Machine learning thatacts, not just answers.

A unifying platform bringing multiple analytical capabilities — scoring, root-cause analysis, screen analysis, and search — under one extensible system.

Q&A over multi-hour video via chunked, sentence-level retrieval — exposed through a chat interface and an MCP-based agent.

Chain-of-thought routing across domain-specific subagents for structured query resolution.

An LLM-based scoring approach benchmarked against golden datasets, with a human-in-the-loop feedback cycle.

A framework-driven RCA system surfacing systemic patterns across call, chat, and email transcripts.

An analyzer extracting structured operational data — actions, idle time, errors — from raw screen recordings.

An end-to-end automated platform covering data versioning, training runs, model artifacts, evaluation, and deployment.

A real-time event pipeline built to hit a strict latency SLA, with idempotent handling and multi-source validation.

Multi-worker distributed training and pipeline infrastructure built on Kubeflow, with Docker-based deployment.

Applying large language models for zero-shot named-entity recognition across a wide range of document types.

End-to-end object detection pipelines covering data processing, model building, evaluation, and deployment.

Structured text extraction combining statistical models, neural networks, and hand-tuned pattern matching.