How we differ 03 · aamp vs Flowise / Langflow
Alternative to Flowise and LangflowFlowise and Langflow are strong visual interfaces for developers experimenting with Python and TypeScript libraries. They serve prototypes well.
Production deployment into CRM, ERP or HRM surfaces different problems: no deterministic calculation engine, hallucination risk in business calculations, and no audit logging.
| Criterion | aamp | Flowise / Langflow |
|---|---|---|
| Deployment model | Single Go binary / local SQLite | Node.js / Python (Docker / cloud) |
| Sovereignty (EU compliance) | 100% native air-gap, zero telemetry | Partial, depends on hosting |
| Code isolation / sandbox | Firecracker microVM | No hardware isolation |
| LLM security | Dual safety firewalls (Llama Guard / PII) | None, requires external custom code |
| Access control | Three-role RBAC with per-agent and per-knowledge-base grants | Missing in base stack |
| Pricing model | Per completed run, 0% token markup | Self-host / paid cloud vendor tiers |
Information was compiled based on public documentation of the open-source projects Flowise and Langflow.
Model hallucinations are removed from production metrics and bill-of-materials structures. Where visual wrappers rely on text output, aamp pairs the model with deterministic, sandboxed Starlark code.
Fourteen native audit log domains stored in aamp.sqlite3 record every modification, tool invocation and guardrail decision, satisfying EU AI Act requirements.
An agent processes variable signals from email and attachments, while material requirement calculations and BOM structures execute in deterministic Starlark code.
The dynamic Python and Starlark interpreter runs only inside single-use microVM instances, so large data files are processed without host compromise.
Vector indexing and document retrieval are logged precisely, with retention inside local SQLite and no dependency on external vector cloud vendors.