Where agents find answers

Web infrastructure for AI to search, extract, monitor, and reason over the world's information

Start building for freeP[Start building for freeP](https://platform.parallel.ai/)
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Join the teams building the AI frontier

Trusted by category-defining startups & Fortune 500 enterprises

  • Harvey
  • Formation Bio
  • Attio
  • Starbridge
  • Granola
  • Monaco
  • Manus
  • Hex
  • Modal
  • Dropbox
  • Owner
  • Greptile
  • Rogo
  • Profound
  • Opendoor

Join the teams building the AI frontier

Trusted by category-defining startups & Fortune 500 enterprises

HarveyCase Study
Formation BioFormation Bio
AttioAttio
StarbridgeCase Study
GranolaGranola
MonacoMonaco
ManusManus
HexHex
ModalCase Study
DropboxDropbox
OwnerOwner
GreptileGreptile
RogoRogo
ProfoundCase StudyOpendoorCase Study

Put the web to work across every industry

  • Monitor portfolios, signals, and pricing

    Watch the things your business runs on: portfolio companies, target accounts, competitor pricing, regulations. Get a structured alert the moment something material changes, so you only hear what matters to you.

    Example query: Find the latest funding rounds for AI infrastructure startups

  • Answer with fresh facts, inside your product

    Give your assistant, copilot, or coding agent current, cited answers fast enough for a chat thread: live docs, real-world context, breaking news. Your users get the answer that's relevant today, not at training time.

    Example query: What changed in the EU AI Act this month?

  • Automate research on any account, market, or thesis at scale

    Hand over an objective and get back hundreds of finished, cited reports in minutes: an account brief before the call, an investment memo, a competitive landscape. Analyst-grade work, embedded in your workflow.

    Example query: Build a cited brief on the industrial robotics market

  • Enrich companies, people, and accounts

    Drop in a list or describe who you're looking for. Get back live, structured profiles: target accounts, investment candidates, vendors, or the long tail. Every field cited and confidence-scored, ready for your CRM or pipeline.

    Example query: Enrich these 50 accounts with headcount and funding

Put the web to work across every industry

Monitor clinical trial registries and FDA updates for my target and indication.

MONITOR

New Phase 2 trial posted for a GLP-1 analog

5M AGO

clinicaltrials.gov

FDA grants Fast Track to a KRAS inhibitor

1H AGO

fda.gov

Competitor reports positive Phase 3 topline

5H AGO

businesswire.com

Watch the things your business runs on: portfolio companies, target accounts, competitor pricing, regulations. Get a structured alert the moment something material changes, so you only hear what matters to you.

FinanceLife SciencesSalesInsurance
Try Monitor[Try Monitor](https://platform.parallel.ai/play/monitor)

Give your assistant, copilot, or coding agent current, cited answers fast enough for a chat thread: live docs, real-world context, breaking news. Your users get the answer that's relevant today, not at training time.

ProductivityCoding & BuildingLegalFinance
Try Search[Try Search](https://platform.parallel.ai/play/search)

Hand over an objective and get back hundreds of finished, cited reports in minutes: an account brief before the call, an investment memo, a competitive landscape. Analyst-grade work, embedded in your workflow.

FinanceLife SciencesSalesLegal
Try Deep Research[Try Deep Research](https://platform.parallel.ai/play/task)

Drop in a list or describe who you're looking for. Get back live, structured profiles: target accounts, investment candidates, vendors, or the long tail. Every field cited and confidence-scored, ready for your CRM or pipeline.

SalesLife SciencesFinanceInsurance
Try FindAll[Try FindAll](https://platform.parallel.ai/play/findall)

Better answers start with better web search

Parallel gives agents real-time access to fresh and relevant context from the web. Search billions of pages, extract key information, monitor changes, and do complex research with cited outputs you can trust in production.

API Playground[API Playground](https://platform.parallel.ai/)

What do I need to know for my meeting tomorrow?

With Parallel retrieval

The company closed a $40M Series B last week and has been hiring aggressively in enterprise sales since, a signal they're moving upmarket. The lead contact joined as VP of Product in January, previously led product at a direct competitor, and published a piece last week flagging retrieval quality as their biggest infrastructure gap.

High confidence

LLM only

The company is an enterprise SaaS business focused on workflow automation, backed by Sequoia and Index Ventures. The lead contact is a senior product leader who previously worked at Salesforce. They've been growing their enterprise segment and expanding internationally.

Better answers start with better web search

Parallel gives agents real-time access to fresh and relevant context from the web. Search billions of pages, extract key information, monitor changes, and do complex research with cited outputs you can trust in production.

API Playground[API Playground](https://platform.parallel.ai/)

What do I need to know for my meeting tomorrow?

LLM only
Your agent

The company is an enterprise SaaS business focused on workflow automation, backed by Sequoia and Index Ventures. The lead contact is a senior product leader who previously worked at Salesforce. They've been growing their enterprise segment and expanding internationally.

With Parallel retrieval
Your agent

The company closed a $40M Series B last week and has been hiring aggressively in enterprise sales since, a signal they're moving upmarket. The lead contact joined as VP of Product in January, previously led product at a direct competitor, and published a piece last week flagging retrieval quality as their biggest infrastructure gap.

High confidence

Designed to compose

With Parallel, agents can find quick answers, watch the web for changes, enrich databases, and do deep research across the deepest corners of the web, all through a single API.

API Playground[API Playground](https://platform.parallel.ai/)
  • EXTRACT: Find the latest news on my competitors
  • MONITOR: Alert me when any of them raises a new round
  • DEEP RESEARCH: Build a cited funding report
EXTRACT

Pull funding details from these 40 press releases

MONITOR

Alert me when any of them raises a new round

DEEP RESEARCH

Build a cited brief on the most active investors

Designed to compose

With Parallel, agents can find quick answers, watch the web for changes, enrich databases, and do deep research across the deepest corners of the web, all through a single API.

API Playground[API Playground](https://platform.parallel.ai/)

Production-grade trust

Parallel's Web Agents use Basis to attach provenance and calibrated confidence scoring to every output, for trusted use and auditability in production. Every score can be fed back into retrieval to continuously improve results over time.

API Playground[API Playground](https://platform.parallel.ai/)

Production-grade trust

Parallel's Web Agents use Basis to attach provenance and calibrated confidence scoring to every output, for trusted use and auditability in production. Every score can be fed back into retrieval to continuously improve results over time.

API Playground[API Playground](https://platform.parallel.ai/)

The World Wide Web was invented by Tim Berners Lee[1] at CERN[2] in 1989[3].

HIGH CONFIDENCE

“Tim Berners-Lee”

0.99
[1]cern.ch

“CERN”

0.94
[2]britannica.com

“1989”

0.98
[3]w3.org
{ "content": "The World Wide Web was invented by Tim Berners-Lee [1] at CERN [2] in 1989 [3].", "basis": [ { "field": "inventor", "citations": ["cern.ch/…"], "reasoning": "…", "confidence": 0.99 }, { "field": "organization", "citations": ["britannica.com/…"], "reasoning": "…", "confidence": 0.94 }, { "field": "year", "citations": ["w3.org/…"], "reasoning": "…", "confidence": 0.98 } ], "confidence": 0.97 }

More signal per token

Reduce your inference spend while improving quality with more context-efficient retrieval. Every query is served by Parallel’s web index, purpose-built for agents.

Onboard your agent[Onboard your agent](https://docs.parallel.ai/getting-started/overview#onboard-your-agent)
$ task 1: Enrich these 2,400 accounts for my CRM
YOUR CONTEXT WINDOW
With Parallel retrieval1 TASK$0.01
Default search provider1 TASK$0.12

More signal per token

Reduce your inference spend while improving quality with more context-efficient retrieval. Every query is served by Parallel’s web index, purpose-built for agents.

Onboard your agentA[Onboard your agentA](https://docs.parallel.ai/getting-started/overview#onboard-your-agent)
Products

Everything your agent needs to work with the web

From a single search to always-on monitoring, Parallel gives agents every way to find, research, and act on web data. All on one platform, powered by the same proprietary index.

How Uber and Lyft won their first million users
Uber
First million

Paid referrals in dense metros.

Lyft
First million

Low-friction shared rides.

Key difference

Uber prioritized driver supply; Lyft leaned into brand and social sharing.

Task

Deep research and analysis at enterprise scale. Give it an objective, get back structured, cited answers

Watching 1,200 Accounts

Monitor

Track changes and act on what matters, with structured alerts via webhook.

What’s driving the spike in gas prices?
Which regions are hit the hardest?

Responses

Cited, synthesized answers from the live web in seconds, built for synchronous interactions.

Searching
1
2
3
4
Most-cited papers on retrieval-augmented generation

Search

The highest-accuracy web search for your AI. Fresh, fast, and affordable grounding in one call.

Extracting
URLshttps://arxiv.org/pdf/1706.03762

Extract

Get full or excerpted contents from the public web, including PDFs, JS-heavy pages, and government sites

Companies building web agents
ID
Company
Product releases
Funding
1
parallel.ai
2
acme.com
3
globex.com
4
scape.net

FindAll

Build structured datasets with real-time enrichment. Describe what you want, get a live list.

TaskMonitorResponsesFindAll
SearchExtract
Parallel Web Index
Index by Parallel
FortuneThe AtlanticPitchBookTracxnPR NewswireRocketReachZoomInfoExponential ViewThe GeneralistNot BoringSourcesFortuneThe AtlanticPitchBookTracxnPR NewswireRocketReachZoomInfoExponential ViewThe GeneralistNot BoringSources

Retrieval, built from the ground up

Parallel makes the web programmable, bringing the world’s information to agents, grounding them in better facts, helping them do complex knowledge work, and even keeping them proactively informed. Everything runs on Parallel’s proprietary web search stack, built for the scale AI demands.

Web Agents

Specialized agents for web research, built to outperform generalist models on cost, quality, and latency. They plan each question, search, read across dense sources, and return cited answers, all running on custom models, a purpose-built harness, and the Parallel Web Index.

Web Tools

Raw web search primitives designed from the ground up for use by AI agents, including our own. Search finds and ranks the most relevant information sources to ground answers in real-time data; Extract fetches content directly from the page for easy LLM synthesis.

Web Index

Proprietary, state-of-the-art index of the web, continuously updated across hundreds of billions of pages and ranked for what’s authoritative and fresh. It includes licensed content other indexes don’t have: paywalled publishers, premium newsletters, and proprietary sources through Index partnerships. Every search call, every agent runs on it.

Our products

Retrieval, built from the ground up

Parallel makes the web programmable, bringing the world's information to agents, grounding them in better facts, helping them do complex knowledge work, and even keeping them pro-actively informed. Everything runs on Parallel's proprietary web search stack, built for the scale AI demands.

  • [Task API](https://parallel.ai/products/task)

    Deep research and analysis at enterprise scale. Give it an objective, get back structured, cited answers

  • [Monitor API](https://parallel.ai/products/monitor)

    Track changes and act on what matters, with structured alerts via webhook.

  • [FindAll API](https://parallel.ai/products/findall)

    Build structured datasets with real-time enrichment. Describe what you want, get a live list.

  • [Search API](https://parallel.ai/products/search)

    The highest-accuracy web search for your AI. Fresh, fast, and affordable grounding in one call.

  • [Extract API](https://parallel.ai/products/extract)

    Get full or excerpted contents from the public web, including PDFs, JS-heavy pages, and government sites

  • [Parallel Web Index](https://index.parallel.ai)

    Real-time access to the web's most valuable sources, built from the ground up for AIs.

Better, faster, cheaper at every price point

From sub-second lookups to hour-long research, state of the art at every tier

Start building for free[Start building for free](#start)View all benchmarks[View all benchmarks](https://parallel.ai/benchmarks)

SimpleQA

SimpleQA — Accuracy (%) vs Cost (CPM).
ProviderAccuracy (%)Cost (CPM)
Parallel Turbo918
Exa Instant89.320
Tavily Ultra Fast7223
Brave Search8716
SerpAPI76.76

Coding

Coding — Accuracy (%) vs Cost (CPM).
ProviderAccuracy (%)Cost (CPM)
Parallel Turbo79.7131
Exa Instant76.7316
Tavily Ultra Fast71.9314
Brave Search64.3204
SerpAPI54131
OpenAI Web Search76.7475

BrowseComp

BrowseComp — Accuracy (%) vs Cost (CPM).
ProviderAccuracy (%)Cost (CPM)
Parallel Turbo51216
Exa Instant33.7361
Tavily Ultra Fast19.3357
Brave Search38.3430
SerpAPI23.3999

FRAMES

FRAMES — Accuracy (%) vs Cost (CPM).
ProviderAccuracy (%)Cost (CPM)
Parallel Turbo8673
Exa Instant88.3133
Tavily Ultra Fast80.7194
Brave Search81.3146
SerpAPI83.389
OpenAI Web Search85.7296

CPM: USD per 1000 requests. Cost is shown on a Log scale.

Dataset

We evaluated search providers against six open benchmarks covering complementary aspects of agentic search: BrowseComp (hard multi-hop questions that require navigating the live web), Frames (multi-document factoid reasoning), FreshQA (time-sensitive questions where the correct answer depends on recent web information), HLE (Humanity’s Last Exam — expert-level academic questions spanning math, science, and humanities), SealQA (ambiguity-robust factoid QA with intentionally misleading snippets), WebWalker (tasks designed around following links across pages to find an answer).

Evaluation methodology

Every task is run through a shared deep-research harness: a single GPT-5.4 agent is given two tools (web search and web fetch) with an iterative budget of up to MAX_TOOL_CALLS=25 tool calls per question. The agent plans sub-queries, fans out searches, fetches specific pages when snippets are insufficient, and returns an answer when it exhausts the number of allowed tool calls or has sufficient information to answer the question. Each answer is then LLM-graded by GPT-5.4. We report accuracy of the final answer.

We measure accuracy and overall cost, which includes LLM token costs and tool call costs.

Testing dates

April 19-21, 2026

Better, faster, cheaper at every price point

From sub-second lookups to hour-long research, state of the art at every tier

Start building for free[Start building for free](#start)View all benchmarks[View all benchmarks](https://parallel.ai/benchmarks)
6,70PARALLEL TURBO91% / 8CPMEXA INSTANT89.3% / 20CPMTAVILY ULTRA FAST72% / 23CPMBRAVE SEARCH87% / 16CPMSERPAPI76.7% / 6CPM

COST (CPM)

ACCURACY (%)

Loading chart...

CPM: USD per 1000 requests. Cost is shown on a Log scale.

Parallel
Others
Benchmark comparison across Cost (CPM) and Accuracy (%). CPM: USD per 1000 requests. Cost is shown on a Log scale.

Dataset

We evaluated search providers against six open benchmarks covering complementary aspects of agentic search: BrowseComp (hard multi-hop questions that require navigating the live web), Frames (multi-document factoid reasoning), FreshQA (time-sensitive questions where the correct answer depends on recent web information), HLE (Humanity’s Last Exam — expert-level academic questions spanning math, science, and humanities), SealQA (ambiguity-robust factoid QA with intentionally misleading snippets), WebWalker (tasks designed around following links across pages to find an answer).

Evaluation methodology

Every task is run through a shared deep-research harness: a single GPT-5.4 agent is given two tools (web search and web fetch) with an iterative budget of up to MAX_TOOL_CALLS=25 tool calls per question. The agent plans sub-queries, fans out searches, fetches specific pages when snippets are insufficient, and returns an answer when it exhausts the number of allowed tool calls or has sufficient information to answer the question. Each answer is then LLM-graded by GPT-5.4. We report accuracy of the final answer.

We measure accuracy and overall cost, which includes LLM token costs and tool call costs.

Testing dates

April 19-21, 2026

Pioneers of the agentic web are building with Parallel

“Authoritative legal data across dozens of countries lives on sites no search engine has ever indexed. Parallel solves that at a scale we couldn't build ourselves.”

Gabe Pereyra, President & Co-Founder, Harvey

“The best agentic search isn't just the fastest or the cheapest. It's net new information that language models don't already know. Parallel delivers that.”

Sarah Sacks, AI Lead, Notion

“Parallel provided us with a big upgrade in speed and index coverage. Combined with a 5x improvement in cost efficiency, it was an easy decision to build our agents with them.”

Vikas Velagapudi, Founder, Convoke

“You cannot make mistakes in financial services. With Parallel, our banking customers run agents that complete complex KYB checks in minutes, not hours.”

Maik Taro Wehmeyer, Co-Founder & CEO, Taktile

“In our internal evaluations we found Parallel to be the fastest and most accurate web search tool we tested. That speed together with its fine-grained control over web search means our agents can iteratively search, view results and refine search terms to get the answers users need.”

James Clough, Head of AI, ModelML

“We benchmarked providers on web research across entity types (companies, people, vessels), geographies, and data richness. Parallel topped every dimension on both breadth of findings and accuracy.”

James Rogers, Product Manager, Bretton AI

“Parallel is core infrastructure for our agents. It outperformed every alternative on quality and cost, pulling from the whole web instead of prepackaged datasets.”

Mihir Garimella, CEO, Actively

“Parallel is the highest accuracy API on the market. It handled the edge cases other providers simply couldn't: obscure companies, ambiguous names, conflicting sources.”

Max Brodeur-Urbas, CEO, Gumloop

“Parallel's Monitor API lets Poke track anything our users care about: their team, their neighborhood, the news that matters to them. It helps make Poke more proactive in their daily lives, which ultimately makes for a better companion.”

Marvin Von Hagen, CEO, Interaction

“Parallel consistently delivered the highest quality results at the best price, and handled the complex government websites every other provider struggled with.”

Sweyn Venderbush, CEO, Starbridge

“Parallel's team was incredibly helpful as we designed how Amp would use their APIs: tool names, params, UI, and other thoughtful guidance. They get it, and they care.”

Quinn Slack, CEO, Amp

“We chose Parallel as our preferred search API because of the comprehension and accuracy of their outputs: structured, well-sourced, and ready to feed straight into our content generation agents.”

Dylan Babbs, Co-founder, Profound

“Our partnership with Parallel replaces repetitive human effort with continuous agentic research that integrates seamlessly into enhanced decision-making systems.”

Sanjeev Vohra, CTIO, Genpact

“We tested every major web search provider. Parallel's outputs came back structured, well-cited, and dense with the right information.”

Amr Shafik, VP Product, Airops

Pioneers of the agentic web are building with Parallel

Hear from the Pioneers[Hear from the Pioneers](https://pioneers.parallel.ai/)

”Authoritative legal data across dozens of countries lives on sites no search engine has ever indexed. Parallel solves that at a scale we couldn't build ourselves.”

Gabe Pereyra
President & Co-Founder, Harvey
Harvey
Case Study→

”The best agentic search isn't just the fastest or the cheapest. It's net new information that language models don't already know. Parallel delivers that.”

Sarah Sacks
AI Lead, Notion
Notion

”Parallel provided us with a big upgrade in speed and index coverage. Combined with a 5x improvement in cost efficiency, it was an easy decision to build our agents with them.”

Vikas Velagapudi
Founder, Convoke
Convoke

”You cannot make mistakes in financial services. With Parallel, our banking customers run agents that complete complex KYB checks in minutes, not hours.”

Maik Taro Wehmeyer
Co-Founder & CEO, Taktile
Taktile

”In our internal evaluations we found Parallel to be the fastest and most accurate web search tool we tested. That speed together with its fine-grained control over web search means our agents can iteratively search, view results and refine search terms to get the answers users need.”

James Clough
Head of AI, ModelML
ModelML

”We benchmarked providers on web research across entity types (companies, people, vessels), geographies, and data richness. Parallel topped every dimension on both breadth of findings and accuracy.”

James Rogers
Product Manager, Bretton AI
Bretton AI

”Parallel is core infrastructure for our agents. It outperformed every alternative on quality and cost, pulling from the whole web instead of prepackaged datasets.”

Mihir Garimella
CEO, Actively
Actively
Case Study→

”Parallel is the highest accuracy API on the market. It handled the edge cases other providers simply couldn't: obscure companies, ambiguous names, conflicting sources.”

Max Brodeur-Urbas
CEO, Gumloop
Gumloop
Case Study→

”Parallel's Monitor API lets Poke track anything our users care about: their team, their neighborhood, the news that matters to them. It helps make Poke more proactive in their daily lives, which ultimately makes for a better companion.”

Marvin Von Hagen
CEO, Interaction
Poke

”Parallel consistently delivered the highest quality results at the best price, and handled the complex government websites every other provider struggled with.”

Sweyn Venderbush
CEO, Starbridge
Starbridge
Case Study→

”Parallel's team was incredibly helpful as we designed how Amp would use their APIs: tool names, params, UI, and other thoughtful guidance. They get it, and they care.”

Quinn Slack
CEO, Amp
Amp
Case Study→

”We chose Parallel as our preferred search API because of the comprehension and accuracy of their outputs: structured, well-sourced, and ready to feed straight into our content generation agents.”

Dylan Babbs
Co-founder, Profound
Profound
Case Study→

”Our partnership with Parallel replaces repetitive human effort with continuous agentic research that integrates seamlessly into enhanced decision-making systems.”

Sanjeev Vohra
CTIO, Genpact
Genpact
Case Study→

”We tested every major web search provider. Parallel's outputs came back structured, well-cited, and dense with the right information.”

Amr Shafik
VP Product, Airops
Airops
Case Study→

Trust

Built for enterprise, secure by design

Build trust with the [Basis framework](https://docs.parallel.ai/task-api/guides/access-research-basis), unique to Parallel: calibrated confidence scores, citations, source excerpts, and reasoning traces.

  • SOC 2 Type 2
  • Zero data retention available
  • HIPAA-ready offering
  • GDPR Compliance
  • Single sign-on (SSO/SAML)
Trust

Built for enterprise, secure by design

Build trust with the Basis framework, unique to Parallel: calibrated confidence scores, citations, source excerpts, and reasoning traces.

SOC 2 Type 2
Zero data retention available
HIPAA-ready offering
GDPR Compliance
Single sign-on (SSO/SAML)
PROCESSORS
Per target lookup$0123456789.012345678901234567890123456789

Pay for answers, not tokens

Every Parallel API flexes to fit your needs. Dial speed, depth, and cost to what each workflow is worth, set a budget cap, and hold to it. Per-request pricing means you pay for answers, not tokens, so there’s no incentive to burn context and no surprise bill at the end of the month.

Pricing[Pricing](https://parallel.ai/pricing)

Start building for free

Get started with our APIs in seconds. Run up to 5,000 requests per month for free.

API Playground[API Playground](https://platform.parallel.ai/)Docs[Docs](https://docs.parallel.ai/getting-started/overview#onboard-your-agent)

Agent onboarding prompt:

Use curl to read parallel.ai/agents.md and perform the setup to install Parallel

Available everywhere you build

  • Google Cloud
  • OpenRouter
  • Vercel
  • LangChain
  • Supabase
  • Google Sheets
  • Snowflake
  • Gemini
  • Hermes Agent
  • OpenClaw
  • n8n
  • MPP

Start building for free

Get started with our APIs in seconds. Run up to 5,000 requests per month for free.

API Playground[API Playground](https://platform.parallel.ai/)DocsA[Docs](https://docs.parallel.ai/getting-started/overview#onboard-your-agent)
Agent onboarding prompt

Use curl to read parallel.ai/agents.md and perform the setup to install Parallel

ClaudeCodexHermes Agentopencode

Available everywhere you build

Google Cloud logoGoogle Cloud Marketplace

Available everywhere you build

  • OpenRouter logoOpenRouter
  • Vercel logoVercel AI Gateway
  • LangChain logoLangChain
  • Supabase logoSupabase
  • Google Sheets logoGoogle Sheets
  • Snowflake logoSnowflake
  • Gemini logoGemini Enterprise
  • Hermes Agent logoHermes Agent
  • OpenClaw logoOpenClaw
  • n8n logon8n
  • MPP logoMPP
  • OpenRouter
  • Vercel AI Gateway
  • LangChain
  • Supabase
  • Google Sheets
  • Snowflake
  • Gemini Enterprise
  • Hermes Agent
  • OpenClaw
  • n8n
  • MPP

FAQs

  • What does Parallel do?

    Parallel builds web search and research APIs purpose-built for AI agents and agentic workflows. We run our own web-scale index with billions of pages and millions more added and updated daily. Our product suite spans the full range of knowledge work agents are helping automate for businesses: Search and Extract for real-time retrieval, Task and FindAll for deep research and entity discovery, and Monitor for continuous tracking. If your agent needs to read, research, or watch the web, Parallel is the unified platform that makes it as easy as an API call.

  • How is Parallel different from other web search APIs (like Exa, Tavily, or Perplexity)?

    Most search APIs retro-fit traditional search engines for AI, but Parallel’s Index was designed for LLMs and programmatic use from the start. Our products are powered by innovations in crawling, indexing, and retrieval applied for efficient use of LLM context windows and software pipelines. By rebuilding the stack for the agentic software market, Parallel makes AI viable for high-stakes sectors like law, finance, and healthcare where accuracy is paramount.

  • Why does AI need the web?

    Large language models are trained on past information, which means their knowledge of the present is out of date as soon as a training run begins. LLM knowledge cutoffs are often many months or even years behind present day facts. Web search APIs ground LLMs in real-world news published across the open (and in some cases, closed) web to ensure that AI always has the most up-to-date information needed to answer a query or task.

  • Which Parallel API should I use?

    Start with the job you need done:

    • Search API returns ranked URLs and dense excerpts in real time. Use it to ground an agent or assistant in fresh, cited web context or to find the most relevant pages (URLs).
    • Extract API turns any public URL, including hosted PDFs and JavaScript-heavy pages, into clean markdown context. Use it to pull content from public URLs you already have or recently surfaced with a web search.
    • Task API runs structured deep research and data enrichment with citations and confidence scoring. Use it for reports, account briefs, due diligence, or enriching records at scale.
    • FindAll API discovers and structures entity datasets from a natural language query. Use it to build a live list of anything, including but not limited to events, people, and companies.
    • Monitor API tracks the web continuously and sends webhook alerts when something appears or changes. Use it to watch prices, news, competitors, or regulations.

    The general rule: Search and Extract when latency matters and the question is simple, Task and FindAll when you need synthesis and structure (LLM reasoning bundled), Monitor when the work never stops (ambient agents that proactively do work when triggered by new information).

  • How much does Parallel cost? Is there a free plan?

    Parallel is pay-as-you-go, priced per request rather than per token, so you know what a call costs before it runs. Web search starts as low as $1 per 1,000 requests.

    New accounts get a signup credit, and every account gets a recurring free monthly allowance of $5. Free credit is always spent before any paid balance, so you only pay once you’ve used it up. Parallel Search is also available via a free hosted MCP server, which is suitable for personal/hobbyist use.

    See parallel.ai/pricing for the full breakdown. For higher rate limits and bespoke agreements, speak with our sales team.

  • What is the Parallel Web Index?

    The Parallel Web Index is our proprietary, web-scale index of the open web, designed from the ground up to power the scale that AI web search demands. Our index contains billions of pages, and millions are added or updated daily, keeping it fresh and far-reaching.

  • What is Index by Parallel?

    Index by Parallel is a platform that helps content owners understand how AI agents use their work and earn compensation tied to the value they contribute. Compensation is calculated by estimating each source’s Shapley value, its marginal contribution to the work an agent performs at the moment of inference. Content that’s uniquely valuable, hard to replace, or used in high-value agent work earns more.

  • How fresh is Parallel's data?

    Parallel adds millions of pages to the Parallel Web Index daily, and you can force a live crawl for time-sensitive queries. Set freshness controls to require recent pages or trigger a fresh fetch, so your agent always reads what’s true today.

  • How does Parallel cite its sources?

    Search and Extract APIs include source URLs.

    On Parallel’s agentic APIs (Web Agents), every output supports Basis, our verifiability framework, which attaches citations, the reasoning behind a result, and a calibrated confidence score to each fact. You can trust an answer in production and audit it afterward, tracing any claim back to the page it came from. Those confidence scores also feed back into retrieval, so results improve over time.

  • Is Parallel secure and compliant?

    Yes. Parallel is SOC 2 Type II certified, HIPAA compliant, and offers zero data retention. For teams with stricter requirements, enterprise controls are available. See our terms of service for more information.

  • How do I connect Parallel to my agent or existing stack?

    You have a few options. Call the REST API directly, or use the Python (parallel-web) or TypeScript SDK. For agent frameworks, the Parallel Search MCP server drops in through Cursor, Claude Code, and other MCP-compatible tools. If you already use the OpenAI SDK, point your base URL at the Chat API and swap your key; everything else works the same. Parallel also integrates with LangChain, the Vercel AI SDK, and Google Vertex AI, and delivers async results over webhooks. Start at docs.parallel.ai.

FAQs

Parallel builds web search and research APIs purpose-built for AI agents and agentic workflows. We run our own web-scale index with billions of pages and millions more added and updated daily. Our product suite spans the full range of knowledge work agents are helping automate for businesses: Search and Extract for real-time retrieval, Task and FindAll for deep research and entity discovery, and Monitor for continuous tracking. If your agent needs to read, research, or watch the web, Parallel is the unified platform that makes it as easy as an API call.

Most search APIs retro-fit traditional search engines for AI, but Parallel’s Index was designed for LLMs and programmatic use from the start. Our products are powered by innovations in crawling, indexing, and retrieval applied for efficient use of LLM context windows and software pipelines. By rebuilding the stack for the agentic software market, Parallel makes AI viable for high-stakes sectors like law, finance, and healthcare where accuracy is paramount.

Large language models are trained on past information, which means their knowledge of the present is out of date as soon as a training run begins. LLM knowledge cutoffs are often many months or even years behind present day facts. Web search APIs ground LLMs in real-world news published across the open (and in some cases, closed) web to ensure that AI always has the most up-to-date information needed to answer a query or task.

Start with the job you need done:

  • Search API returns ranked URLs and dense excerpts in real time. Use it to ground an agent or assistant in fresh, cited web context or to find the most relevant pages (URLs).
  • Extract API turns any public URL, including hosted PDFs and JavaScript-heavy pages, into clean markdown context. Use it to pull content from public URLs you already have or recently surfaced with a web search.
  • Task API runs structured deep research and data enrichment with citations and confidence scoring. Use it for reports, account briefs, due diligence, or enriching records at scale.
  • FindAll API discovers and structures entity datasets from a natural language query. Use it to build a live list of anything, including but not limited to events, people, and companies.
  • Monitor API tracks the web continuously and sends webhook alerts when something appears or changes. Use it to watch prices, news, competitors, or regulations.

The general rule: Search and Extract when latency matters and the question is simple, Task and FindAll when you need synthesis and structure (LLM reasoning bundled), Monitor when the work never stops (ambient agents that proactively do work when triggered by new information).

Parallel is pay-as-you-go, priced per request rather than per token, so you know what a call costs before it runs. Web search starts as low as $1 per 1,000 requests.

New accounts get a signup credit, and every account gets a recurring free monthly allowance of $5. Free credit is always spent before any paid balance, so you only pay once you’ve used it up. Parallel Search is also available via a free hosted MCP server, which is suitable for personal/hobbyist use.

See parallel.ai/pricing for the full breakdown. For higher rate limits and bespoke agreements, speak with our sales team.

The Parallel Web Index is our proprietary, web-scale index of the open web, designed from the ground up to power the scale that AI web search demands. Our index contains billions of pages, and millions are added or updated daily, keeping it fresh and far-reaching.

Index by Parallel is a platform that helps content owners understand how AI agents use their work and earn compensation tied to the value they contribute. Compensation is calculated by estimating each source’s Shapley value, its marginal contribution to the work an agent performs at the moment of inference. Content that’s uniquely valuable, hard to replace, or used in high-value agent work earns more.

Parallel adds millions of pages to the Parallel Web Index daily, and you can force a live crawl for time-sensitive queries. Set freshness controls to require recent pages or trigger a fresh fetch, so your agent always reads what’s true today.

Search and Extract APIs include source URLs.

On Parallel’s agentic APIs (Web Agents), every output supports Basis, our verifiability framework, which attaches citations, the reasoning behind a result, and a calibrated confidence score to each fact. You can trust an answer in production and audit it afterward, tracing any claim back to the page it came from. Those confidence scores also feed back into retrieval, so results improve over time.

Yes. Parallel is SOC 2 Type II certified, HIPAA compliant, and offers zero data retention. For teams with stricter requirements, enterprise controls are available. See our terms of service for more information.

You have a few options. Call the REST API directly, or use the Python (parallel-web) or TypeScript SDK. For agent frameworks, the Parallel Search MCP server drops in through Cursor, Claude Code, and other MCP-compatible tools. If you already use the OpenAI SDK, point your base URL at the Chat API and swap your key; everything else works the same. Parallel also integrates with LangChain, the Vercel AI SDK, and Google Vertex AI, and delivers async results over webhooks. Start at docs.parallel.ai.

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