/technology

Production-ready web search API for AI agents

Give AI-powered products relevant, information-dense web context with fewer wasted tokens, controls to tune retrieval by workflow, and the flexibility to switch models without rebuilding search.

/use cases

Powering the agents behind modern software

  1. Customer-facing AI agents

    Customer-facing AI agents

    Build customer-facing agents that retrieve current, source-linked information for account research, legal drafting, threat investigation, and other product workflows.

    • Target specific sources, regions, and recent information
    • Give customers verifiable results they can review
    • Control when and how agents search the web
  2. AI assistants

    AI assistants

    Connect AI assistants to current web context, improving answers beyond model training data without maintaining your own search infrastructure.

    • Answer questions using current web information
    • Ground responses in content with source links
    • Support privacy requirements with Zero Data Retention
  3. Coding agents

    Coding agents

    Ground coding agents in current documentation, SDK references, and community discussions, so developers spend less time correcting outdated suggestions.

    • Retrieve the latest documentation and framework updates
    • Ground technical answers in source-cited context
    • Tune search depth, freshness, and result volume by task
  4. CRM enrichment

    CRM enrichment

    Retrieve current firmographics, ownership details, and public company information to fill CRM gaps and support more accurate account prioritization.

    • Enrich company and account records with current information
    • Identify parent, subsidiary, and ownership relationships
    • Verify firmographic data against external sources
  5. Competitive research

    Competitive research

    Give internal research agents current, source-backed information for competitive briefs, market reports, and product or positioning decisions.

    • Track competitor announcements, product changes, and market news
    • Focus research on relevant sources and time periods
    • Generate source-backed briefs for internal teams
  6. Model training

    Model training

    Supply live web retrieval for high-volume training workloads, helping research agents find relevant context with fewer repeated searches.

    • Generate research trajectories using live web data
    • Reduce irrelevant context and unnecessary search behavior
    • Use a consistent retrieval layer during training and deployment
/customer stories

Trusted by tech companies building AI products at scale

  • 99.8%

    retrieval success rate

    monday.com

    Powering web retrieval across monday.com's AI products

    monday.com uses Tavily for news monitoring, contact enrichment, and open-ended research across multiple AI products, with 99.8% of retrievals completing successfully.

    Read the monday.com story
  • 67K of 80K

    trajectories used to train Nemotron 3 Super

    NVIDIA

    Generating training data for NVIDIA's deep research agents

    NVIDIA used Tavily across approximately 80,000 research trajectories and retained approximately 67,000 to fine-tune Nemotron 3 Super.

    Read the NVIDIA story
  • Millions

    of requests a day

    Rox

    Powering real-time account intelligence for Rox

    Rox uses Tavily to bring fresh company news and web context into its revenue agents, supporting account intelligence and personalized outreach at scale.

    Read the Rox story
/capabilities

Why technology teams choose Tavily

answer quality

Give customers answers they can verify

Ground responses in current, relevant web evidence with source links, helping customers confirm results and reducing the time your team spends correcting poor outputs.

cost efficiency

Spend fewer tokens on irrelevant content

Send focused passages to your models instead of noisy pages, helping control inference costs as queries become more complex and product usage grows.

control

Improve retrieval for every workflow

Tune sources, freshness, search depth, and result volume to balance answer quality, speed, and cost for each product experience.

model-agnostic search

Adopt new models without rebuilding search

Preserve your search integration and retrieval controls as you change models or cloud platforms, making it easier to choose the best model for each product.

production readiness

Grow without building more search infrastructure

Scale AI products on a production-ready web search API with custom rate limits, enterprise SLAs, and dedicated support. Keep engineers focused on the product instead of retrieval infrastructure.

security

Protect customer data and reduce risk

Support enterprise requirements with Zero Data Retention, prompt-injection protection, malicious-source filtering, PII filtering, SOC 2 Type II, and ISO 27001.

/security

Reduce risk with built-in, enterprise-grade security

  • SOC 2
  • ZDR
  • GDPR
  • ISO 27001

/partners

Bring web retrieval to your existing AI stack

  • Databricks
  • Snowflake
  • LangChain
  • IBM
  • AWS
  • MongoDB

/faq

Frequently asked questions

Contact us

Built-in search is convenient for prototypes, but it ties retrieval to one provider and gives teams limited control over how agents search. Tavily provides an independent web search API with configurable sources, freshness, depth, and result volume.

Tavily ranks results and extracts focused passages, so models process less irrelevant content. Teams can also control when agents search and how much they retrieve, helping balance answer quality, latency, and cost for each workflow.

Yes. Tavily keeps web retrieval separate from the model, allowing teams to reuse the same search integration and controls across models and cloud platforms. You can switch models without rebuilding how your agents access the web.

Yes. Tavily supports production workloads with custom rate limits, enterprise SLAs, dedicated support, and security controls including Zero Data Retention, prompt-injection protection, PII filtering, SOC 2 Type II, and ISO/IEC 27001:2022.