AI Agent Use Cases — Self-Hosted RAG, Local GPU Inference, ERP Integration | aamp
Production agent workloads

Governed AI agent use cases and workflows.

Engineering, security and operations teams deploy autonomous AI agents with strict host authority, Firecracker microVM sandboxing and dual safety firewalls. From untrusted code execution to air-gapped internal RAG, these are the workloads aamp is built for.

01 · Autonomous agent orchestration

Build and deploy enterprise AI agents with total host control

Single-binary Go execution, three-role RBAC with per-agent grants, and no step penalties on reasoning loops.

02 · RAG with 100% local data sovereignty

Enterprise RAG where your data never leaves the perimeter

Vector indexing and inference hosted entirely on-premise — or on an engineer’s workstation.

03 · Customer-facing information chatbot

A support chatbot answers from your content only

A web widget or OpenAI-compatible API, backed by a RAG knowledge base and dual input/output firewalls.

04 · Hardware ROI and open-weight inference

Amplify your local GPU investment from day one

Native integration for Ollama, vLLM and local open weights, with 0% platform markup.

05 · Governed enterprise integration

Add AI to core legacy ERP and CRM systems

MicroVM sandboxing, dual LLM firewalls and hard budget caps keep execution safe and CFO-approved.

06 · Complex document workflows

Automate deep technical RFI and RFP responses

Isolated Firecracker microVM document rendering with precise local context extraction.

07 · Model agnosticism and infrastructure freedom

Plug in any model or provider without rewriting your workflows

Side-by-side model testing, native cloud connectivity, and no vendor lock-in.

08 · Custom workload orchestration

Replace fragile cloud webhooks with self-hosted control

Hybrid visual and code execution, predictable per-run billing, full auditability.

Yours

Tell us your case

LLM · RAG · agents · workflows · scheduling — one control layer.

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