Discover the architectural and business differences between the fully ready aamp control plane, cloud-based SaaS solutions and open prototyping frameworks. Explore why enterprises are moving from the R&D phase to production-grade, sovereign AI systems.
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| Dimension | aampAgent Control Plane | Orchestration platformsSaaS: Lindy, Make · OS: Dify, Flowise · workflow: n8n | Open-weight & local AIOpen-weight, Ollama · e.g. Bielik, PLLuM, Hermes | Chat & RAG ecosystemse.g. Open WebUI, AnythingLLM |
|---|---|---|---|---|
| Main role in the system | Ready-to-use engine and orchestration platform (Agent Control Plane).Provides an isolated environment for autonomous AI agents to operate. | Workflows and prototypes.Creating cloud-based workflows, prototyping and task automation. | Model runner and local models.Infrastructure tools and locally optimised language models. They serve raw text. | RAG interfaces and knowledge chats.They provide the end-user visual layer. |
| Environment & deployment model | Single Go binary.Native on-premise operation. Local SQLite database. | Cloud SaaS or Docker and Node.js.Fully cloud-based SaaS services or environments based on Docker and Node.js scripts. | CLI or Docker on GPU servers.Command-line binaries (CLI) or Docker containers requiring dedicated servers with GPU resources. | Cloud SaaS or web ecosystem.External cloud-based environments (SaaS) or complex web and development ecosystems. |
| Data sovereignty (EU AI Act) | 100% data sovereignty (native air-gap mode).Zero external telemetry, protecting ERP/CRM environments from leaks. | No native sovereignty.Typical cloud models do not guarantee native sovereignty, and sensitive data is sent to external data centres. | Total privacy.Weights are processed on your own hardware. The engines themselves lack logic to protect traffic from external attacks. | Basic compliance.Cloud-based solutions mostly require full trust in the hosting provider's procedures. |
| Code & integration isolation (sandbox) | Hardware-level isolation.Processes run inside closed Firecracker microVM virtual machines. | Shared environments, no isolation.Standard shared cloud environments or operationally non-isolated Node/Docker containers. | None.Engines like Ollama are solely for inference and are not designed for the safe execution of external code. | Predefined plugins only.No built-in isolation like Firecracker microVM. |
| Prompt protection & LLM security | Dual safety firewalls (guardrails).Automatic filters for sensitive data and PII before the request reaches the model. | Basic mechanisms, e.g. human-in-the-loop.Usually basic defence mechanisms, or external services have to be installed. | Depends solely on the model.The security model depends entirely on the features of the language model selected by the administrator. | No native dual API barriers.They typically rely on system prompt configuration and basic RBAC. |
| Pricing model & maintenance costs | 0% markup on requests (BYOK) and no step fees.No hidden commissions on calls in an execution-based model. | Monthly credit packages.Constant accrual of a step tax on every call. | No markup, but costly hardware.The software is free and has no middleman margins. Server infrastructure and team maintenance costs are substantial. | Message-pool and per-user fees.Complicated, hard-to-estimate fees for message pools and per-user access margins. |
The table compares aamp with other market categories on dimensions known from classic standards and pricing models, e.g. environment, security and pricing model.
A common mistake engineers and developers make when automating an enterprise is writing manual integration scripts on open-source models (like Bielik running in Ollama) and treating them as competitors to aamp. In reality, this is a complementary technology stack (Full Air-Gap Stack): the model thinks, aamp acts and controls.
Thinking: open-weight models and engines (Ollama, Qwen, Mistral). Their sole task is to provide raw text quickly and locally, without any knowledge of the system architecture and without checking the security of the application logic.
Action and control: the aamp platform (Agent Control Plane). It removes the Day-1 Operational Gap burden of infrastructure management. It retrieves generated commands, runs them in an isolated Firecracker microVM hardware environment, enforces 35 granular access permissions (RBAC), protects company secrets from leaking and records an audit trail in 14 log domains.
Predictable costs and savings of up to 70% by eliminating the step tax and using a native BYOK model with zero hidden commissions for external cloud providers.
Test and switch newer models, run e.g. in Ollama or vLLM in air-gap mode, from a single panel with one click. No expensive DevOps teams and no rewriting of working code.
Stable operation of extensive and sensitive ERP/CRM-class systems. Test any model without the risk of violating GDPR.
microVM isolation, air-gap mode and billing per completed run instead of per loop step.
See the comparison → aamp vs. Dify.aiA single Go binary, personal data protection and hardware isolation for regulated environments.
See the comparison → aamp vs. Flowise / LangflowA production environment instead of a visual layer on LangChain: full audit logs and 0% token markup.
See the comparison → aamp vs. Lindy.aiDeployment on your own infrastructure, air-gap mode and no credit limits.
See the comparison → aamp vs. OllamaOllama serves model weights; aamp executes, isolates and audits. Comparison below.
See the comparison →| Criterion | aampAgent Control Plane | OllamaModel Runner |
|---|---|---|
| Architectural role | Agent orchestration, execution and control | Running and serving LLM weights (inference) |
| Code execution / sandbox | Native Firecracker microVM (hardware-level) | None (Ollama does not execute code) |
| LLM security | Dual safety firewalls (prompt guard and PII) | None (relies entirely on the selected model) |
| Tools & access control (RBAC) | 35 granular permissions for tools and databases | None (exposes the raw /api/generate endpoint) |
| Auditability | 14 audit log domains in local SQLite (EU AI Act ready) | Basic HTTP / Docker container logs |
| Deployment model | Single Go binary, local SQLite (air-gap ready) | CLI binary / Docker |
A common mistake in designing local AI systems is treating Ollama as a ready-made engine for building agents. Ollama is a great, lightweight tool for serving model weights, but by itself it cannot safely execute code, manage RBAC permissions, run browser task loops or protect against data leaks. aamp is not a competitor to Ollama: it is a management layer (Control Plane) that can use an Ollama server as a local model provider and adds a rigorous B2B production environment around it.
Combining aamp and Ollama creates a 100% sovereign, isolated (air-gap) AI stack inside your server room. Ollama ensures that queries and company data do not leak to commercial cloud providers. aamp ensures that code and automations generated by the local model do not damage internal servers or transmit unauthorised data within the local network.