Best AI Search Tools for Work in 2026: Company Search and Agent Search APIs

Type "best AI search engine" into any of those engines and every result names the same five consumer apps, none of which can search a company's own Slack messages.

That gap is the whole story. "AI search" is not one shopping decision, it is at least three, and every roundup that ranks Perplexity, Bing, and Andi Search as competitors quietly leaves out the tools that actually search a company's internal documents.

Glean has grown into a $300 million-a-year business doing exactly that job, and it does not appear on a single top-ten list built from a plain Google search. For a 20-person operations team told to "just get us an AI search tool," picking off the wrong list wastes a procurement cycle, not just a subscription fee.

AI Search Splits Into Three Purchases, Not One

The first question is not which tool is best. It is which job you are hiring for, because the three jobs do not compete on the same axis.

The first job is open-web answers: a question with a public, current answer, phrased in plain language, returned with citations. Perplexity, Bing, Andi Search, and Consensus (for academic papers specifically) all compete here, and they compete mostly on price and citation quality, not on whether they can find anything at all.

The second job is workplace search: finding the right internal document, thread, or decision across Slack, Google Drive, Notion, and email, with the same permissions a human employee would have. Glean and the newer Cerenovus compete here, and the competitive axis is completely different: not "can it answer," but "can it be trusted with everyone's private channels," which is a security and procurement question before it is a product question.

The third job is narrow discovery: a single, specific kind of search that has nothing to do with the other two. Google Lens identifies objects and products from a photo. A general-purpose answer engine is the wrong tool for this job, and a workplace search platform is worse.

A fourth buyer sits beside these three and rarely appears in a consumer roundup: a developer whose searcher is not a person at all, but an AI agent or a retrieval pipeline. That buyer needs an API, not a chat window, and it gets its own shelf below.

Name the job before you shop. Everything below is organized by that split, not by star rating.

Four Questions That Actually Sort the Category

Skip the shortlist entirely and these four questions still get a buyer to the right shelf, because each one has a testable yes-or-no answer.

Does the answer need to come from inside a login, or from the open web? If someone outside the company, with just a browser, could eventually find the same answer, that is job one, not job two. Does the pricing scale per seat, or does it carry a contract floor regardless of headcount? A five-person team can afford $20 a seat; almost none can absorb a $60,000 annual minimum, no matter how good the per-seat math looks on a slide.

Does the tool preserve the permissions that already exist, so that an employee can only search what they could already open? Workplace search that ignores existing access controls is a compliance problem wearing a product feature, and it is the reason Glean and Cerenovus both lead with security posture before they lead with search quality.

Is the free tier good enough for the actual job, or is it a lead-generation teaser that expires the moment the work gets real? Andi Search and Google Lens pass that test today; several tools in this category do not.

A reader who answers these four questions honestly will land on the right shelf even without reading another word of this guide. The shortlist below exists to name names once that shelf is chosen.

The Open-Web Shortlist: Perplexity, Bing, and Andi Search

Perplexity is the default for a reason: over 45 million monthly active users, according to usage data compiled by Demandsage, and a free tier with five Pro Searches a day before the $20-a-month Pro plan removes the cap. A Max tier at $200 a month adds broader model access, and an Enterprise Pro tier runs $40 a user a month for teams that need admin controls without a full workplace-search platform.

Its citation-first format has made it the benchmark every other open-web engine gets measured against, including inside this article.

For the open web on its own, Hokai keeps a full comparison of six free AI search engines, with free-tier limits and data handling for each. This guide spends its length on the other two purchases: search across a company's own files, and search an AI agent can call. And if what you need is a long cited report rather than a search box, that is a different product again, covered in the best AI for deep research. Academic, legal and medical research with checkable citations is in the best AI for research.

Bing costs nothing extra if the team already pays for Microsoft 365, since Copilot search rides along on top of an existing license rather than adding a new seat. Microsoft's own Copilot for Business page describes a free consumer tier and a Microsoft 365 Copilot add-on priced at $30 a user a month for full Microsoft Graph integration across files, email, and meetings.

The caveat: outside the Microsoft ecosystem, Bing's answers lag Perplexity's on citation depth, and there is little reason to choose it as a standalone tool.

Andi Search is the outlier worth naming specifically: completely free, ad-free, with no account required and no paid tier live at all as of this writing, per Andi's own site. The company has said an Andi Plus tier and a developer API are planned, with no date attached. Most "free" AI tools mean free-with-limits. Andi is the rare one that currently is not, which also means there is no roadmap commitment that it stays that way once a paid tier does ship.

The Workplace-Search Shortlist: Glean and Cerenovus

This is the shortlist every consumer roundup skips, and it is priced on an entirely different scale. Glean crossed $300 million in annual recurring revenue in May 2026, according to the company's own press release, on the strength of enterprise contracts that start around $50 to $75 a user a month.

The real barrier is not the per-seat rate. According to Glean's own pricing analysis published on its site, typical enterprise deployments carry a minimum annual contract near $60,000, a floor that applies whether a company buys 15 seats or 300.

Cerenovus is the challenger worth watching. Y Combinator's own company page lists it as a Summer 2026 batch company, founded by three Harvard students, building what it calls a "company brain" that turns Slack, email, and internal docs into a single markdown knowledge graph, readable by both employees and the AI agents working inside it.

Cerenovus has no public pricing page; its own site states pricing is available only through direct outreach, with pilot customers already live. That is a genuine gap in what can be verified today, not a number worth guessing at, and it is also the reason Cerenovus cannot yet be scored against Glean on price at all, only on approach.

Neither vendor discloses a self-serve signup flow. Both are sold through a sales conversation, not a checkout page, which is itself a signal: workplace search touches enough sensitive company data that no vendor in this shortlist wants a stranger indexing a Slack workspace without a human on the other end of the contract.

The Developer Shelf: Firecrawl, for When the Searcher Is an AI Agent

Every tool above assumes a person reads the answer. A growing share of web searches are now run by software instead: a coding agent checking current documentation, a research agent gathering sources, a retrieval pipeline keeping a knowledge base fresh. That buyer does not want a summary with footnotes. It wants the pages themselves, in a format a language model can read without cleanup.

Firecrawl is built for that job. Its search endpoint takes a query and returns titles, descriptions and URLs. With one extra option it also scrapes every result and returns the full page as clean Markdown in the same call, according to Firecrawl's own documentation.

Search is one part of a wider API. The same credits cover:

• Scraping a single page into Markdown, HTML or structured JSON.
• Crawling and mapping a whole site, not just the page a search result points to.
• Driving a browser for pages that need clicks before they show content.

The core is open source, and an official MCP server lets an agent call Firecrawl directly instead of through custom glue code.

Pricing is credit-based and published in full, which is rarer in this category than it should be. These are the plans on Firecrawl's pricing page as of October 2026, with yearly billing:

A basic page scrape costs 1 credit and a search costs 2 credits per 10 results, all from one shared balance. Enterprise is priced on request and adds zero data retention and SSO.

Firecrawl, Tavily or Exa: Picking an Agent Search API

Tavily and Exa sell to the same developer buyer with different strengths: Tavily packages search, extraction and research as separate agent endpoints, and Exa ranks the web by meaning rather than keywords. Firecrawl is the pick when the agent needs to read and act on what it finds, not just locate it, because search, scraping, crawling and browser interaction all run on the same API and the same credits.

The test for this shelf is the same as for the other three: name the job first. If a person reads the answer, start with Perplexity. If an agent reads it, start with Firecrawl's free plan and measure how many credits a real week of queries uses before choosing a tier.

Perplexity vs. Glean: The Question That Actually Decides This

Put the two principals of this category side by side and the comparison collapses almost instantly, which is itself the finding. Perplexity answers a question from the open web in seconds for $0 to $20 a month. Glean answers a question from a company's own systems, with permissions intact, for an annual contract that runs five figures at minimum and climbs from there.

Pick Perplexity if the question could be answered by a well-informed stranger with a browser: market sizes, competitor pricing, a technical explainer. Pick Glean, or evaluate Cerenovus's pilot program, if the question can only be answered by someone who already works at the company: where a specific contract clause lives, who approved a vendor last quarter, what the finance team decided in a Slack thread six months ago.

No amount of Perplexity Pro credits closes that second gap, because Perplexity was never indexing the company's Drive in the first place.

Two Names Fell Out of This Category While Nobody Was Watching

Two tools still tagged under "AI search" no longer fit the label, and neither drift shows up in a spec sheet.

Komo AI used to market itself as an AI research and search platform with tiered credit plans. Its own homepage today carries the tagline "The Self-Driving Business" and describes autonomous systems that run "Propose, Execute, Measure, Learn" cycles for business operations, with no mention of search anywhere on the page. Whatever Komo is building now, it is not competing for the same buyer as Perplexity or Glean, and a 2026 search roundup that still lists it as a search engine is working from stale information.

Shepherd, a book-discovery site built around author-curated reading lists, rebranded to Book DNA earlier this year. According to the company's own migration notes, the domain moved from shepherd.com to bookdna.com with the same features and accounts intact, just a new name.

It was never a search engine in the Perplexity or Glean sense to begin with, matching readers to books by taste rather than answering an open query, which is exactly the kind of narrow-discovery tool that gets swept into "AI search" listicles for search-engine-optimization reasons rather than functional ones.

Neither drift is a scandal. Products pivot, and brands rename. The problem is specific to this category: a roundup that gets refreshed once a year, or not at all, keeps citing a tagline that has not been true for months, and a reader comparing search quality against either tool is benchmarking against a moving target that already moved.

Checking a vendor's own homepage before publishing a comparison sounds obvious. Most roundups skip it anyway, because it is the one step that cannot be done from a spreadsheet of old screenshots.

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Who Should Skip This Category Entirely

A team under five people almost never needs anything on the workplace-search shortlist. The free tiers of Perplexity, Bing, and Andi Search cover open-web questions, and a five-person team's internal knowledge usually fits in someone's head or a single shared drive that a person can search manually faster than any platform can be configured. Buying into a $60,000 Glean contract at that size is not an early adoption, it is a wasted budget line.

A researcher who only needs literature reviews should also skip the general-purpose engines. Consensus indexes peer-reviewed papers specifically and includes a "Consensus Meter" that shows what percentage of studies agree on a yes-or-no research question, a feature none of the open-web engines replicate because they are not built for it. Its free tier covers a handful of AI-generated paper analyses a month, enough to test whether the format fits before anyone pays for the unlimited version.

Anyone whose actual need is visual or shopping search should skip every tool named so far. Google's own Shopping Graph, which Google Lens draws on for in-store product matches, lists more than 45 billion product listings, a scale no general-purpose answer engine or workplace search platform is trying to compete with. That is not a gap in Perplexity or Glean. It is a different job entirely, and naming it correctly is the whole point of this guide.

The Split Still Holds, Even for the Team That Thinks It Does Not

The obvious objection: a five-person startup will just type questions into Perplexity or ChatGPT forever and never touch anything Glean-shaped, so why does the three-way split matter to them at all?

It matters because the trigger point arrives faster than most teams expect. The moment headcount crosses roughly 20 to 30 people and documentation has spread across Slack, a shared Drive, and a wiki nobody fully trusts, a team typically already has an "AI search tool" on the books, purchased off a consumer roundup that never mentioned Glean or Cerenovus existed. By then, switching vendors costs more than choosing correctly would have the first time.

What Changes Next

Cerenovus's pricing is still unpublished, which means the real test of this category over the next year is whether a workplace-search product can undercut Glean's $60,000 contract floor without cutting the permissions model that makes workplace search trustworthy in the first place. The first vendor to do that, not the one with the best demo, is the one worth re-checking this list for.

Frequently asked questions

What's the real difference between an AI search engine and an AI workplace search tool?

An AI search engine like Perplexity or Bing answers questions from the public web and returns citations. An AI workplace search tool like Glean instead indexes a company's own Slack, Drive, and email, respecting each employee's existing permissions. The two solve different jobs and are priced on completely different scales, from free to about $20 a month for open-web search versus enterprise contracts that start near $60,000 a year for workplace search.

Is there a genuinely free AI search tool in 2026?

Yes. Andi Search offers unlimited AI-powered search with no account, no ads, and no paid tier live as of 2026. Google Lens and Bing's consumer search are also free with no usage caps, though both are narrower in scope than a general-purpose answer engine.

How much does enterprise AI search like Glean actually cost?

Glean does not publish pricing, but buyer-reported figures put per-seat costs around $50 to $75 a user a month. The bigger constraint for smaller companies is Glean's typical minimum annual contract of roughly $60,000, which applies regardless of headcount. Cerenovus, a newer competitor for the same workplace-search job, has not published pricing at all and currently sells through direct outreach and pilot programs.

What is the best AI search tool for developers building AI agents?

Firecrawl is a strong default when an agent needs to search the web and then read the pages it finds. Its search endpoint can return each result as clean Markdown in one call, and the same API scrapes, crawls and drives a browser. The free plan gives 1,000 credits a month with no card, and paid plans start at $16 a month billed yearly. Tavily and Exa are the main alternatives for the same job.

What should a small team use instead of enterprise search?

A team under about five people rarely needs anything beyond the free tiers of Perplexity, Bing, or Andi Search, since their internal knowledge base is usually small enough to search manually. Workplace search tools like Glean start making sense once headcount reaches roughly 20 to 30 people and documentation is scattered across Slack, a shared drive, and a wiki. Buying enterprise search earlier than that trades a real budget line for a problem the team does not have yet.

Covered in this guide

• Perplexity: Perplexity AI answers from the live web with numbered citations and lets paid users pick among models from 6 AI labs; a limited free plan exists.
• Glean: Enterprise AI search platform at $300M ARR in 2026, connecting 100+ apps with permissions-aware results, AI agents, and MCP support from ~$50/user/month.
• Andi Search: AI search for the next generation: answers, not just links
• Bing: Microsoft's AI-powered search engine with Copilot integration, multi-turn search, and enterprise capabilities. Free consumer search; Copilot Search powered by OpenAI's Prometheus model. Enterprise Bing Chat is also available for teams.
• Cerenovus: AI operating partner for large enterprises, PE and advisory firms: reads a company's own email, contracts, invoices, tickets and chat to find operational inefficiencies, each finding ranked and cited to its source. Demo-only, custom priced. Y Combinator S26. Not the medical-device company of the same name.
• Consensus: AI-powered search engine for peer-reviewed research literature
• Exa: Search API that ranks the web by meaning for AI agents and retrieval pipelines, with Lite, Auto and Deep search modes, an asynchronous research Agent and an official MCP server. A free Starter plan with monthly credits needs no payment method.
• Firecrawl: Web data API for AI agents: search, scrape, crawl and interact, returning LLM-ready Markdown. Open source core with a free plan and an MCP server.
• Google Lens: Google's AI-powered visual search tool that identifies objects, translates text in 100+ languages, matches products against the Shopping Graph, and provides homework help. Free on Android, iOS, and Chrome, with a Windows desktop app that launched in 2026.
• Komo AI: AI search engine that returns cited answers from the web, with deep research, people search and premium models on paid credit plans.
• Shepherd: Free book discovery platform with 3,500+ author-curated lists and AI Book DNA matching that connects readers with books matched to their personal taste, free forever.
• Tavily: Five-endpoint web access API for AI agents: search, extract, map, crawl and research, with a free plan and a keyless trial mode.

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