serp.fast

Ad-free, privacy-first AI search that answers rather than lists links

Nathan Kessler
By Nathan KesslerUpdated

Each tool is evaluated against our methodology using public docs, vendor demos, and hands-on testing.

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Andi Search website

What is Andi Search?

AI-powered search engine with a conversational interface and API access, focused on ad-free, privacy-respecting results.

Our verdict

A privacy-first AI search engine that provides direct answers rather than link lists. The conversational UX is clean and the API is straightforward. Small team and limited index depth compared to Exa or Brave. Works for privacy-conscious use cases but not yet battle-tested for high-volume agent pipelines.

Categories:

AI search APIs are the infrastructure layer that gives large language models access to current web information. Unlike traditional search engines, these APIs return semantically relevant, structured results optimized for retrieval-augmented generation (RAG) and AI agent workflows. They are used by AI products that need to answer questions about the real world beyond their training data.

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How Andi Search compares

Exa

Exa offers dramatically deeper index coverage and more sophisticated embeddings-based retrieval.

Perplexity Sonar

Perplexity Sonar provides superior AI-synthesized answers, though without the privacy focus.

Linkup

Linkup shares the ethical positioning but with publisher licensing and SOC2 compliance.

Frequently asked questions

How much does Andi Search cost?

Andi Search is freemium. The consumer search interface is free and ad-free. The developer API does not publish fixed tiers; Andi describes it as usage-based at roughly under a cent per query, and access is still waitlisted rather than open signup. Request access and confirm current pricing on andisearch.com before you build it into a pipeline.

Is Andi Search open source or self-hostable?

No. Andi Search is a hosted, closed-source product. You cannot run the index or the search engine on your own infrastructure. The github.com/andisearch organization publishes only peripheral tooling and API docs, not the core index or engine, so there is nothing to fork that would let you self-host. You reach it through the consumer interface or the hosted API. If running search inside your own environment is a hard requirement, Andi Search will not meet it, and you should look at self-hosted retrieval stacks instead.

Does the Andi Search API return structured output for AI agents?

Yes. Andi Search exposes a search API that returns structured results usable in RAG pipelines and agents. One caveat: it does not render JavaScript or fetch full page bodies for you. It returns search results over its own index, so you pair it with a separate fetch or scrape step when you need the complete contents of a page.

How does Andi Search compare to Exa?

Both are AI search APIs aimed at agent and RAG use, but Exa has a deeper index and a longer production track record at high volume. Andi Search positions on privacy and an ad-free consumer interface. For high-throughput retrieval that has been tested at scale, Exa is the safer default today. Choose Andi Search when privacy posture matters more to you than index depth.

What is the best alternative to Andi Search?

Exa is the strongest alternative for most teams building agent and RAG retrieval, given its larger index and proven scale. Perplexity Sonar suits cases where you want answer generation bundled with search, and Linkup is worth comparing for sourced, citation-style results. Pick based on whether you need raw retrieval, generated answers, or strict sourcing. Andi Search stays reasonable when privacy is the priority.

Who is Andi Search best for?

Andi Search fits AI product teams that want privacy-respecting, ad-free search and a usage-priced API for retrieval features, especially early-stage builders who watch per-query spend. It is less suited to high-volume production agent pipelines that need a very deep index and a long reliability history, where Exa is more proven. Treat it as a fit for privacy-conscious or cost-sensitive cases rather than maximum-scale workloads.

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