Glean and Naxis get compared because both promise answers from your company's knowledge. They are different machines for different questions. Glean is Google for your company: an enterprise search platform that finds where things are stored across 275+ connected apps, built and priced for organisations of hundreds or thousands of seats, sales-quoted at a recorded median of $98,890 a year. Naxis is the one that actually knows your business: a private knowledge engine whose proprietary modelling algorithm holds your people, permissions, concepts and live records, so it answers what is true right now (totals, statuses, agreements, who handles what) with citations, in the channels you already use, under your company's own name, from €99 a month on published plans, managed or on your own server. Most questions inside a company are not "where is the file". They are "what is true". That is the question Naxis was built to answer, and it is what makes Naxis the practical Glean alternative for companies of roughly 5 to 200 people.
The wall
You have probably already lived the reason this page exists. Somebody asked, again, something your company has answered before. Not "where is the contract", but "what did we actually agree with Acme". Not "where are the invoices", but "how much is still unpaid". The answer existed: in a PDF nobody opened, an AI call summary nobody read, a comment at the bottom of a CRM record. It still had to travel through a person to reach the asker. So you went looking for a fix, and the first name you met was Glean.
Glean, in one line, is Google for your company. Search, an assistant and agents across 275+ connectors, built since 2019 for enterprises with thousands of seats, and genuinely the best-known way to find where things are stored across a sprawling stack.
But read your question again. It was never "where is it stored". It was "what is true right now". Finding the six documents that mention the Acme deal is not the same as knowing what the deal currently is. Search points. It does not know.
Then comes the wall. There is no pricing page; there is a sales process, minimum commitments that typically start around 100 to 250 users, and contracts Vendr records at a median of $98,890 a year across 174 purchases, from $29,880 at the low end to $208,897 at the high. If you run thousands of seats and company-wide search is your problem, book the call; you will be in good hands. If you run 30 people and your problem is truth, you just hit a wall built for somebody else. It is not a pricing decision made against you. It is what a platform costs. And the way through is not a discount. It is a different machine, built for your actual question.
Two different machines
Glean is a platform. Platforms are big on purpose: hundreds of connectors to maintain, a search destination to operate, an agents layer to orchestrate, enterprise cloud estates to deploy into, a salesforce to sell it all. Every part of that is rational, and every part costs money that only enterprise contracts can carry. The seat minimums are not greed. They are physics.
Naxis is an engine. It does one thing, deep: enterprise knowledge and context modelling. There is no destination app to operate and nothing to roll out. It connects the dozen tools a real company actually runs, including the custom ones no connector list ever includes (that is what the ingestion API is for), builds a live model of the business, and answers wherever people already type. It is a far smaller machine to run. That is why it can be priced for a 30-person company: physics again, this time in your favour.
So no, Glean is not Naxis for bigger companies, and Naxis is not Glean for smaller ones. One is built to find. The other is built to know. Hold that frame: every difference below falls out of it.
An index of documents, or a model of the business
Ask both machines the same question: "How much did we invoice Acme this quarter, and who handled it?"
A search platform does what search does: finds content that mentions Acme, hands it to a model, and summarises. Glean is genuinely good at that, across more sources than anyone. But finding and summarising documents is not the same discipline as knowing the business.
Naxis answers from its model instead. Its proprietary enterprise knowledge modelling algorithm does not stop at indexing text. It holds the people and what each one is allowed to see, the concepts work revolves around, and the records behind them, with exact totals, so a money question comes back as a figure with citations, not an estimate. Context is modelled too: who is asking, from which channel, about what, so a vague question in a busy chat still lands on the right answer. Every source is re-swept every 15 minutes and the model is maintained by no one. And every answer is grounded: it cites what it stands on, or it says it does not know.
In our internal evaluations against the enterprise platforms, answer quality on real company corpora holds level or better. We publish no benchmark theatre. The demo is the real application; judge it there.
Your company's assistant, not our brand
Rollout is where knowledge tools go to die. The wiki nobody updated, the portal nobody opened: every one of them assumed people would come to it. Glean's answer is to make the destination excellent, and for browser-native enterprises it works.
Naxis's answer is to have no destination at all. The engine answers as your company's assistant: on your WhatsApp number, your Slack and Teams, your Google Chat, your email address, the widget on your website, your own domain at assistant.yourcompany.com. Sixteen channels, every one wearing your name, not ours. Externals you choose get a doorway too: customers on the widget or on Messenger and Instagram see only the groups you allow. Apart from the person who connects it, your team may never see or hear the word Naxis at all. People just notice that asking works now. Naxis is not an app you open; it just is.
Who holds your data
A shared platform holds many companies' knowledge behind one control plane, and that concentration is exactly what attackers love: one break-in, many victims. Enterprises manage that risk with vendor security reviews and contract clauses. A small company should manage it with architecture.
Every Naxis deployment is single-tenant by construction: its own application, its own database, its own document store, serving one company and nobody else. Permissions are enforced architecturally, inside retrieval itself, so an answer cannot reach someone outside their access. Indexing runs on your deployment, and generation goes through a contracted model API under a data-processing agreement with zero-retention terms. If policy says your infrastructure, self-hosting puts the identical product on your own Linux server, and your data never touches us. The control work behind ISO 27001 and SOC 2 is built into how deployments run; current status for both lives at /iso27001 and /soc2.
Glean's options are enterprise-shaped: its hosted service, a tenant Glean deploys and manages inside your own AWS or GCP (their documentation is clear this is a managed service, not traditional self-hosting), and an on-premises route with Dell for data-centre scale. Sound engineering for their buyer. But a 30-person company does not have a cloud estate for a vendor to move into. It has one server and a policy, and with the right machine that is enough.
What it costs, and why
The prices come last because by now they explain themselves.
- Glean, as of July 2026: sales-quoted only. Median contract $98,890 a year (Vendr, 174 recorded purchases), minimums typically 100 to 250 users, reported per-seat figures around $40 to $50 a month plus usage credits for heavier AI features. The platform could not be cheap if it wanted to be.
- Naxis, published at /pricing: Starter €99, Team €299, Enterprise €599 a month, Unlimited by quote. Managed hosting included, cancel any month. Self-hosting a flat €249 on top of any plan. The engine can be, because there is far less machine to pay for.
In round numbers, the median Glean contract equals about twenty-five years of the Naxis Team plan. Neither number is wrong. They are the running costs of two different machines.
The Glean alternative for small teams
Five questions decide it, honestly:
- Seats. 100+ with an enterprise budget culture is Glean's lane. Five to two hundred is ours.
- Procurement. If vendor security reviews and six-figure line items are normal for you, book their demo.
- Where work lives. Signed into a browser all day, or in WhatsApp, Slack, Teams and email? The second is our home ground.
- Who must hold the data. If the honest answer is "we do", you want the machine that ships whole on your own server.
- What you ask. Finding documents, or knowing what is true right now (totals, statuses, what was agreed) with citations? The second is what a knowledge model is for.
If what you need is Google for your company, at thousands of seats with the budget culture to match: choose Glean, genuinely. It leads that segment. If what you need is the one that knows your business, Naxis is the Glean alternative built for you: what is true, right now, with citations, at your size, in your channels, under your name, on your servers if you want them.
Either way, do not take a vendor's comparison on faith, including this one. The demo is the real application. Open it and ask it something you would normally have to chase a person for.
Plans and the self-hosting add-on: /pricing.
