Skip to main content
Parallel (Parallel Web Systems) connects with an API key from the Parallel platform. One key covers all three surfaces: search, extraction, and asynchronous task runs. What makes it different from a keyword search API is the objective: you describe what you are trying to learn, and Parallel selects the excerpts that answer it - so one call replaces several keyword searches.

​
What you can do

Actions - search the web, read pages, start a task run, read a task run. Triggers - none. Use it through the assistant in chat or as an action node in an automation.

​
Get your credential

1

Open the Parallel platform

Sign in at platform.parallel.ai.
2

Generate an API key

Generate a key and copy it.

​
Connect

1

Open Integrations

In arg.ai, go to Settings → Integrations and click Connect on Parallel.
2

Paste the key

Enter your API key in the API key field.
3

Save

arg.ai checks the key without spending a search, then connects it.

​
Use it

  • In chat: “Research this company’s recent funding with Parallel and cite the sources.”
  • In an automation: add a Parallel action node to start a task run per row of a spreadsheet, then read each run’s structured output back into the sheet.

​
Search modes

Pick a mode for the latency and cost you need: turbo is the fastest and cheapest, basic suits most agent workloads, fast fits a one-second budget, and advanced (the default) is the deepest. Narrow the sources with include_domains / exclude_domains and after_date only when you must - a source policy can cut result quality by excluding relevant pages.

​
Task runs are asynchronous

Start a task run returns a run id immediately. Choose a processor for the depth you need - lite and base for simple enrichments, core for cross-referenced answers, pro and ultra for exploratory research - and append -fast to any of them to trade data freshness for latency. The deeper tiers run for minutes to hours. Read it back by id with Read a task run. While the run is still working, it returns the run’s status; once that is terminal, the same read returns the finished output with its citations and confidence, so a polling automation only needs the one action.