Technical Specifications
Our infrastructure is designed for performance, security, and scalability. We use a modular approach to AI automation, ensuring that every component can be independently audited and improved.
Orchestration Layer
- Platform: self-hosted n8n (fair-code)
- Deployment: Docker Containers / Cloud Native
- Security: All workflows remain inside your VPC or a dedicated secure instance
Intelligence Layer (LLMs)
- Models: GPT-4o, Claude 3.5 Sonnet, Llama 3 (via Groq/Local)
- Optimization: Custom Prompt Engineering & In-context Learning
- Privacy: Zero Data Retention (ZDR) via enterprise API endpoints
Data & Memory Layer
- Vector DB: Pinecone, Weaviate, or pgvector
- Search: High-performance semantic retrieval (RAG)
- Caches: Redis for conversational context persistence
Security & Compliance
We prioritize the "Privacy-First" approach. By using self-hosted orchestration (n8n), we ensure that sensitive business logic never transits through third-party servers except for the encrypted LLM inference calls.