Pricing and Agents

We offer consulting in obtaining the software, the licenses and the software keys.

Run on different LLM providers

The CORE as well as the agents need their own LLM runtimes subscriptions! This costs are additional to PARAMUS but give you the freedom to balance your spendings. You have the choice how much power PARAMUS will have in which field of expertise.

Mix them up for a well balanced system

You should configure different runtimes for different agents! Just like your team members have different skills (and salaries). This is just as comparable: By assigning agents to providers differently, we have achieved incredible results in optimizing the performance of PARAMUS (as a whole system) in terms of response time, response quality and total costs.

For example: run the free Calculator agent with non-critical, cheap but VERY FAST(!) xAI-Grok2 and run in contrast the PARAMUS Core with a openAI-GPT4o. To our experience the PARAMUS CORE (supervisor) should run with the best model you can effort. Simple agents like the calculation Agent can run „more stupid“.

Runtime LLM available:

  • OpenAI
  • Google Vertex AI (untested)
  • XAI
  • Anthropic

SECURE by design

How to install PARAMUS

(1) We offer a Docker-based distribution that can be deployed on-premises or run PARAMUS in your private cloud. Or: (2) For local installations: there is also Windows Installer that PARAMUS runs on your local system. Paramus has a Web/Browser based frontent.

Safety philosophy

Every user has his own PARAMUS. No shared environments – this is by design! The reason is, that PARAMUS is your personal assistant, really powerfull and so need to know the access to the systems on your behalf. Shared environments may be safe meanwhile … but still not enough for us to trust.

Both deployment options give a consistent user experience across any environment.

Newletter

Upcoming

This new technology build on CORE and has the ability to act in the background without supervision. It is intended for time-consuming advanced reasoning. It has implemented asynchronous agent access (=parallel).

This makes sense for long-running jobs like with computational calculations or route prediction in combination with advanced LLM like openAI o3 – and is really expensive!

(First beta release in Q3/25)

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