Context
The system needed to run AI workflows in an off-grid local environment with modular services for LLMs, automation, retrieval, and content generation.
AI & Agentic Systems
Off-Grid Modular AI Ecosystem
An offline modular AI ecosystem for local routing, RAG, automation, and avatar rendering.
Type: Off-Grid AI InfrastructureStack: Ubuntu + Ollama + LocalAI + n8n + ChromaDB + Wav2LipMarket: India (INR)
Challenge
Offline AI stacks require careful service orchestration. The challenge was to connect local models, automation tools, vector storage, and generation pipelines without cloud dependency.
Solution
Avlys assembled an Ubuntu-based ecosystem using Ollama, LocalAI, n8n, ChromaDB, Wav2Lip, local RAG, LLM routing, outreach automation, content generation, and avatar rendering.
Visual Proof
A designed view of the system Avlys delivered.
These visuals are clean representative mockups of the project system, not fabricated client screenshots. Real labels and project context stay in HTML for quality and accessibility.
Detail View
03
Core
Workflow View
04
Core
Scope
What was delivered.
01
Local LLM routing
02
n8n automation
03
ChromaDB RAG
04
Avatar and content generation
Process
Step 01
Mapped the user journey, operating workflow, and conversion or handoff points.
Step 02
Defined the information architecture, system rules, and implementation plan.
Step 03
Built the interface, integration layer, content structure, and launch-ready handoff.
Step 04
Reviewed performance, responsiveness, QA issues, and post-launch support needs.
Outcomes
Outcome 01
A modular local AI environment for experimentation and operations.
Outcome 02
Reduced dependency on cloud-only AI workflows.
Outcome 03
Connected retrieval, automation, and generation services.
Outcome 04
A system architecture that can be extended module by module.
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