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Rented by the seat, and run by someone else.
Enterprise chat products, enterprise search products and single-purpose assistants — meeting notetakers, employee-support bots, departmental copilots — are usually evaluated one at a time, but they share one shape. You license them per person, inference happens on the vendor's infrastructure with the vendor's model, and at the end of the contract there is nothing you keep. That shape is a good trade for a lot of work. This page is about the point where it stops being one, and it replaces six near-identical vendor pages that were all making this argument with the name swapped.
The structural differences
Four properties of the category, not complaints about a product.
Deliberately written about the category rather than about named vendors. Every product in it is good at what it was built for, the specifics change every quarter, and a page asserting defects about somebody else's software ages badly and deserves to.
What exists at the end of the contract
A packaged assistant
Access, for as long as you pay for it. The configuration, the connectors and the tuning live in the vendor's product, and they leave when you do. That is a normal and acceptable trade for a productivity tool.
NeuralSeek
A deployment and a configuration you hold. The workflows, the guardrail policy and the retrieval setup are artefacts in your environment, which is the difference between a tool you use and a system you operate.
How wide the problem can get
A packaged assistant
Scoped to what the product is for — meetings, employee support, internal search, chat over documents. Within that scope it is usually better than anything you would build, because the vendor has done nothing else for years.
NeuralSeek
Not scoped to a use case, which is a genuine disadvantage when your problem is exactly one of theirs. It matters when the second and third workloads arrive and they are not the same shape as the first — because otherwise each one arrives with its own vendor, its own data path and its own audit story.
Which model, and where it runs
A packaged assistant
The vendor's, on the vendor's infrastructure, changing when the vendor changes it. You will usually get a strong statement about not training on your data, and it is usually accurate — but the inference itself happens outside your boundary.
NeuralSeek
Yours, per step, on endpoints you control, inside the boundary you chose — including one with no egress. For most organisations this is a preference. For an organisation whose regulator has asked, it is the only question.
What happens after the third one
A packaged assistant
Each product is a separate contract, a separate set of permissions into your document estate, a separate log format and a separate answer to 'who can see what'. The individual decisions are all defensible; the aggregate is what security teams end up calling shadow AI.
NeuralSeek
One connection layer, one policy surface and one audit trail across every workload built on it. This is less exciting than any single product's headline feature and it is the thing organisations wish they had chosen at the third assistant.
When to reach for which
Buy the packaged one when the shape fits.
Three tests, and the first two point away from us.
One well-defined job, done for staff, inside the company
Transcribing meetings, answering IT questions, searching the intranet. A product built for exactly that will beat a general platform configured to do it, and it will beat it next quarter too. Buy it.
You need it working this month and nobody will operate it
A packaged product with a connector and a login is a genuinely different commitment from a deployment. If there is no one to own configuration and no appetite to acquire one, the platform is the wrong answer regardless of what it can do.
The answer goes to a customer, a regulator or a record
This is where the category runs out. An answer that leaves the company needs to be grounded in material you approved, refusable when it is not confident, stripped of sensitive fields before the model sees them, and reconstructable afterwards. Those are deployment properties, not features you can enable.
Three questions about running a mix.
Which is what almost everyone is actually doing.
Does this mean removing the assistants we already have?
Usually not, and proposing it is normally a sign a vendor has not understood the estate. The productive pattern is to leave the tools that do one internal job well, and to move the work that crosses a boundary — customer-facing, regulated, or reaching systems of record — onto something you can evidence.
How is this different from enterprise search?
Enterprise search is one of the workloads, not a different category. The distinguishing questions are whether retrieval respects your source permissions, whether an answer carries a score you can threshold on, and whether the result can be routed into a workflow rather than returned to a person. Those determine whether you can put search in front of a customer or only in front of staff.
Which products does this page mean?
Deliberately none by name. The previous version of this site had a page per vendor, and the arguments were identical with the noun changed — while the supporting material had drifted into repeating litigation allegations and citing competitors' marketing blogs as evidence of defects. If you want a comparison against a specific product you are evaluating, ask for one in a call, where it can be about your requirements and can be corrected when it is wrong.
See it running inside your own boundary.
Talk to a NeuralSeek expert about how it fits your stack, where your data has to live, and the governance your auditors already expect.