AI-Powered, Thread-First Messaging Platform for Teams

The Situation

Sociail set out to replace noisy channel-based workplace chat with focused threads enhanced by native AI. They needed a technical product leader to architect context-aware AI assistance — summarization, task generation, and proactive support — on top of Matrix-based real-time infrastructure.

What We Did

• —Designed a prompt-routing layer for GPT-4 integrations with optimized latency (<500ms) and cost (<$0.01/query via caching and model fallbacks)
• —Architected a unified RAG pipeline with Pinecone vector embeddings for shared memory across multiple models, reducing multi-turn errors by 80%
• —Introduced agentic patterns using LangChain and ReAct-style prompting for modular agents — summarizer, scheduler, and GitHub issue auto-creation
• —Ensured security and scale with end-to-end encryption via Matrix, maintaining 99.9% uptime during beta spikes

Outcomes

• —Attracted 2,300+ beta users within two months with strong engagement metrics
• —Reduced AI context errors by 80% through unified RAG pipeline with hybrid scoring
• —Achieved 99.9% uptime and sub-200ms retrieval latency at scale
• —Shipped production integrations with GitHub, Zoom, and Google Drive