Neurifly vs Mistral
Mistral is a European vendor with open weight models and an assistant licensed per seat, deployable in your own infrastructure. Neurifly is the managed European platform around models: usage based, auditable, and open to several vendors at once.
Mistral publishes open weight models under Apache 2.0, sells an assistant per seat and offers an enterprise edition that can be self hosted or run in your own cloud. If the objective is to operate the model on infrastructure you control, that is a strong starting point, and it remains one of the reasons the company is a credible European choice. Running a model, however, is only part of what a business deployment requires. The rest is retrieval you can scope, execution you can contain, approvals before irreversible actions, records that stand up to review, and a cost that can be attributed to a team or a key. Neurifly supplies that operating layer as a managed service inside the European Union, with open weight models among the ones you can select per conversation, an append only trail carrying the cost of every call, and budgets that decline a request rather than invoice for it later.
| What you are comparing | Neurifly Apptivity | Mistral Mistral AI |
|---|---|---|
| Paid for what runs, not per seat | Confirmed A balance you top up, spent on tokens, searches, runs and storage. No seats and no minimum. | Unconfirmed Pro is 14.99 dollars a month. Team is 24.99 dollars per user a month with a 50 dollar monthly minimum. Enterprise goes through sales. source |
| Runs in the European Union without changing plan | Confirmed European Union by default, on every plan. There is no region to switch on. | In part Enterprise can be self hosted, run in your own cloud, or run on Mistral's cloud. source |
| Models from more than one vendor on one account | Confirmed Models from several vendors, including open weight ones, picked per conversation and billed on one account. | Unconfirmed Mistral's own models, with open weight ones under Apache 2.0 you can host yourself. source |
| Every call recorded with its tokens, latency and cost | Confirmed An append only trail with the model, tokens, latency, cost and the key that made the call. Agent runs are hash chained. | In part The product pages list the administration features for companies. source |
| A budget per key, refused before the spend | Confirmed A limit per key and per organization. The call is refused before it goes past the limit rather than invoiced after. | Unconfirmed Seat prices, with a monthly minimum on the Team plan. source |
| Attach files to a conversation | Confirmed Documents and images go into the conversation and land in a knowledge base you control. | Confirmed A standard part of the product. source |
| Answers can search the web | Confirmed Search is a platform service: the organization picks the engine, results are redacted before the model sees them, and every query is priced and recorded. | Confirmed A standard part of the product. source |
| Single sign on for the whole company | Confirmed Sign in with the company account, with roles and a permission catalogue enforced by every service rather than by the interface. | In part Listed among the enterprise features. source |
| Several models answer the same question at once | Confirmed Fusion sends the question to a panel of models in parallel and a separate model synthesises the result. | Unconfirmed See the vendor's own pages. source |
| Every source opens on the passage it came from, with its page and relevance | Confirmed Sources are numbered from what retrieval actually returned, and each opens the passage with its page number and its relevance score. | In part The assistant cites what it reads; the detail is on Mistral's pages. source |
| You choose what a conversation may read: a base, folders, or single documents | Confirmed Retrieval is pointed at a knowledge base, at folders in it, or at named documents, and access is granted per base and per group. | In part Libraries and files are offered; the detail is on Mistral's pages. source |
| Code the model writes runs in a sandbox with its network cut | Confirmed The runner installs a filter on itself that cuts the network, files it produces come back to you, and the run is recorded like any other action. | In part Mistral publishes a code interpreter feature; the detail is on its pages. source |
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Last updated 4 August 2026
Start with a question, not a project.
Create an account, ask something real, and look at what the trail recorded. That is the whole evaluation.