSON for CRM imports, marketing tools, or analytics platforms. You can also set up webhooks or API calls to push new data to downstream systems automatically on crawl completion.
Monitor a website, extract text and links, navigate to subpages with potential profiles, and store social profile data in Supabase for outreach.
