Who is AgentQL best for?

AgentQL is built for Software developers building AI agents and browser automation pipelines, Data engineers running large-scale web scraping and extraction workflows, Enterprise automation and RPA teams in hospitality, e-commerce, and transportation, AI/ML researchers and product teams needing real-time structured web data. Common use cases include 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.

How is AgentQL priced?

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.

What are the alternatives to AgentQL?

Common AI Browser Infrastructure alternatives to AgentQL include Browserbase, Browserless, Steel, Browser Use, Hyperbrowser. See the full comparison hub at /verticals/ai-browser-infrastructure/compare.

What do users praise about AgentQL?

Users frequently praise: 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.

What are common complaints about AgentQL?

Frequently cited limitations: 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.

When was AgentQL founded and where?

AgentQL was founded in 2024, headquartered in Palo Alto, CA, USA by Sudheesh Nair, Shuhao Zhang, Keith Zhai.

AI visibility report

AI visibility report for AgentQL in AI Browser Infrastructure.

Outside the top three on 25 of the 25 prompts buyers actually ask.

Browserbase is cited on 23 of those losses.

25 prompts

6 platforms

Updated Aug 14, 2026 - refreshed weekly

Track AgentQL daily

Free trial. Setup comes pre-filled for AgentQL.

Track AgentQL across these prompts daily.

Start free trial

0percent

Presence Rate

Low presence

Still absent from 100% of tracked prompt responses

Top-3 citations across 150 prompt × platform pairs

N/A

Sentiment

-1.00.0+1.0

Unknown

No clearrank

Peer Ranking

#1#8

No clear rankin AI Browser Infrastructure

Key Metrics

Presence Rate

0.0%

Share of Voice

0.0%

Avg Position

N/A

Docs Presence

0.0%

Blog Presence

0.0%

Brand Mentions

0.7%

Platform Breakdown

Google AI Mode

0%0/25 prompts

Gemini Search

Research dossierCapabilities, use cases, sources, reviews, pricing, and FAQ

Overview

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.

AI visibility report

AI visibility report for AgentQL in AI Browser Infrastructure.

Outside the top three on 25 of the 25 prompts buyers actually ask.

Browserbase is cited on 23 of those losses.

25 prompts

6 platforms

Updated Aug 14, 2026 - refreshed weekly

Track AgentQL daily

Free trial. Setup comes pre-filled for AgentQL.

Track AgentQL across these prompts daily.

Start free trial

0percent

Presence Rate

Low presence

Still absent from 100% of tracked prompt responses

Top-3 citations across 150 prompt × platform pairs

N/A

Sentiment

-1.00.0+1.0

Unknown

No clearrank

Peer Ranking

#1#8

No clear rankin AI Browser Infrastructure

Key Metrics

Presence Rate

0.0%

Share of Voice

0.0%

Avg Position

N/A

Docs Presence

0.0%

Blog Presence

0.0%

Brand Mentions

0.7%

Platform Breakdown

Google AI Mode

0%0/25 prompts

Gemini Search

Research dossierCapabilities, use cases, sources, reviews, pricing, and FAQ

Overview

Reviews

1/5Product Hunt·1+

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.

Prompt	Google AI Mode	Gemini Search	ChatGPT	Bing Copilot	Perplexity	Grok
Capability0/5 cited (0%)
Which headless browser platforms handle anti-bot detection and CAPTCHA solving well enough for production-grade AI web agents?	A competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited	A competitor was cited
Which cloud browser environments support multi-tab and multi-session orchestration for agents running parallel web tasks at scale?

#	Brand	PresencePres.	Share of VoiceSoV	DocsDocs	BlogBlog	MentionsMent.	Avg PosPos	Sentiment
1	Browserbase	42.0%	33.1%	19.3%	18.0%	80.0%	#23.2	+0.43
2	Browserless	33.3%	24.2%	14.7%	18.0%	48.7%	#24.5	+0.39
3	Steel	31.3%	20.2%	6.7%	10.0%	52.7%	#20.9	+0.46
4	Browser Use	17.3%	6.4%	4.0%	2.7%	37.3%	#16.1	+0.46
5	Hyperbrowser	15.3%	8.4%	0.0%	0.0%	30.0%	#15.4	+0.52
6	Skyvern	12.7%	4.7%	0.0%	12.0%	20.7%	#32.3	+0.23
7	Stagehand	5.3%	3.0%	4.7%	0.0%	50.0%	#34.8	+0.40
8	AgentQL	0.0%	0.0%	0.0%	0.0%	0.7%	—	—

Developer Experience0/5 cited (0%)
Which cloud browser platforms give engineers the best live session replay and observability when building autonomous web agents?	Neither your brand nor a competitor was cited	A competitor was cited	A competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited	A competitor was cited

Integrations & Ecosystem0/5 cited (0%)
Which AI browser platforms have built-in integrations with workflow automation tools for connecting web agent actions to downstream systems?	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited	A competitor was cited

Performance & Reliability0/5 cited (0%)
Which managed headless browser platforms can reliably handle thousands of concurrent AI agent sessions without significant latency spikes?	A competitor was cited	A competitor was cited	A competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited	A competitor was cited

AI visibility report for AgentQL in AI Browser Infrastructure.

Key Metrics

Platform Breakdown

Overview

AI visibility report for AgentQL in AI Browser Infrastructure.

Key Metrics

Platform Breakdown

Overview

Prompts where competitors are visible and AgentQL is not.

Where AgentQL is winning

Where AgentQL is losing5

Key Facts

Key Capabilities10

Key Use Cases8

AgentQL customer outcomes

Recent Trend

How AI describes AgentQL1

Most cited sources

Alternatives in AI Browser Infrastructure6

Reviews

Pricing

Limitations

Topic Coverage

Prompt-Level Results

Vertical Ranking

Turn this into your team dashboard

Frequently asked questions

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?	Neither your brand nor a competitor was cited	Neither your brand nor a competitor was cited	A competitor was cited	A competitor was cited	A competitor was cited	A competitor was cited

AI visibility report for AgentQL in AI Browser Infrastructure.

Key Metrics

Platform Breakdown

Overview

AI visibility report for AgentQL in AI Browser Infrastructure.

Key Metrics

Platform Breakdown

Overview

Prompts where competitors are visible and AgentQL is not.

Where AgentQL is winning

Where AgentQL is losing5

Key Facts

Key Capabilities10

Key Use Cases8

AgentQL customer outcomes

Recent Trend

How AI describes AgentQL1

Most cited sources

Alternatives in AI Browser Infrastructure6

Reviews

Pricing

Limitations

Topic Coverage

Prompt-Level Results

Vertical Ranking

Turn this into your team dashboard

Frequently asked questions

What does AgentQL do?

Who is AgentQL best for?

How is AgentQL priced?

What are the alternatives to AgentQL?

What do users praise about AgentQL?

What are common complaints about AgentQL?

When was AgentQL founded and where?