Glean alternatives: open-source enterprise AI search without the €50k/year lock-in

If you asked ten CIOs what tool they would use to make all their company knowledge searchable — Confluence, Jira, Slack, Google Drive, Salesforce, your internal wikis — eight of them would name Glean.

The product is real. It works. The search is fast, the connectors are mature, the AI summaries are good enough that people actually use it instead of going back to the old habits.

There is one problem.

It costs a fortune.

Glean does not publish pricing, but enterprise buyers and procurement teams have been transparent about the range. The widely reported floor is around $30 to $50 per user per month, with implementation costs and minimum seat requirements that push the real first-year commitment into the €50,000 to €150,000 range. For a company with 200 people, that is a line item the CFO will notice and question.

The product is worth the money for companies with 2,000 people and a knowledge management problem they can no longer defer. For a mid-market company with 50 to 500 people, the question is not whether Glean is good. The question is whether the math works.

It usually does not.

There is an alternative that a growing number of companies are choosing. It is called Onyx. It was previously known as Danswer. It is fully open source, and it does the same fundamental thing: it connects to your data sources, indexes them, and lets people ask questions and get answers grounded in the actual documents.

A thread on Reddit's r/dataengineering captured the decision well. A company needed better search across scattered knowledge articles. They had built a custom prototype with Pinecone and Streamlit. It was impressive early on, but they knew it did not come close to high-quality enterprise products like Glean. Glean was too expensive. They searched for an open-source, self-hosted alternative. Onyx was the closest thing they found — running for maybe $100 a month instead of thousands per month like Glean would have cost.

That is not a marketing claim. That is a real company making a real procurement decision on a public forum.

The tradeoffs are real too. Glean has a larger team, more connectors, polished UX, and enterprise support baked into the price. Onyx has fewer out-of-the-box integrations, requires someone to actually run and maintain the infrastructure, and demands a level of technical ownership that Glean buyers never think about. The open-source model does not eliminate complexity. It moves it.

The question most companies should ask is not which product is better. The question is what kind of complexity they can handle.

If your company has an IT team comfortable running self-hosted services, managing infrastructure, and troubleshooting when things break, the open-source path is a legitimate way to get 80 to 90 percent of Glean's capability at a fraction of the cost. Onyx has connectors for Confluence, Jira, Slack, Google Drive, SharePoint, Salesforce, HubSpot, and more. The core search and retrieval engine is production-ready. The permission model works.

If your company does not have that internal capacity, the open-source path becomes a project instead of a product. You save on license fees and spend on engineering time. That can still be the right answer, but you need to count it honestly.

There is a middle option that some companies are choosing: managed open source. Someone who understands the tool, the infrastructure, and the data landscape deploys it, configures the connectors, sets up the permission model, and stays accountable for it running. The company gets a working system without needing to hire the expertise in-house. The cost sits somewhere between self-hosting and the Glean license — and the data stays under the company's control, not a third-party SaaS.

That is the model Solve IT uses when the problem is knowledge access rather than process redesign.

There is another dimension that rarely gets discussed in these comparisons.

Enterprise AI search is not a one-time purchase. It is a living system. New connectors get added. Permissions change. New teams need access. Old documents need de-indexing. The company that buys Glean has a vendor relationship to manage. The company that goes open source has a system to maintain.

Neither is free. Neither is easy. They are just different kinds of work.

The company that goes with Glean will get a polished experience and will never think about the infrastructure. The company that goes with Onyx will think about it every time something breaks, but it will also own the stack, the data, and the roadmap. Vendor lock-in is a real cost, even when it is invisible on a quarterly P&L.

For companies that are serious about building internal AI capabilities rather than consuming them, owning the search layer is a strategic decision, not just a cost optimization. It is the difference between renting the nervous system of your company and building it.

Here is the honest part that most vendors will not say.

Glean is the better product right now. If budget is not a constraint, and you want the most polished experience available, Glean wins. The connectors are more mature. The UX is better. The AI summaries are more refined. The support team exists.

Onyx is the better choice if you are a mid-market company that needs working enterprise search without the enterprise price tag, and you either have the technical capacity to run it or you are willing to partner with someone who does.

The decision is not about features. It is about what kind of company you are building. The one that buys polished tools from vendors, or the one that builds and owns its infrastructure.

Both are valid. One is much more expensive. And one requires something the other does not: someone inside the company who understands how the pieces fit together.

If you are evaluating options for enterprise AI search, the first step is not a vendor demo. It is a map of where your knowledge actually lives, who needs access to it, and what level of ownership you want over the system that serves it.

That map does not take months to build. It takes a focused conversation with someone who has done this before.

The cost of the conversation is lower than the cost of the wrong platform choice. And the wrong platform choice costs more than anyone admits during the procurement process.