Neurifly vs Hermes
Hermes is a free, MIT licensed agent from Nous Research that you operate yourself, with its own tools and messaging channels. Neurifly is the governed European platform for the same ambition, run as a service.
Hermes is open source under the MIT licence, runs locally or in Docker, ships dozens of built in tools and speaks across a long list of messaging platforms, with model costs going directly to whichever provider you configure. For an engineering team that wants autonomy, it is a serious option. Deploying agents across a business adds requirements the runtime itself does not attempt to cover: authorisation of who may run what, a human decision before an irreversible action, a record that cannot be rewritten after the fact, containment for generated code, centralised purchase of model access, and a spending limit that holds. Neurifly delivers those as a hosted European platform, with an append only trail carrying the model, tokens, latency and cost of every call, an approval centre for anything irreversible, an isolated sandbox with no network, and budgets per key that decline the request before the limit is passed.
| What you are comparing | Neurifly Apptivity | Hermes Nous Research |
|---|---|---|
| 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. | In part Free and open source under the MIT licence; you pay your own model provider. source |
| Runs in the European Union without changing plan | Confirmed European Union by default, on every plan. There is no region to switch on. | Confirmed It runs on hardware you choose, locally or in Docker, so the location is yours. 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. | In part You bring your own model keys and pay each provider 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. | Unconfirmed See the vendor's own pages. 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 See the vendor's own pages. source |
| Attach files to a conversation | Confirmed Documents and images go into the conversation and land in a knowledge base you control. | Unconfirmed See the vendor's own pages. 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. | Unconfirmed See the vendor's own pages. 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. | Unconfirmed See the vendor's own pages. 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. | Unconfirmed See the vendor's own 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. | Unconfirmed See the vendor's own 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. | Unconfirmed See the vendor's own pages. source |
Confirmed
In part
Unconfirmed
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.