Agentic AI without token costs and without data leakage to the cloud

The transition from chatbot to AI agent changes the costs and risks of corporate AI. A chatbot answers a single question. An agent plans a task, gathers information, uses tools, evaluates intermediate results, and continues until a document, analysis, or draft is ready. Every step requires additional context and computing power. With cloud AI, this can lead to a bill that only becomes clear after the fact. In practice, this often results in unexpected and sky-high invoices.

Silent AI Pro from FAST LTA brings this way of working to your own data center. The organization purchases fixed computing capacity (one appliance) instead of individual tokens, API quotas, or per-user licenses. At the same time, data, prompts, and results remain under your own management.

Why agents demand more from the infrastructure

A simple question to a language model often consists of one input and one answer. An agentic task contains a series of operations. The agent can compare documents, retrieve information from a company system, flag discrepancies, create a draft, and re-check the result. The longer the task and the larger the context, the more model calls are required.

This makes a fully variable pricing model difficult to budget for. A successful pilot can actually become more expensive as more employees use the solution more often and processes become more complex. Organizations should therefore look not only at the price of a single prompt, but at the total costs of functioning AI processes.

Fixed capacity in your own environment

With Silent AI Pro, the computing power is part of the appliance. There is no billing per token and there are no API quotas or per-user licenses. The practical capacity is determined by the chosen hardware. This allows IT to tailor the system to the expected number of simultaneous users, the models used, and the complexity of the tasks.

The new 4U hardware is configurable with one to three NVIDIA GPUs. The platform design allows for expansion without having to switch immediately to a completely new hardware generation. This creates a growth path that can be planned technically and financially in advance.

More than local enterprise search

Silent AI ES focuses on searching company knowledge with local RAG. Silent AI Pro builds on that and adds a complete working environment.

• Projects bundle sources, instructions, and context for a specific assignment.
• Skills record recurring workflows so that teams can reuse them.
• Agents perform multi-step tasks and use linked tools and systems where necessary.
• Memory preserves the work context across sessions.
• Artifacts deliver the result as a document, analysis, or draft.

For example, a finance team can have contracts and supporting documents checked against a checklist. A service team can combine historical tickets, maintenance reports, and knowledge articles into a new answer or report. A sales team can use customer information, previous proposals, and current pricing data for an initial quote draft.

Control over data and access rights

The appliance can operate entirely within your own infrastructure. As a result, documents, prompts, answers, and intermediate results do not need to be sent to an external AI service. Silent AI Pro adopts existing read permissions from the identity provider and the linked source systems. Changes in permissions are synchronized, ensuring that access to information aligns with existing governance.

Answers contain references to the sources used. This makes it easier to verify a result and record the basis for a conclusion. For organizations in healthcare, government, financial services, industry, and research, this traceability is often a prerequisite for wider AI adoption.

A different calculation for corporate AI

Cloud AI can be suitable for experiments and fluctuating workloads. As soon as agents structurally perform processes with sensitive information, the calculation shifts. Variable token costs, external data processing, and dependence on licensing terms then carry more weight.

Silent AI Pro offers an alternative for organizations that want to manage AI capacity as part of their own infrastructure. The investment is fixed upfront, usage is not billed per token, and data remains in the chosen environment. This allows teams to scale agentic AI with more control over costs, capacity, and information.