Tavily is live · free plan, paid from $30/mo · last verified 9 Nov 2026 · viability healthy
Tavily
A web search API that grounds AI agents with live, structured web context
For production agent teams, Tavily is the search API we would prototype first. The 99.99% SLA, 180 ms p50, and inline PII and prompt-injection filtering are work you would otherwise build and maintain in-house. The NVIDIA post-training case and the October 2026 benchmark back it up on real workloads rather than demos.
Verdict generatedVerified 4d ago · liveness 88/100 · cite: rightaichoice.com/tools/tavily
- AI agent teams needing live web facts to cut hallucination
- Production teams that require a documented SLA and p50 latency
- Developers consolidating search, extract, crawl, map, and research into one API
- Regulated enterprises that must block PII leakage and prompt injection at retrieval
- SEO teams wanting Google-style SERP layouts or rank tracking
- Hobby projects that can't absorb per-request credits on top of LLM inference
- Workflows that depend on extracting personal data — the PII filter blocks those queries
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Skip Tavily if you need a human-readable search UI with SERP layouts and rank tracking rather than an API that feeds chunks into your own agent.
Credits reset on the first of the month regardless of your billing date, so heavy usage late in a cycle can leave you out of requests until the 1st
Pricing scales from a 1,000-credit free tier to $0.008/credit pay-as-you-go to $30/mo for 4,000 credits, with a startup program granting 100k free credits and custom Enterprise contracts. That fits seed-to-Series-B agent teams and enterprise pilots alike. Compare against building retrieval in-house (an engineer plus a proxy bill) or against bundled search in a model provider's API, which is cheaper per call but narrower on crawl, map, and safety filtering.
In short
Tavily — A web search API that grounds AI agents with live, structured web context. Best for AI agent teams needing live web facts to cut hallucination, Production teams that require a documented SLA and p50 latency, Developers consolidating search, extract, crawl, map, and research into one API. Free to start; paid plans from $30/mo.
What is Tavily?
Tavily — A web search API that grounds AI agents with live, structured web context. Best for AI agent teams needing live web facts to cut hallucination, Production teams that require a documented SLA and p50 latency, Developers consolidating search, extract, crawl, map, and research into one API. Free to start; paid plans from $30/mo.
Tavily is the web access layer for AI agents: one API that returns live web results already cleaned, chunked, and formatted so a model can reason over them without hallucinating. Endpoints cover the full retrieval loop — /search for real-time results, /extract for readable content from a URL, /crawl and /map to pull or discover whole sites, and /research for a multi-step agent pass over the open web. The customer list leans on grounded accuracy: JetBrains reports description accuracy moving from 20% to 100%, and Ocean runs roughly one billion monthly investigations on the API. The vendor publishes the operating numbers a platform team checks before shipping: 3M+ developers, 300M+ monthly requests, 180 ms p50 on /search, and a 99.99% uptime SLA. Requests pass through security, privacy, and content-validation layers — an email in a query comes back as a PII-detected error, and prompt injection plus malicious sources are filtered. Integration is not an afterthought: SDKs for Python, Node, Go, Rust, and Java, drop-in connectors for OpenAI, Anthropic, and Groq, plus LangChain, Databricks, IBM watsonx, Nebius, JetBrains, and the MCP ecosystem. In October 2026 Tavily published a Company Search Benchmark built on real agent tasks and placed itself first among nine providers. That makes it a fit for teams building research agents, fact-checking pipelines, or vertical retrieval products that need documented latency and safety at the retrieval layer. It is not a Google-SERP replacement for SEO teams, and credits stack on top of your LLM inference bill, so model the math before committing.
Key features
- Real-time web search API (/search) for AI agents
- Structured, chunked content output sized for LLM ingestion
- Content extraction and cleaning (/extract) for models
- Whole-website crawling (/crawl)
- URL discovery across any site (/map)
- /research agent for multi-step in-depth web research
- Built-in PII detection that blocks queries containing personal data
- Prompt injection and malicious source filtering
- Drop-in connectors for OpenAI, Anthropic, and Groq
- SDKs for Python, Node, Go, Rust, and Java
- MCP-compatible API for agent frameworks
- Intelligent caching and indexing for predictable latency
- 180 ms p50 latency on /search
- 99.99% uptime SLA
- Free API access for students
Behind the verdict
Retrieval is where most agent prototypes quietly break. A model that mocks up a plausible answer from stale training data is worse than one that says it doesn't know, and plugging in a raw SERP API leaves you parsing HTML and fighting boilerplate. Tavily's pitch is that the cleaning, chunking, and filtering happen before the text reaches your model — and in practice that is the part teams underestimate when costing out a build. Pick it when you are shipping to production and need paperwork-grade numbers: a 99.99% SLA and a published 180 ms p50 on /search are things a platform review will ask for, and few search vendors put them on the homepage. The inline PII block is another quiet win — one less thing to bolt on yourself if compliance is watching. Pass if your workload is low-volume exploration where per-request credits on top of inference make the math ugly, or if your use case genuinely needs to surface personal data that the filter will block. SEO teams looking for rank tracking or SERP layouts should look elsewhere entirely; that is not the product. The closest alternative is Claude's native web search, which Tavily itself compared against in October 2026. Built-in search wins on setup effort and keeps everything in one vendor; Tavily wins when you want retrieval you can tune, log, and swap under a model-agnostic stack. If you are already locked to one model provider, the native option is worth trying before you add a second bill. Watch the customer stories for caveats rather than the benchmark. Tavily's Company Search result is self-published on its own dataset — useful, not neutral. The third-party proof points carry more weight: NVIDIA post-training deep research agents on the API and JetBrains going from 20% to 100% description accuracy.
Models under the hood
as of 2026-11-07
Limitations
- Tavily is a web access API for agents, not a general-purpose search interface — there is no SERP-style UI or rank tracking.
- Usage is metered in API credits: the free Researcher tier includes 1,000 credits per month, Pay As You Go is $0.008 per credit, and Project is $30/mo for 4,000 credits.
- Credits reset on the first day of each month regardless of billing date, and once you exhaust them requests stop until reset or upgrade.
- Credit consumption varies by request type — search, extract, crawl, and research burn different amounts, with higher-volume or advanced requests using more — so budget forecasting requires the docs.
- The PII filter blocks queries containing personal data by design, which rules out that class of workflow.
- The sources name no underlying generative model for the /research agent.
as of 2026-10-21
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Is Tavily still active?
Tavily is live · free plan, paid from $30/mo · last verified 9 Nov 2026 · viability healthy.
Viability score
How well maintained and how widely used is Tavily? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What's new in Tavily
Checked 12 days agoAcross the latest 6 updates: 6 news mentions.
How Astelia Uses Tavily for Vulnerability Analysis at the Speed of Disclosure
Tavily customer story: Astelia uses the search API for vulnerability analysis at the speed of disclosure.
Three Steps to Build Production-Ready AI Agents for Financial Services
Tavily posted a three-step guide to building production-ready AI agents for financial services.
Understanding the Role of Context Management in RL Post-Training
Tavily research post on context management in reinforcement learning post-training.
World of Tavily: Where We Started, Where We're Going
Tavily company post covering its history and product direction.
Inside Ocean's One Billion Monthly Investigations with Tavily
Tavily customer story on Ocean running one billion monthly investigations with the API.
Tavily Introduces Company Search Benchmark, Ranks First of 9 Providers
Tavily released a Company Search Benchmark built on real agent tasks and says it ranks first among the 9 evaluated providers.
What do users say about Tavily?
What people actually say about Tavily — is it worth it?
We scanned public community sources for Tavily on Sep 29, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 2 of the posts we fetched could be positively tied to Tavily. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
How we verified this
Every listed fact about Tavily — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 9 Nov 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified Tavily 22 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed pricing page
- — changed GitHub stars, features, description, summary, pricing tiers, our verdict
- — changed pricing page
- — changed pricing tiers, our verdict, summary, GitHub stars, description, integrations
- — changed platforms, pricing page
- — changed who it suits, description, our verdict, features, hidden costs, integrations, limitations, switching in, switching out, who should skip it, pricing fit, setup time, summary, use cases
Showing the 6 most recent of 22 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Tavily cost in 2026?
Tavily: Free to start; paid plans from $30/mo. Pricing last verified 9 Nov 2026.
Plans compared
Every published Tavily tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Researcher Free | Free | — | Solo developer or student prototyping an agent who needs a working search endpoint without a card on fileAdds: Starting tier: 1,000 API credits per month, no credit card required, email support |
| Pay As You Go | $0.008/credit | usage | Small teams with spiky or unpredictable agent traffic who don't want a fixed monthly credit blockAdds: Adds metered billing at $0.008 per credit with cancel-anytime flexibility instead of a fixed monthly quota |
| Project | $30/mo | monthly | A production agent team running steady traffic that needs higher rate limits and a predictable 4,000-credit blockAdds: $30/mo (adjustable via a plan slider) for 4,000 credits per month and higher rate limits than the free tier |
| Enterprise | Custom | quote | Corporations that need custom volume, custom rate limits, and contractual SLAs and security termsAdds: Adds custom API call volume, custom rate limits, enterprise-grade support and SLAs, and enterprise security and privacy |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Tavily's pricing actually pencils out — and where peers do it cheaper.
Pricing scales from a 1,000-credit free tier to $0.008/credit pay-as-you-go to $30/mo for 4,000 credits, with a startup program granting 100k free credits and custom Enterprise contracts. That fits seed-to-Series-B agent teams and enterprise pilots alike. Compare against building retrieval in-house (an engineer plus a proxy bill) or against bundled search in a model provider's API, which is cheaper per call but narrower on crawl, map, and safety filtering.
Has Tavily's pricing changed?
No plan price for Tavily has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Tavily?
Pick Tavily if you are AI agent teams needing live web facts to cut hallucination, Production teams that require a documented SLA and p50 latency, Developers consolidating search, extract, crawl, map, and research into one API, Regulated enterprises that must block PII leakage and prompt injection at retrieval.
Look elsewhere if you are SEO teams wanting Google-style SERP layouts or rank tracking, Hobby projects that can't absorb per-request credits on top of LLM inference, Workflows that depend on extracting personal data — the PII filter blocks those queries, Questions a model can answer from its own training data without retrieval.
Skip it if Skip Tavily if you need a human-readable search UI with SERP layouts and rank tracking rather than an API that feeds chunks into your own agent.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Tavily actually fits — and what changes day-one when you adopt it.
You swap a hand-rolled scraper for /search and /extract, send queries through the PII and prompt-injection filters, and cache results to hold latency steady as traffic grows.
Outcome: Agents reason over fresh, chunked web facts with 180 ms p50 on /search and a 99.99% SLA behind the endpoint.
You call /research for multi-step web passes and /map to discover URLs across a source site, then feed the cleaned output into your existing OpenAI or Anthropic pipeline.
Outcome: A research assistant that cites live sources instead of reciting training data, built without a second vendor.
You point /search and /extract at company and news sources to speed AML screening research, the same step BMO automated.
Outcome: Screening research that runs in minutes rather than days, with PII filtering enforced at the retrieval layer.
Use cases
- Grounding AI agents in fresh web data so they stop hallucinating library methods and facts
- Building a research assistant that pulls and summarizes recent news on demand
- Automating competitive intelligence by crawling and extracting specific company sites
- Powering a Q&A chatbot that answers from live web results instead of stale training data
- Feeding a RAG knowledge base with cleaned, chunked web content
- Giving coding agents like JetBrains Junie up-to-date documentation at request time
- Speeding AML screening research, as BMO did for its slowest screening step
- Adding first-class web search to an open-source agent framework like IBM CUGA
Setup time & first value
How long it actually takes to get something useful out of Tavily — broken out by persona, not the marketing-page minute.
Grab an API key from the dashboard after a free signup (no credit card), then drop the Python or JavaScript SDK in and make a first /search call — a working retrieval loop in well under an hour. Wiring /crawl and /research into an existing agent takes longer, since credit consumption differs per endpoint.
Switching to or from Tavily
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a raw SERP API: replace the results parser with /search, which returns content already chunked for a model.
- →From a hand-rolled scraper: move URL fetches to /extract and site sweeps to /crawl and /map.
- →From a model provider's built-in search: keep the model and route retrieval through Tavily for crawl, map, and safety filtering.
- →From LangChain's default retriever: swap in the Tavily connector and keep the chain unchanged.
- ↗To a model provider's native search: drop the retrieval endpoint and rely on built-in grounding, accepting narrower crawl and map coverage.
- ↗To a self-hosted scraper stack: rebuild extraction and caching in-house, plus your own PII and prompt-injection filters.
- ↗To a raw SERP API: lose the structured chunking and re-add content cleaning downstream.
Resources & guides
- Resourcetavily.com
Tavily
Tavily is the real‑time search engine for AI agents and RAG workflows — Fast and secure APIs for web search and content extraction.
- Resourcetavily.com
Tavily
Tavily is the real‑time search engine for AI agents and RAG workflows — Fast and secure APIs for web search and content extraction.
- Resourcetavily.com
Tavily
Tavily is the real‑time search engine for AI agents and RAG workflows — Fast and secure APIs for web search and content extraction.
Tutorials & Learning
YouTube returned 6 videos for “Tavily”, and we withheld 6: 6 could not be judged, because “Tavily” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Tavily.
What are the best Tavily alternatives?
The closest alternatives to Tavily we list are The Hog, Firecrawl and Linkup. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| The Hog | Freemium | Pricing not published | — |
| Firecrawl | Freemium | Pricing not published | — |
| Linkup | Paid | Pricing not published | — |
Alternatives to Tavily
View all
Tools that pair well with Tavily
Common stack mates teams adopt alongside Tavily, with the specific reason each pairing earns its keep.
The Hog
The Hog is a web intelligence API that turns live web signals into structured context for AI agents.
Firecrawl
Firecrawl is a web data API that scrapes, searches, and interacts with live pages to feed LLM-ready Markdown and JSON into AI agents.
Linkup
Linkup is a web search API that gives AI agents sourced, cited answers from the live web.
Tavily vs its closest rival
Tavily's closest head-to-head is with Crawl4ai.
Our Tavily vs Crawl4ai verdict written May 12, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
Head-to-head comparisons
Crawl4ai vs Tavily
Verdict being re-reviewed against current pricing and data.
Firecrawl vs Tavily
Verdict being re-reviewed against current pricing and data.
Exa vs Tavily
Verdict being re-reviewed against current pricing and data.
Perplexity vs Tavily
Choose Tavily if you are a developer building AI agents that need fast, reliable web search with security filters at scale, or want to experiment with autonomous payments via x402. Choose Perplexity if you are an individual researcher, student, or professional who needs cited answers with source transparency and a clean GUI. Tavily is an API; Perplexity is a consumer product — they serve different use cases.
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