What We Build

• AI agents that automate business workflows end-to-end
• LLM-powered internal tools (support, ops, sales)
• Workflow automation using n8n (no-code + code hybrid)
• Custom MCP integrations for tool orchestration
• Data pipelines feeding real-time AI decisions

Technical Stack

• Automation: n8n (self-hosted, extensible workflows)
• LLMs: OpenAI / Claude / open-source models (Llama, Mistral)
• Agent Frameworks: LangChain / custom agent runtimes
• Protocols: MCP (Model Context Protocol) for tool chaining
• Backend: Node.js / Python (FastAPI)
• Memory: Vector DBs (Pinecone, Weaviate, FAISS)
• Orchestration: Redis queues / event-driven pipelines
• Deployment: Docker / cloud / on-prem setups

What Makes This Different

• Focus on automation, not just chatbots
• Agents connected to real business systems (CRM, ERP, APIs)
• Deterministic + AI hybrid flows (reliable + intelligent)
• Cost-optimized inference (routing, caching, batching)
• Full control via self-hosted workflows (no black boxes)

Use Cases

• Customer support automation
• Lead qualification & sales automation
• Internal ops copilots
• Data extraction & document processing