Octen is a real-time web search platform that redesigns the search engine for AI agents and LLMs rather than for human readers. A single API key gives you Broad Search, which automatically splits one question into many sub-queries and searches them in parallel; Extract, which turns any URL into structured data; in-house embedding models; and a Model Gateway that calls multiple LLMs through one interface. It launched officially in March 2026 and plugs directly into development environments such as Claude Code, Cursor, LangChain and LlamaIndex as an MCP server, CLI or Skill. The service is operated by Octen Inc., based in the United States.
Key Features
- Web Search API: Returns ranked results and highlights in a shape that LLMs can consume easily, with low latency. Full page content is included at no extra charge for up to 10 results per call
- Broad Search: Automatically breaks one question into many sub-queries, searches them in parallel and aggregates the results. The API takes over the “investigate a topic from several angles” pattern for you
- Extract: Converts any URL into clean Markdown, adding intent-based highlights and page classification. You no longer need to write your own scraping and main-text extraction
- Embedding / VL Embedding: Provides in-house text and multimodal embedding models over the API, so search and similarity computation can stay on the same platform
- Model Gateway: Gives single-API access to major LLMs and multimodal models. You can run inference with search results built in, and part of your spend is returned as monthly credit
- Application layer: Answer, Deep Research, Multimodal Chat and Grounded Generation are available. Of these, image and video search, Multimodal Chat and Grounded Generation are in Early Access
Pricing
The basis is pay-as-you-go with no fixed base fee. New sign-ups automatically receive $5 in free credit, so you can try it without an upfront cost.
| Feature | Indicative price |
|---|---|
| Web Search | $1–$5 / 1,000 calls |
| Broad Search | $1–$5 / 1,000 sub-queries |
| Extract | $1 / 1,000 URLs |
| Embedding | $0.01–$0.07 / 1M tokens |
| VL Embedding | $0.05–$0.25 / 1M tokens |
| Deep Research | $0.20–$3.00 / request |
| Grounded Generation | $0.25–$1.00 / output |
If you want to reserve search throughput (QPS), you add a QPS Plan, which is billed separately from usage credit.
| QPS Plan | Monthly | Max QPS |
|---|---|---|
| Free | $0 | Up to 20 QPS (10 QPS initially) |
| Builder | $2,099 | Up to 50 QPS |
| Pro | $13,999 | Up to 200 QPS |
| Max | $33,999 | Up to 500 QPS |
| Enterprise | Contact sales | 1,000,000+ QPS |
Builder and above include a dedicated priority queue, throughput and SLA guarantees, and email support. Enterprise adds Zero Data Retention and support through a dedicated Slack channel.
Pricing is current as of September 2026. Web Search unit prices and the Builder-and-above QPS Plans carried limited-time discount labels, so list prices and actual billing may change. Please check the official site for the latest pricing.
Pros & Cons
✅ Pros
- The API handles multi-angle research in parallel, which shortens the time your agent spends “looking things up”
- Search, extraction, embedding and model calls all run on one API key, so the number of vendors and keys you manage does not grow
- MCP server, CLI and Skill integrations let you start evaluating it inside your usual environment, such as Claude Code or Cursor
- The automatic $5 free credit lets you measure real results for your own use case before asking for budget approval
- SOC 2 Type 2 compliance, plus a no-retention option on Enterprise, makes internal security review easier to get through
⚠️ Cons
- Image search, video search, Multimodal Chat and Grounded Generation are Early Access, so designing around them leaves you exposed to availability
- There is no conventional fixed monthly SaaS plan, so your bill moves with usage and is harder to forecast
- If you need sustained high throughput, a QPS Plan is charged monthly on top of usage-based billing
- The accuracy benchmarks are numbers published by the vendor itself, and we could not confirm independent third-party verification. It is safer to base your decision on measurements with your own queries
Comparison with Similar Services
| Service | How it differs from Octen |
|---|---|
| Exa | An established player in AI-oriented web search APIs, ahead on track record and volume of material. Octen claims a higher accuracy rate than Exa instant in its own published benchmarks |
| Parallel | Also a search API for AI agents. Octen publishes a comparison benchmark against its turbo tier on its own site |
| Tavily | A search API for LLM agents that has been in use for some time. In Octen’s own benchmark it shows the largest gap among the compared services |
All of them share the idea of returning search results in a form LLMs can handle easily. Octen’s differentiators are automatic decomposition into sub-queries and keeping embedding models and the Model Gateway on the same platform.
Who Is It For
- Developers who want AI agents or copilots to answer with up-to-date web information
- Teams building RAG that fetches web-scale information on demand, because a static vector database goes stale
- People building deep research or report generation apps that fire a large number of searches behind a single request
- Anyone contracting search, extraction and embedding from separate vendors who wants to cut management overhead
Summary
Not having to stitch search, extraction, embedding and model calls together from separate vendors is the main reason to consider Octen. For apps that let an agent do the investigating, Broad Search’s parallel retrieval is what you feel in the response time. On the other hand, some features are Early Access, pricing is usage-based by default, and the accuracy evidence comes from in-house benchmarks ─ so the reliable path is to send your own queries using the $5 free credit and confirm both accuracy and cost before committing.