Integration
Describe what you want to scrape or research, and Twin builds an agent that runs it on a schedule—feeding results into Sheets, Docs, or any downstream tool.
Integration guide
Twin treats Apify as part of a larger workflow, not as an isolated connector. An agent can read the relevant records, combine them with context from other tools, decide what needs to happen next, and report the finished work back to the team.
The page below shows the practical automation patterns for Apify: what the agent can monitor, which actions it can take, and how the workflow stays observable when it runs on a schedule.
Common starting points include sales prospecting, lead enrichment, competitive research. Each example is designed to become a reusable agent, so teams can start from a narrow job and expand it as the process matures.
Twin is most useful when apify returns raw data. Getting that data into Sheets, a CRM, or a doc usually means writing ETL scripts or stitching together multiple tools manually. Twin handles the entire chain—scrape, parse, route—without you writing any of it.
Real Apify workflows the Twin community runs every day, ready for you to clone.
Pull structured product and pricing data from competitor sites via Apify and compile it into a comparison report.
ExploreScrape LinkedIn for profiles matching specific roles, filter out irrelevant results, and export names, titles, and URLs.
ExploreSearch LoopNet, Crexi, and similar platforms for properties matching criteria like location, size, and price range.
ExploreScrape event calendars across multiple venues, then enrich contacts for outreach—all in one repeatable agent run.
ExploreCombine Apify scraping with Google Trends and YouTube data to surface signals for content or market research.
ExploreRun weekly LinkedIn job scans to capture B2B leads matching hiring signals, then write structured rows to a Sheet.
ExploreThree steps from idea to a running Apify agent.
Connect via OAuth
Sign in to Apify once. Twin securely manages the connection and handles token refreshes for you.
Describe the workflow
Tell Twin in plain English what you want done in Apify. The agent figures out the API calls itself.
Twin builds and runs
Twin assembles the agent, runs it on demand or on a schedule, and adapts when Apify responds in unexpected ways.
What makes Twin a better fit than a generic automation tool.
Apify returns raw data. Getting that data into Sheets, a CRM, or a doc usually means writing ETL scripts or stitching together multiple tools manually. Twin handles the entire chain—scrape, parse, route—without you writing any of it.
Users report that manual copying between Apify outputs and downstream tools creates stale data and missed follow-ups. Twin agents run the same workflow on a schedule, so the data stays current without anyone remembering to trigger it.
Some Apify workflows surface data that isn't cleanly accessible via structured API calls. Twin can fall back to browser-driven steps when needed, so the agent completes the job regardless of how the underlying page is structured.
Be the first to build a Apify agent.
The Twin community hasn't published a Apify agent yet — describe what you'd like to automate and we'll build it for you in minutes.
Build the first Apify agentPatterns that show up across the Twin community — start from one and adapt it.
Find, enrich, and prioritize prospects from web and app data.
Turn sparse lead records into usable context for outreach.
Monitor competitors and summarize changes.
Track products, pricing, orders, and competitor stores.
These related integration pages give crawlers and readers another path through the automation catalog. They connect Apify to nearby apps, categories, and paired workflows that teams often evaluate together.
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