Case Studies & Selected Production Work

Standard AI streaming setups freeze or stutter because the browser UI tries to re-render token-by-token, causing massive display delays (minutes) on dense markdown reports, compounded by polluted raw stream status indicators.

Built a client-side adaptive character buffer that dynamically throttles and scales UI injection size based on stream congestion, combined with a clean multi-agent routing architecture completely isolated from UI string pollution.

Out-of-the-box RAG solutions fragment documents haphazardly, saturate context windows, and lose narrative or sequential continuity (such as cross-referenced lists and tables) during standard Top-K retrieval.

Eliminated heavy third-party AI abstractions in favor of a custom ingestion engine that weaves a linear graph directly inside the database using chronological neighborhood pointers.

Post-meeting information loss and operational delays caused by manual minute-taking, poor task tracking, and delayed extraction of concrete action items.

Deployed a decoupled, event-driven state sync loop using Socket.io for real-time room communication, backed by an asynchronous semantic extraction worker to instantly generate structured meeting intelligence.

Unstructured LLM outputs suffer from severe hallucination vectors, making raw text generation unusable for data-dense legal risk scoring matrices.

Enforced strict contract parsing boundaries using Structured Outputs via Zod schemas, converting probabilistic text into strict deterministic JSON payloads mapped to UI charts.