Parallel Web Systems has unveiled a groundbreaking API designed to redefine how AI systems interact with the deep web. The company announced that its platform is the first AI system to outperform both humans and leading models such as GPT-5 on rigorous benchmarks for deep web research. With its APIs now widely available, Parallel brings production-grade web intelligence directly into AI agents, enterprise applications, and critical workflows.
Already trusted by some of the fastest-growing AI companies and public enterprises, Parallel processes millions of research tasks every day. Startups and large organizations alike rely on its technology to embed web intelligence into their platforms. Public enterprises are automating traditionally human-driven workflows with accuracy that exceeds human-level performance, while coding agents leverage Parallel’s search capabilities to locate documentation and resolve issues efficiently.
A New Era of AI-Powered Web Research
Parallel’s API is enabling companies to reimagine how AI uses the web. Developers are building AI-driven sales agents that analyze leads, coding assistants that interpret technical documentation, and financial tools that surface insights from SEC filings. Insurance providers are streamlining claims processing with web-sourced verification powered by Parallel’s structured intelligence.
Also Read: NVIDIA Unveils Granary: An Open Multilingual Speech AI Dataset with High-Performance Canary and Parakeet Models
The platform offers key advantages for enterprises and AI developers, including:
-
Reduced hallucinations with verifiable outputs: Every result is paired with confidence ratings, reasoning chains, and source attribution. For example, a global BPO uses these capabilities to automatically route high-confidence insurance claims while sending edge cases for human review—boosting efficiency without sacrificing quality.
-
Flexible compute budgets: Organizations can allocate resources from cents to dollars depending on task value. This ensures predictable costs while maintaining quality. A private equity firm, for instance, can fund deep market analysis while sales teams enrich CRM records at scale for minimal cost.
-
Machine-ready, structured data: Unlike traditional search, outputs are delivered in customizable schemas. Customers have already transformed the web into proprietary databases, while coding agents integrate API documentation directly into their environments.
-
Declarative interfaces for efficiency: Agents specify what they need rather than how to find it. For instance, an AI analyst might request “a market map of the top 50 global semiconductor ecosystem players beyond chip designers and fabs,” and Parallel’s infrastructure handles the rest.
Unlocking the Next Frontier
Parallel’s vision extends beyond today’s applications. The company is actively building capabilities to support long-horizon agents that can complete the work of entire teams in hours, continuous monitoring systems for real-time insights, event-driven architectures that react to web changes, and SQL-style programmatic queries over the web. Future APIs will not only read the web but also write to it, unlocking a new era of programmable intelligence.
A Web Built for AI
“At Parallel, we’re creating the interfaces, infrastructure, and economic models for AI agents to thrive on the open web. Our API is the first step toward that vision.”
The company’s founding team brings deep expertise from their work building the infrastructure and markets at Twitter, early Google, Stripe, Airbnb, and Chime, as well as applied machine learning at Waymo and Kitty Hawk. Parallel is backed by Khosla Ventures, First Round Capital, Index Ventures, Terrain, and several visionary angel investors who share its mission to design the future of the web for AI.