Tavily

Nebius Group agreed to acquire Tavily for $275 million in February 2026. The acquisition will integrate Tavily's search capabilities into Nebius's AI cloud platform and Token Factory product.

Prior to the acquisition, Tavily raised $25 million in total funding. The company completed a $20 million Series A round in August 2025 led by Insight Partners and Alpha Wave Global, following a $5 million seed round in July 2024.

The acquisition price of $275 million represents roughly a 98x revenue multiple based on Tavily's 2025 revenue.

Tavily provides an API-first search engine for large language model workflows. Instead of returning traditional link-based results, it delivers pre-scraped, pre-ranked text chunks with citations that AI agents can consume.

A search endpoint accepts plain-English queries and returns structured data. For each query, Tavily reaches up to 20 websites in real time, crawls the pages, applies proprietary relevance scoring, and condenses each page into snippets under 500 characters.

Beyond search, Tavily offers extract capabilities for scraping known URLs, mapping functionality for discovering internal site links, crawl tools for traversing entire websites, and a research endpoint that orchestrates multiple searches into structured reports.

The platform integrates with AI development frameworks like LangChain and LlamaIndex through dedicated SDKs. Developers can fine-tune results with parameters such as search depth, topical filters for news or finance, time ranges, and domain allow/deny lists.

Tavily sells B2B SaaS API access on a credit-based consumption model. Developers buy monthly plans or pay-as-you-go credits, which are deducted per search request, extraction, or research operation.

The pricing structure ranges from a free tier with 100 monthly credits up to enterprise plans with custom credit pools. Basic searches cost 1 credit while advanced searches with deeper crawling cost 2 credits. The research endpoint, which orchestrates multiple searches, ranges from 4 to 250 credits depending on complexity.

As an asset-light aggregator, Tavily does not maintain its own search index, instead it fans out to multiple data sources and search engines in real time. This approach lowers infrastructure costs relative to models that build and maintain their own crawling operations.

Usage expands as customers’ AI agents scale their search activity. Enterprise customers often start with pilot projects and expand across multiple departments after internal ROI validation on automated research and data gathering workflows.

Exa operates a neural search index optimized for semantic relevance, charging $5 to $25 per 1,000 searches depending on depth. The company reached approximately $10 million ARR and raised $85 million at a $700 million valuation, positioning itself as a premium option with very low-token outputs and high recall on long-form documents.

Brave Search API leverages a 30 billion page independent index with AI plans starting at $5 per 1,000 requests. The company added AI Grounding capabilities in August 2025, combining multi-hop reasoning with citations to compete more directly with agent-focused search providers.

Perplexity offers both raw search results at $5 per 1,000 calls and integrated reasoning through its answer engine, which hit $100 million ARR by March 2025. The platform bundles models with search but competes with its own customers through its consumer interface.

Serper and SerpAPI focus on traditional SERP scraping and Google results formatting, typically pricing an order of magnitude cheaper than index owners but lacking the LLM-optimized outputs that AI agents require.

Searlo and similar providers offer basic web scraping capabilities but don't provide the real-time crawling, relevance scoring, and structured data formatting that makes Tavily particularly suited for autonomous agent workflows.

OpenAI's Responses API, Google Gemini's Grounding, and Microsoft Azure AI Agents bundle search directly into model and agent frameworks. These integrated approaches threaten to commoditize external search APIs by making web access a native platform feature rather than a third-party service.

The fully-managed research endpoint transforms Tavily from atomic search into higher-value synthesis work, enabling developers to spin up complete research agents in a single API call. This moves the company up-stack toward insight-level outputs that command higher pricing and opens use cases like competitive intelligence dashboards and automated due diligence reports.

Agent Skills library and native Vercel AI SDK plugins lower integration friction for TypeScript and Next.js developers, expanding Tavily's addressable market to the rapidly growing front-end AI builder community.

Fast and ultra-fast search modes target latency-sensitive applications like voice assistants, gaming, and algorithmic trading where every 100 milliseconds matters and traditional search APIs cannot compete on speed-for-LLMs.

The Nebius acquisition plugs Tavily directly into Nebius's AI cloud customer base, accelerating enterprise adoption through bundle pricing and one-click activation inside Token Factory. This provides immediate access to Microsoft and other large enterprise accounts already using Nebius infrastructure.

Marketplace integrations with IBM watsonx, AWS AgentCore, Snowflake, and Databricks position Tavily as the default retrieval layer inside enterprise AI stacks. This expands the total addressable market from independent developers to corporate IT budgets and multi-year enterprise contracts.

Fortune 500 references including IBM, Cohere, and Groq validate production readiness and create land-and-expand opportunities as successful agent projects spread across different departments within large organizations.

Nebius operates data centers across Europe, Latin America, and Asia-Pacific, enabling region-local endpoints that satisfy data residency requirements and reduce latency. This geographic footprint unlocks customers in regulated industries and markets where data sovereignty is critical.

The combined entity can offer localized search capabilities and compliance with regional regulations like GDPR, expanding beyond Tavily's current US and Israel operations into major international markets for AI development.

Platform dependency: Tavily's asset-light model relies on aggregated results from multiple search engines and data sources, creating exposure if major providers restrict access, raise prices, or change terms of service. Microsoft deprecated the public Bing Search API in August 2025, an example of rapid upstream change that can affect downstream services and competitive dynamics.

Model integration: Large language model providers like OpenAI, Google, and Microsoft are building search capabilities directly into their platforms, which could commoditize external search APIs. If native search becomes standard across major AI platforms, demand for Tavily as a third-party service could decline.

Margin compression: As an aggregator paying pass-through costs to data providers, Tavily faces pressure on gross margins if upstream source costs rise or if competition forces pricing down. Balancing pricing against margin requirements while paying licensing fees to multiple data sources remains a constraint.