Secure Alternative to Dify.ai | aamp – Hardware Isolation and Air-Gap

How we differ 02 · aamp vs Dify.ai

Alternative to Dify.ai

Past the prototype, into governed production.

Dify.ai is a flexible open-source system for fast prototyping of LLM applications and simple RAG workflows. B2B teams, ERP systems, healthcare and finance need architectural maturity it does not deliver.

Hardware sandboxing, granular access control and full data sovereignty are what separate a prototyping tool from a governance-first control plane.

  • Single Go binary
  • Hardware sandbox
  • 14 audit domains
  • NIS2 / DORA ready
01 · Side by side

aamp compared with Dify.ai.

Criterion aamp Dify.ai
Deployment model Single Go binary / local SQLite Docker Compose / managed SaaS cloud
Sovereignty (EU compliance) 100% native air-gap, zero telemetry Partial, requires complex configuration
Code isolation / sandbox Firecracker microVM at hardware level Standard Docker container
LLM security Dual safety firewalls (inbound prompt guard / outbound PII) Basic prompt-guard rules
Access control Three-role RBAC with per-agent and per-knowledge-base grants Basic organization role split
Pricing model Execution-based, 0% token markup Message models / credits / queries

The presented information was prepared based on the analysis of publicly available information sources regarding Dify.ai.

02 · What changes

Where the architectures diverge.

01

Single-binary architecture

Rather than maintaining a multi-container Docker stack with PostgreSQL and Redis, aamp runs as one Go binary against a local SQLite database. Installation takes seconds and fits on-premise environments.

02

NIS2, DORA and EU AI Act compliance

aamp records the full agent decision cycle across 14 audit log domains directly on the local server, satisfying EU data-sovereignty requirements.

03 · In practice

What teams bring to aamp from Dify.ai.

Strict data privacy & healthcare

Process medical records and PII without data leaving the hospital network

With air-gap mode and local models (vLLM, Ollama), aamp powers agents that analyse medical histories and e-referrals with a full data-privacy guarantee under GDPR.

Secure document parsing

Parse unknown PDF and Excel files with resistance to prompt injection

Counterparty documents are parsed inside a microVM sandbox behind outbound PII filters. A hidden malicious prompt cannot infect the system or exfiltrate data.

Enterprise governance

Precise control over what each agent may reach

Build agents that operate on internal company resources with explicit boundaries on which tools, knowledge bases and datasets they can access.

Looking for your own scenario? See all eight use cases

Run the same agents on your own terms.