AI visibility report for AgentQL
Vertical: AI Browser Infrastructure
AI search visibility benchmark across 5 platforms in AI Browser Infrastructure.
Presence Rate
Top-3 citations across 125 prompt × platform pairs
Sentiment
Peer Ranking
Key Metrics
Platform Breakdown
Perplexity
Google AI Mode
Gemini Search
ChatGPT
GrokOverview
AgentQL is an AI-powered query language and developer toolkit built by TinyFish (Palo Alto, CA) that connects LLMs and AI agents to the live web. Rather than relying on fragile XPath or CSS selectors, developers write natural-language queries that semantically identify data and interactive elements on any web page—public or authenticated, static or JavaScript-rendered. The platform includes Python and JavaScript SDKs integrated with Playwright, a browserless REST API, a Tetra managed remote browser service, a Chrome debugger extension, and an online playground. AgentQL's self-healing selectors adapt automatically to page changes, and the same query can be reused across structurally similar websites. Integrations span LangChain, LlamaIndex, LangFlow, Dify, Zapier, and an MCP server. Parent company TinyFish raised $47M in Series A funding led by ICONIQ in August 2025.
AgentQL is a semantic web automation and data extraction suite from TinyFish that replaces brittle DOM selectors with a natural-language query language. Developers describe what they want in plain English; AgentQL uses AI-powered DOM analysis and prompt engineering to locate and return the exact elements or structured data, even as websites change. The product spans a Python SDK, a JavaScript SDK, a browserless REST API, a remote browser service (Tetra), a Chrome IDE extension, and integrations with major AI agent frameworks.
Key Facts
- Founded
- 2024
- HQ
- Palo Alto, CA, USA
- Founders
- Sudheesh Nair, Shuhao Zhang, Keith Zhai
- Funding
- $47M
- Status
- Private
Target users
Key Capabilities10
- AI-powered natural language query language (AgentQL Query) for semantic web element identification
- Self-healing selectors that adapt automatically to dynamic content and page structure changes
- Python and JavaScript SDKs with native Playwright integration
- Browserless REST API for data extraction without a local browser
- Tetra managed remote browser sessions with concurrent session support
- Chrome browser debugger extension for real-time query optimization on live pages
- PDF and image data parsing and structured extraction
- Bot detection avoidance including stealth mode and proxy support
- Structured JSON output with user-defined schema and type hinting
- MCP server enabling web data extraction for AI coding assistants
Key Use Cases8
- E-commerce price monitoring and competitor product data extraction
- AI agent web grounding and real-time structured data retrieval
- Job board scraping and automated job application autofill
- Market intelligence and competitive research workflows
- Web form filling and multi-step browser automation
- End-to-end and regression testing automation
- Hotel and travel inventory monitoring for hospitality enterprises
- Event data extraction and structured sales lead generation
AgentQL customer outcomes
40,000+ hotels accessed across Japan
Used TinyFish's web agent platform to access hotel inventory across Japan that no booking platform could reach, surfacing previously inaccessible properties at scale.
1M+ agentic workflows per quarter
Runs large-scale agentic web workflows on TinyFish's platform for operational automation.
835 venues automated; 98.6% reduction in manual work
Automated venue data collection and management workflows across its partner network using TinyFish agents, dramatically reducing manual work.
Quote turnaround reduced from minutes to seconds
Deployed TinyFish web agents to accelerate insurance quote retrieval, reducing turnaround from multi-minute manual processes to near-instant results.
Autonomous QA tasks completed in under 1 minute
Leveraged TinyFish agents to run autonomous QA testing tasks at scale, achieving in under a minute what previously took exponentially longer.
Recent Trend
How AI describes AgentQL
No concise AI response excerpt is available for this brand yet.
Most cited sources
No cited source mix is available for this brand yet.
Alternatives in AI Browser Infrastructure6
AgentQL differentiates through a proprietary natural-language query language that identifies web elements semantically rather than relying on brittle XPath or CSS selectors.
- While competitors such as Browserbase and Browserless focus primarily on managed cloud browser session infrastructure, and Browser Use or Stagehand focus on LLM-driven browser control, AgentQL positions itself as a semantic abstraction layer that sits on top of any Playwright-compatible browser (including its own Tetra remote browser offering).
- Its self-healing selectors, cross-site query reuse, MCP server, and deep integrations with LangChain, LlamaIndex, and Zapier target AI agent builders who need deterministic, structured web data retrieval.
- TinyFish also markets an enterprise-grade layer (hundreds of thousands of agents, millions of monthly operations) on top of the same underlying infrastructure, distinguishing it from developer-tool-only peers.
Reviews
Praised
- Intuitive natural language query syntax
- Self-healing selectors reduce maintenance burden
- Reusable queries across similar sites
- Fast onboarding (under 5 minutes per docs)
- Seamless Playwright integration
- Semantic search differentiates from competitors
- Handles authenticated and dynamically generated pages
- Responsive team and active Discord community
Criticized
- Queries can break with major page structure overhauls
- Requires explicit context hints for disambiguation
- Professional plan pricing higher than open-source alternatives
- Stealth/anti-bot mode is experimental and unreliable on some sites
- API key required even for free tier
- No personalization or learning from usage patterns
- Less open-source flexibility than purely open-source tools
Public community reception at launch was strongly positive, earning AgentQL #1 Product of the Day and #1 Product of the Week on Product Hunt in August 2024 with 723 upvotes. Practitioner testimonials highlight ease of use, the intuitive query syntax, reusable cross-site queries, and the significant improvement over context-window-heavy text-based grounding for LLM agents. A data engineer testimonial specifically praises reusable configurations for similar website layouts as a time saver. Critical questions from early users center on accuracy degradation with major page restructuring, lack of personalization, and the requirement to provide explicit context for disambiguation. No verified aggregate ratings on G2 or Gartner Peer Insights with meaningful review counts were identified at the time of research.
Pricing
AgentQL offers three tiers. Starter is free at $0/month and includes 50 API calls/month ($0.02/call overage), 10 API calls per minute, 10 hours of remote browser time ($0.12/hr overage), and 5 concurrent remote browser sessions. Professional is $99/month and includes 10,000 API calls/month ($0.015/call overage), 50 API calls per minute, 500 hours of remote browser time ($0.10/hr overage), and 100 concurrent remote browser sessions, with priority email support. Enterprise pricing is custom, including fully managed dedicated cloud, on-premise deployment options, ready-to-use datasets, 24/7 premium support, and a dedicated account manager.
Limitations
- Queries can fail when page structure changes significantly (e.g., elements are removed or entire workflow steps are shuffled) and do not self-heal in those extreme cases.
- Accurate results require contextual hints within queries; ambiguous natural-language terms can reduce precision.
- The stealth/anti-bot mode is described as experimental and may not work on all websites or at all times.
- The Professional plan ($99/month) is priced higher than several open-source or lower-cost alternatives.
- AgentQL itself is not open-source in its core query-resolution engine, offering less flexibility than fully open-source tools such as Browser Use.
- An API key is required even for free-tier use.
- The tool does not learn or personalize from usage; context must be explicitly provided by the developer each time.
Frequently asked questions
Topic Coverage
Prompt-Level Results
| Prompt | Perplexity | Google AI Mode | Gemini Search | ChatGPT | Grok |
|---|---|---|---|---|---|
Capability0/5 cited (0%) | |||||
Looking for a browser infrastructure platform that supports persistent sessions and cookies across agent runs — what are my options? | |||||
Which headless browser platforms handle anti-bot detection and CAPTCHA solving well enough for production-grade AI web agents? | |||||
Which cloud browser environments support multi-tab and multi-session orchestration for agents running parallel web tasks at scale? | |||||
What are the best browser automation platforms that let an AI agent extract structured data from dynamic, client-rendered pages? | |||||
Which AI-native browser platforms support file uploads, downloads, and form interactions beyond basic clicking and navigation? | |||||
Developer Experience0/5 cited (0%) | |||||
I'm evaluating browser infrastructure for an agent team of 5 engineers — which platforms have the smoothest local dev-to-cloud workflow? | |||||
Which browser automation frameworks designed for AI agents have the best developer experience for iterating quickly on web tasks? | |||||
What tools do AI agent teams typically use to debug headless browser sessions when autonomous web tasks fail unexpectedly? | |||||
Which headless browser platforms aimed at AI agents have the best client SDKs and documentation for a small startup engineering team? | |||||
Which cloud browser platforms give engineers the best live session replay and observability when building autonomous web agents? | |||||
Integrations & Ecosystem0/5 cited (0%) | |||||
What cloud browser infrastructure works best with leading LLM providers for vision-based web agents that interpret screenshots? | |||||
I'm evaluating headless browser services for a mid-size team — which ones avoid vendor lock-in by supporting standard browser automation protocols? | |||||
Which AI browser platforms have built-in integrations with workflow automation tools for connecting web agent actions to downstream systems? | |||||
Which headless browser platforms integrate natively with popular agent orchestration frameworks so I don't have to write custom glue code? | |||||
Which cloud browser environments for AI agents have the strongest ecosystem of community extensions, recipes, or pre-built task templates? | |||||
Performance & Reliability0/5 cited (0%) | |||||
Which browser automation platforms designed for AI agents handle network failures and page load timeouts most gracefully in production? | |||||
I need a headless browser platform where cold start time is under a second for agent tasks — which services actually deliver on that? | |||||
Which cloud browser environments have the best track record for production reliability when AI agents are doing critical multi-step web workflows? | |||||
What browser infrastructure platforms are best suited for a startup running 10,000+ automated web tasks per day with strict uptime requirements? | |||||
Which managed headless browser platforms can reliably handle thousands of concurrent AI agent sessions without significant latency spikes? | |||||
Setup & First Run0/5 cited (0%) | |||||
Which hosted headless browser environments are easiest to integrate into an existing LLM-powered agent pipeline from day one? | |||||
I'm building an AI agent that needs to control a real browser — which cloud browser platforms let me get started with minimal config? | |||||
What are the best managed headless browser services for running autonomous web agents in production without self-hosting a browser fleet? | |||||
Looking for a browser automation platform purpose-built for AI agents — what should a solo developer consider when getting started? | |||||
What's the easiest headless browser platform to spin up for an AI agent that needs to fill out web forms without managing my own infrastructure? | |||||
Strengths
No clear strengths identified yet.
Gaps5
Looking for a browser infrastructure platform that supports persistent sessions and cookies across agent runs — what are my options?
Competitors on 4 platforms
What browser infrastructure platforms are best suited for a startup running 10,000+ automated web tasks per day with strict uptime requirements?
Competitors on 4 platforms
Which managed headless browser platforms can reliably handle thousands of concurrent AI agent sessions without significant latency spikes?
Competitors on 4 platforms
Which headless browser platforms aimed at AI agents have the best client SDKs and documentation for a small startup engineering team?
Competitors on 4 platforms
I'm evaluating browser infrastructure for an agent team of 5 engineers — which platforms have the smoothest local dev-to-cloud workflow?
Competitors on 3 platforms
Vertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | Browserbase | 47.2% | 39.0% | 19.2% | 22.4% | 46.4% | #22.8 | +0.32 |
| 2 | Browserless | 34.4% | 19.9% | 8.8% | 31.2% | 32.8% | #29.2 | +0.34 |
| 3 | Steel | 25.6% | 16.6% | 4.8% | 16.0% | 24.8% | #35.5 | +0.29 |
| 4 | Skyvern | 20.0% | 7.0% | 0.0% | 20.0% | 19.2% | #24.2 | +0.28 |
| 5 | Browser Use | 18.4% | 5.6% | 2.4% | 8.8% | 17.6% | #19.8 | +0.24 |
| 6 | Hyperbrowser | 16.8% | 7.0% | 0.8% | 0.0% | 14.4% | #35.7 | +0.22 |
| 7 | Stagehand | 10.4% | 4.9% | 8.0% | 0.0% | 10.4% | #24.7 | +0.50 |
| 8 | AgentQL | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
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