The right enterprise search tool is the one that respects permissions: staff should only get answers built from documents they're allowed to open. Test that before anything else. Then decide whether you want a finished workplace product, a question assistant or a developer toolkit you build on, and run your own staff's real questions through two shortlisted tools.
An AI answer is only as safe as the document behind it. If you're comparing Glean with other ways to search company data, that's the first thing to hold every vendor to, ahead of the interface, the integrations or the demo. Below are eight options, in no particular order, grouped by what you're really buying.
Permissions decide whether anyone trusts it
Enterprise search is only as good as two things: its connectors and its permission handling. Connectors decide which systems it can read. Permission handling decides whether it respects who's allowed to see which document.
Get the second one wrong and the damage is real. A staff member asks a harmless question and the answer quotes a salary review, a board paper or a customer contract they were never meant to see. Once that happens, nobody trusts the tool again, however clever its answers are.
So before you compare anything else, ask each vendor how it reads permissions from your source systems, how quickly it updates when someone's access changes, and whether answers are built only from documents the person asking can open. Then check it yourself with test accounts at different levels.
Finished platforms, assistants or toolkits
Finished workplace products. Moveworks is an AI assistant platform that helps employees find answers and automate tasks across business apps. Ayfie offers one AI platform for a company's assistants, agents and use cases, built on its own data, and the vendor says it's hosted on your terms and made in Norway. SWIRL takes a federated approach, searching the systems you already run, live, as the signed-in user, and it's pitched at regulated firms.
Question assistants. Dashworks unifies company data from your tools into one knowledge base and answers questions in plain language. Onyx is open-source AI enterprise search, which suits IT teams who'd rather run it themselves.
Developer toolkits. Algolia is an AI search and retrieval platform spanning agentic, generative and keyword search. Vectara is an enterprise platform that turns complex, multimodal data into answers. Mendable lets you build AI chat applications by ingesting your content. These aren't finished workplace search products. You build on them, so they suit teams with developers and a specific use in mind.
Most vendors in the first two groups quote on request and sell to larger teams, so expect a sales process rather than a sign-up page.
Eight workplace search options compared
| Tool | Approach | Good for |
|---|---|---|
| Algolia | Search and retrieval API | Building AI and keyword search into your own product |
| Ayfie | Enterprise AI platform | Assistants and agents on your own data and hosting |
| Dashworks | Workplace question assistant | Plain-language answers across company tools |
| Mendable | AI chat for docs and support | AI chat built on your own content |
| Moveworks | Workforce AI assistant | Employee answers and task automation across apps |
| Onyx | Open-source enterprise search | Open-source search across company data |
| SWIRL | Federated AI search | Live search across existing systems as the signed-in user |
| Vectara | Enterprise RAG platform | Answers from complex, multimodal company data |
Who each tool is built for
Algolia
Best for: Developer teams building their own search on an AI search and retrieval platform that spans agentic, generative and keyword search.
Ayfie
Best for: Companies wanting one AI platform for their assistants, agents and use cases, built on their own data and hosted on their terms, per the vendor.
Dashworks
Best for: Smaller teams that want an AI assistant pulling company data from their tools into one knowledge base and answering questions in natural language.
Mendable
Best for: Sales and support teams building AI chat applications by ingesting their own content, with just-in-time answers as the vendor's pitch.
Moveworks
Best for: Large employers wanting an AI assistant that helps staff find answers and automate tasks across business apps.
Onyx
Best for: IT teams who'd rather run open-source AI enterprise search, searching all company sources in parallel, according to the vendor.
Want AI doing the heavy lifting in your marketing?
I build the systems that handle the boring 80 percent, so you get your week back. Done properly, with the human kept in.
SWIRL
Best for: Regulated firms that want federated AI answers searching their existing systems live, as the signed-in user, without copying data elsewhere.
Vectara
Best for: Enterprises turning complex, multimodal data into answers through a RAG platform that promises to unify data and deliver context.
My advice for IT and knowledge teams
Don't start with features. Start with the systems your staff use every day and the permission rules that already exist inside them. A tool that connects to everything but ignores those rules is worse than no tool at all, and a tool that respects them but misses your main document store won't get used.
Decide early whether you want to buy or build. A finished platform gets you moving faster, while a developer toolkit gives you more control and asks more of your team. Federated search, which queries systems live rather than copying data, is worth a look if you're in a regulated industry and want less data moving around.
For a wider view, see my guide to enterprise search software. If what you really need is a customer-facing chatbot trained on your docs, my list of AI chatbot builder alternatives is a better starting point.
Running a twenty-question test
- Collect twenty real questions from staff in different teams, in their own words.
- Include a few questions whose answers sit in restricted documents.
- Connect two shortlisted tools to the same systems with the same permissions.
- Ask every question in both, signed in as different staff members with different access.
- Open the sources each answer cites and check they're correct and allowed for that person.
- Note which questions each tool couldn't answer, and why.
Twenty honest questions will tell you more than a polished demo, and the restricted ones will tell you whether it's safe to roll out.
Do you make enterprise search or workplace AI software? Tool makers can ask to be considered for a featured place on this list.
Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.
Frequently asked questions
What's enterprise search?
It's software that searches across a company's own systems, such as documents, chat, tickets and wikis, and increasingly uses AI to answer questions in plain language rather than only returning links.
How does enterprise search handle permissions?
Good tools read the access rules from each connected system and only use documents the person asking is allowed to see. Ask each vendor how it does this and how fast it updates when access changes.
What's federated search?
Federated search queries your existing systems live at the moment someone asks, instead of copying everything into a central index. It can mean less data moving around, which some regulated firms prefer.
Should I buy a finished product or build on a toolkit?
Buy if you want staff searching soon with little engineering effort. Build if you've got developers, a clear use case and a need for more control over how answers are produced.
How do I check AI search answers are accurate?
Open the sources each answer cites and read them. Run the same real questions through each shortlisted tool and compare both the answers and the documents they came from.
