Parallel Web Systems

"Agents don't just process information differently from humans; they break all of the business models that have existed on the web. Search ads, recommendation systems, AdSense, subscriptions by the seat. None of them work when agents use the web." Watch the full interview from Raise Summit 2026: https://lnkd.in/eKh4bGXa

In less than a year, Parallel has scaled from supporting hundreds of developers to tens of thousands. Along the way, we lost the "do things that don't scale" support instincts that helped us grow in the first place. But with AI, we could become proactive again. We built an internal tool called Customer Watch, an always-on background agent for Slack that lets us provide customer support before customers even realize they need it. Here's the stack: Pi.dev - agent harness Parallel Web Systems Monitor + Task APIs: real-time web data Attio - customer records Hex - product analytics Slack - where the agent interfaces with our team To learn more about the architecture and how to build it for your own customer support workflow, check out our blog: https://lnkd.in/eyzfwSz2

How are search engines built for AI different from the legacy search engines built for humans? Michael Jahr and Travers Nisbet discuss following the launch of Turbo mode for Parallel Search.

"All the business models that have been built on the web over the last three decades are about to change completely" Watch Parag Agrawal's full interview on Grit with Joubin Mirzadegan and Mamoon Hamid: YouTube: https://lnkd.in/dM8fVepJ Apple: https://apple.co/4hz6m7U Spotify: https://lnkd.in/dxDj96x3

Thank you to everyone who joined us tonight at OpenAI’s Builder Lounge. The evening kicked off with a talk from Akshat Agrawal on how we built the harness that powers our state-of-the-art web agents. Later, Marc Manara & Parag Agrawal sat down for a fireside chat and AMA with early stage founders building at the frontier. Keep an eye on our events page for the next one: https://lnkd.in/gTjk7-Nf

Enterprise vendor risk teams have a volume problem: too many vendors, too many public signals, and never enough analysts to read all of them. That's why continuous vendor risk monitoring has mostly stayed an enterprise privilege. We built a cookbook that shows how any company can run the same kind of program with AI agents, without hiring a research team. The system uses Parallel's Task API to build a baseline report on each vendor across six risk dimensions: financial health, legal and regulatory, operational resilience, leadership governance, ESG and reputation, and cybersecurity. Adverse events like breaches or lawsuits are tracked separately. A snapshot Monitor then watches the entire report for changes over time, so you catch a new signal in any dimension without writing a query for each one. When something changes, deterministic code, not the model, decides the risk level and whether it needs a human. Only changes that clear a configurable threshold trigger a deeper follow-up investigation. That means a small team can run and trust a vendor intelligence system, because every decision traces back to evidence and a rule you can read. Check it out: https://lnkd.in/edABQS6C

Introducing the Parallel Responses API. Turn any question into a synthesized answer, grounded in the live web, in seconds. Like the Task API, Responses returns answers to research or enrichment tasks with full citations and support for structured outputs. The difference is that Responses is significantly faster, purpose-built for latency-sensitive use cases. It’s also compatible with the OpenAI Responses standard. Switching to Parallel is a 3-line diff. Point the SDK at api.parallel.ai/v1, set model="parallel", and ask. The Responses API is live today. https://lnkd.in/ePA6_3hJ

Choosing the right search API for your agent shouldn't be hard. Parallel makes it easy. One Search API, three modes optimized to common needs: Turbo, Basic, and Advanced. Here's when to use each one.

Today, Cartesia and Parallel Web Systems are making it possible for your voice agents to search the web at conversational speed. Cartesia builds the fastest voice models available, and Turbo mode for Parallel Search extends that same low latency to web search. Together, they let an agent built on Cartesia query the live web and respond without interrupting the natural flow of conversation. Learn more 👇