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Parallel
Parallel, the company formally named Parallel Web Systems, builds web search, extraction, and deep research APIs for AI agents, priced per request, and counts Harvey, Notion, Replit, and Pfizer among its users.
Engineering teams at AI startups and enterprises that need agents to search, read, and research the open web with citations, and that want to trade speed against depth request by request.
Teams that only need a cheap keyword search API, and buyers who run heavy deep research at its top tiers, where costs climb quickly.
Verdict
Parallel offers one of the widest sets of web APIs for agents we have reviewed, from $1-per-thousand search calls to multi-minute research tasks, and its customer quotes point to strong accuracy on hard queries. Pricing is pay-as-you-go, with up to 5,000 free requests a month, but the top research tiers run from $300 to $2,400 per thousand tasks. The company is young and well funded after a $100 million Series B, and for agent builders it earns a clear recommendation.
Score Breakdown
These scores cover how accurate and well cited Parallel's research results are, how broad its set of APIs is, how well its speed options suit live agents, and how predictable its costs are at high tiers, and then how it does as a company on innovation, communication, pricing, and contract terms.
Who Uses Parallel, Where It Fits on Price, and Its Competitors
Parallel lists Harvey, Notion, Replit, Lovable, Granola, LangChain, Modal, Pfizer, and Rogo among its users, and its customers mostly build AI agents for legal, finance, sales, and coding work. Its APIs cover search, page extraction, multi-step research tasks, entity discovery (FindAll), web monitoring, and a chat-style Responses API, and buyers pick a processor tier for each call to balance speed, depth, and cost. Parallel was founded in 2023 by Parag Agrawal, holds a SOC 2 Type II report, and offers zero data retention for enterprises.
On price, Parallel is usage-based. Search starts at $1 per thousand requests, extraction is $1 per thousand pages, and research tasks run from $5 to $2,400 per thousand depending on the tier. Its closest competitors are Firecrawl, Exa, Linkup, and Valyu.
Pricing
We checked Parallel's pricing page and recorded its main APIs. All are pay-as-you-go, with up to 5,000 free requests a month.
| Plan | Price | What stands out |
|---|---|---|
| Search API | $1 to $5 per 1,000 requests | Ten results per request, with Turbo and Fast modes at $1 and Basic and Advanced at $5. |
| Extract API | $1 per 1,000 pages | Clean page content for agents to read. |
| Task API | $5 to $2,400 per 1,000 tasks | Nine processor tiers, from Lite at $5 and Core at $25 to Ultra at $300 and Ultra8x at $2,400. |
| Enterprise | Custom | Zero data retention, a data processing agreement, single sign-on, and custom rate limits. |
The Field at a Glance
How Parallel compares with other AI web search API vendors we reviewed, by Overall Score and relative typical engagement cost.
Parallel scores 7.9 in AI web search APIs, level with Firecrawl (7.9), and ahead of Exa (7.7), Linkup (7.5), and Valyu (7.2).
How Well Parallel Fits Each Web Search API Use Case
We rated Parallel against the situations teams bring to a web search API, drawing on its pricing and customer pages and its Series B announcement.
| Use case | Fit | Notes |
|---|---|---|
| Deep research with citations | Strong | Higher Task tiers run multi-step research and return cited answers. |
| Fast search inside live agents | Strong | Turbo and Fast search modes cost $1 per thousand requests and suit chat agents. |
| Hard-to-reach sources | Strong | Harvey uses Parallel for legal data on sites ordinary search engines do not index. |
| Monitoring pages over time | Strong | The Monitor API tracks changes on the web and sends alerts. |
| High-volume deep research | Mixed | Ultra tiers cost $300 to $2,400 per thousand tasks, so heavy use needs careful budgeting. |
| Simple keyword search | Mixed | Cheaper basic search APIs exist for teams that do not need research depth. |
Review Excerpts
These excerpts come from customer quotes Parallel publishes on its site, which the company chose, and from the buyer concern we found in its pricing and public developer discussion. Paid reviews and pay-for-play sites were excluded.
“In our internal evaluations we found Parallel to be the fastest and most accurate web search tool we tested.”
“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.”
“Results at the Ultra tiers are excellent, but at $300 per thousand tasks and up, we had to cap which agent steps get deep research or the bill ran ahead of us.”
Representative buyer view
Where customer reviews couldn't be found, our analysts attempted to give a voice to buyer sentiment, drawing on real information from review sites, forums, and product documentation.
Based on: Parallel pricing and Parallel's Series B announcement
Company Facts
- Founder
- Parag Agrawal (CEO) (Parallel)
- Founded
- 2023 (Parallel)
- Headquarters
- Palo Alto, California (PR Newswire)
- Funding
- $230 million in total, including a $100 million Series B led by Sequoia at a $2 billion valuation in April 2026 (PR Newswire)
- Security
- SOC 2 Type II, with zero data retention available for enterprises (Parallel)
- Website
- parallel.ai
Key Leadership
Parag Agrawal
Founder and CEO
He founded Parallel in 2023 after serving as CTO and then CEO of Twitter (WSJ).
Methodology
We scored Parallel on eight criteria, from research accuracy and citations to contract fairness, and the Overall Score is their simple average on a 0 to 10 scale. The scores draw on reviews from public review sites and forums, with paid reviews and pay-for-play sites excluded, plus a hands-on look at the product, its pricing, and its documentation and training. Scores can change as we add reviews and product checks.