Automate Parallel.ai with AI Agents

State-of-the-art web search, deep research, and data extraction APIs for AI agents. Provides web intelligence infrastructure with search, content extraction, and deep research capabilities optimized for LLMs.

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The Most Powerful Parallel.ai Integration

Transform your workflows into intelligent automation hubs. Our integration gives you complete control over your Parallel.ai data with enterprise-grade reliability and performance.

Cloud-Based Automation

Seamlessly sync and automate your Parallel.ai data in real-time across all your tools.

Lightning Fast

Execute actions and retrieve data in milliseconds with our optimized API.

Enterprise Security

Bank-level encryption and OAuth 2.0 authentication keep your data completely secure.

Scale Infinitely

Handle millions of operations without breaking a sweat.

Available Parallel.ai Actions

Explore the powerful actions available for Parallel.ai

All Actions

Extract Web Content

Action

Extract clean, LLM-optimized markdown content from specific URLs. Can retrieve focused excerpts based on an objective or the full page content. Supports up to 10 URLs per request with customizable fetch policies for balancing speed (cached) vs freshness (live). Ideal for converting web pages into structured data for AI processing.

Get Task Run Result (Blocking)

Action

Retrieve the result of a task run by run_id, blocking until the run is completed or timeout is reached. This endpoint waits for task completion (up to 10 minutes by default) and returns the full output with citations, reasoning, and confidence scores. Unlike the regular status endpoint, this automatically waits for completion, eliminating the need for polling.

Get Task Run Status

Action

Retrieve the status and results of any task run using its run_id. Returns current status (processing, completed, failed) and output data if the task has completed. Use this to poll for task completion.

Task Group: Create Group

Action

Create a new task group to organize and manage related tasks for batch processing. Task groups act as containers for multiple tasks, allowing efficient management, tracking, and result retrieval. Optionally provide metadata for organization and filtering. Returns a taskgroup_id to use when adding tasks.

Create Task Run

Action

Create a generic task run with custom input and processor configuration. Use this for running any Parallel.ai task that accepts natural language input. Returns a run_id to track task status and retrieve results.

Create Deep Research Task

Action

Create a comprehensive deep research task that transforms natural language research queries into structured intelligence reports. Accepts research prompts up to 15,000 characters and returns structured JSON with automatic schema generation or markdown reports. Tasks can take up to 45 minutes to complete. Use "pro" processor for balanced performance or "ultra" for maximum quality and depth. Includes inline citations and verification data.

Get Deep Research Result

Action

Retrieve the results of a completed deep research task. Returns either structured JSON output with auto-generated schema or markdown formatted report based on the task configuration. Includes calibrated verification metrics for output quality assurance. Poll this endpoint to check task status and retrieve results once processing is complete.

FindAll: Get Run Results

Action

Poll for the status and results of a FindAll run. Returns detailed entity data including filter results, enrichment results, relevance scores, and metadata about the search process (pages read/considered). Use this to check if the run is complete and retrieve the discovered entities.

FindAll: Ingest Query

Action

Convert a natural language query into a structured FindAll specification. Accepts queries like "Find all AI companies that raised Series A in 2024 and get their website, CEO, and CTO" and returns a structured spec with enrichment fields and constraints. This spec is then used to start a FindAll run.

FindAll: Create Run

Action

Start a FindAll run to discover and enrich entities based on a structured query specification. Use the spec from the ingest endpoint, optionally provide seed entities, and configure quality level (base/pro) and result limits. Returns a findall_id to track progress and retrieve results. Useful for market research, lead generation, and competitive analysis.

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