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August 21, 2025

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Webhooks for the Task API

Webhooks are now available for the Parallel Task API. When you’re orchestrating hundreds or thousands of long-running web research tasks, webhooks push real-time notifications to your endpoint as tasks complete. This eliminates the need for constant polling. Learn more in our latest blog.
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August 14, 2025

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Deep Research Benchmarks

Today, we’re announcing that Parallel is the only AI system to outperform both humans and leading AI models like GPT-5 on the most rigorous benchmarks for deep web research. Our APIs are now broadly available, bringing production-grade web intelligence to any AI agent, application, or workflow. Learn more in our latest blog.
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August 7, 2025

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Server-Sent Events for Tasks

Server-Sent Events are now available for Parallel Task API runs. SSE delivers live progress updates, model reasoning, and status changes as tasks execute. Learn more in our latest blog.
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August 5, 2025

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New advanced deep research processors

New advanced processors are now available with the Parallel Task API, giving you granular control over compute allocation for critical research workflows. Last month, we demonstrated that accuracy scales consistently with compute budget on BrowseComp, achieving 39% and 48% accuracy with 2x and 4x compute respectively. These processors are now available as ultra2x and ultra4x, alongside our most advanced processor yet - ultra8x. Learn more in our latest blog.
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August 4, 2025

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Auto Mode in the Parallel Task API

The Parallel Task API now supports Auto Mode, enabling one-off web research queries without requiring explicit output schemas. Simply ask a question. Our processors will then conduct research and generate a structured output schema for you. Learn more in our latest blog.
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July 31, 2025

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State-of-the-art Search API benchmarks

The Parallel Search MCP Server, built on the same infrastructure as the Parallel Search API, demonstrates superior performance on the WISER-Search benchmark while being up to 50% cheaper. Learn more in our latest blog.

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Parallel Search MCP Server in Devin

The Parallel Search MCP Server is now live in Devin’s MCP Marketplace, bringing high quality web research capabilities directly to the AI software engineer. With a web-aware Devin, you can ask Devin to search online forums to debug code, linear from online codebases, and research APIs. Learn more in our latest blog.
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July 28, 2025

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Tool Calling via MCP Servers

The Parallel Task API now supports Tool Calling via MCP Servers. With a single API call, you can choose to expose tools hosted on external MCP-compatible servers and invoke them through the Task API. This allows Parallel agents to reach out to private databases, code execution sandboxes, or proprietary APIs - without custom orchestrators or standalone MCP clients. Learn more in our latest blog.
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July 14, 2025

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The Parallel Search MCP Server

The Parallel Search MCP Server is now generally available, making our Search API instantly accessible to any MCP-aware model as a drop-in tool. This hosted endpoint takes flexible natural language objectives as inputs and provides AI-native search results with extended webpage excerpts. Built on Parallel’s proprietary web infrastructure, it offers plug-and-play compatibility with OpenAI, Anthropic, and other MCP clients at production scale. Learn More.
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July 8, 2025

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Source Policy for Task API and Search API

Source Policy is now available for both the Parallel Task API and Search API - giving you granular control over which sources your AI agents access and how results are prioritized. Source Policy lets you define exactly which domains your research should include or exclude. Learn more in our latest blog.
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July 2, 2025

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Task Group API in beta

Today we’re launching the Task Group API in public beta for large-scale web research workloads. When your pipeline needs hundreds or thousands of independent Parallel Tasks, the new Group API wraps operations into a single batch with unified monitoring, intelligent failure handling, and real-time results streaming. These batch operations are ideal for bulk CRM enrichment, due diligence, or competitive intelligence workflows. Learn more in our latest blog.
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June 17, 2025

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State of the Art Deep Research APIs

Parallel Task API processors achieve state-of-the-art performance on BrowseComp, a challenging benchmark built by OpenAI to test web search agents’ deep research capabilities. Our best processor (ultra) reaches 27% accuracy, outperforming human experts and all commercially available web search and deep research APIs - while being significantly cheaper. Learn more in our latest blog.
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August 05, 2025

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Search API in beta

The Parallel Search API is now available in beta - providing a tool for AI agents to search, rank, and extract information from the public web. Built on Parallel’s custom web crawler and index, the Search API takes flexible inputs (search objective and/or search queries) and returns LLM-ready ranked URLs with extended webpage excerpts. Learn more in our latest blog.
curl https://api.parallel.ai/v1beta/search \
  -H "Content-Type: application/json" \
  -H "x-api-key: ${PARALLEL_API_KEY}" \
  -d '{
    "objective": "When was the United Nations established? Prefer UN'\''s websites.",
    "search_queries": [
      "Founding year UN",
      "Year of founding United Nations"
    ],
    "processor": "base",
    "max_results": 5,
    "max_chars_per_result": 1500
  }'
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May 30, 2025

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Chat API in beta

The Parallel Chat API is now generally available in beta. The Chat API utilizes our rapidly growing web index to bring real-time low latency web research to interactive AI applications. It returns OpenAI ChatCompletions compatible streaming text and JSON outputs, and easily drops in to new and existing web research workflows. Learn more in our latest blog.
from openai import OpenAI

client = OpenAI(
    api_key="PARALLEL_API_KEY",  # Your Parallel API key
    base_url="https://api.parallel.ai"  # Parallel's API beta endpoint
)

response = client.chat.completions.create(
    model="speed", # Parallel model name
    messages=[
        {"role": "user", "content": "What does Parallel Web Systems do?"}
    ],
    response_format={
        "type": "json_schema",
        "json_schema": {
            "name": "reasoning_schema",
            "schema": {
                "type": "object",
                "properties": {
                    "reasoning": {
                        "type": "string",
                        "description": "Think step by step to arrive at the answer",
                    },
                    "answer": {
                        "type": "string",
                        "description": "The direct answer to the question",
                    },
                    "citations": {
                        "type": "array",
                        "items": {"type": "string"},
                        "description": "Sources cited to support the answer",
                    },
                },
            },
        },
    },
)

print(response.choices[0].message.content)
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May 21, 2025

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Basis with Calibrated Confidences

Basis is a comprehensive suite of verification tools for understanding and validating Task API outputs through four core components.
  1. Citations: Web URLs linking directly to source materials.
  2. Reasoning: Detailed explanations justifying each output field.
  3. Excerpts: Relevant text snippets from citation URLs.
  4. Confidences: A calibrated measure of confidence classified into low, medium, or high categories.
Use Basis with Calibrated Confidences to power hybrid AI/human review workflows focused on low confidence outputs - significantly increasing leverage, accuracy, and time efficiency. Read more in our latest blog post.
{
 "field": "revenue",
 "citations": [
   {
     "url": "https://www.microsoft.com/en-us/Investor/earnings/FY-2023-Q4/press-release-webcast",
     "excerpts": ["Microsoft reported fiscal year 2023 revenue of $211.9 billion, an increase of 7% compared to the previous fiscal year."]
   },
   {
     "url": "https://www.sec.gov/Archives/edgar/data/789019/000095017023014837/msft-20230630.htm",
     "excerpts": ["Revenue was $211.9 billion for fiscal year 2023, up 7% compared to $198.3 billion for fiscal year 2022."]
   }
 ],
 "reasoning": "The revenue figure is consistent across both the company's investor relations page and their official SEC filing. Both sources explicitly state the fiscal year 2023 revenue as $211.9 billion, representing a 7% increase over the previous year.",
 "confidence": "high"
}

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Billing Upgrades

We’ve made several improvements to help you more seamlessly manage and monitor Billing. This includes:
  • Auto-reload: Avoid service interruptions by automatically adding to your balance when configured thresholds are met.
  • Billing History: View prior Invoices and Receipts. Track status, amount charged, and timestamp of charges.

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April 24, 2025

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Task API for web research

The Parallel Task API enables state-of-the-art web research at scale, with the highest quality at every price point. State your research task in natural language and Parallel will do the rest of the heavy lifting - generating input/output schemas, finding relevant URLs, extracting data in a structured format.
from parallel import Parallel
from pydantic import BaseModel, Field

class ProductInfo(BaseModel):
    use_cases: str = Field(
        description="A few use cases for the product."
    )
    differentiators: str = Field(
        description="3 unique differentiators for the product as a bullet list."
    )
    benchmarks: str = Field(
        description="Detailed benchmarks of the product reported by the company."
    )

client = Parallel()
result = client.task_run.execute(
    input="Parallel Web Systems Task API",
    output=ProductInfo,
    processor="core"
)

print(f"Product info: {result.output.parsed.model_dump_json(indent=2)}\n")
print(f"Basis: {'\n'.join([b.model_dump_json(indent=2) for b in result.output.basis])}")

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Python SDK

Our SDK is now available for Python, making it easy to implement Parallel into your applications. The Python SDK is at parity with our Task API endpoints and simplifies request construction and response parsing.

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Flexible Processors

When running Tasks with Parallel, choose between 5 processors - lite, base, core, pro, and ultra. We’ve built distinct processor options so that you can optimize price, latency, and quality per task.

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Self-Serve Developer Platform

Platform is the home for Playground, API Keys, Docs, Billing, Usage, and more.
  • Run a research task from scratch or using a template from Task Library
  • Generate and manage API keys for secure integration
  • Manage billing details, auto-reload settings, and usage analytics
  • Access comprehensive guides to learn how to use the API