Uniphore’s Sachdev on FDEs and Data Ontologies

Enterprise AI is shifting from reliance on massive foundational models and human-led engineering toward autonomous, agentic platforms. CIOs now prioritize tokenomics, data readiness, and sovereignty, moving away from expensive, static, human-curated ontologies. Uniphore addresses these challenges by deploying proprietary data agents that autonomously crawl enterprise data to build dynamic knowledge graphs. Small Language Models (SLMs) fine-tuned on domain-specific data outperform frontier LLMs in specialized tasks, delivering a 97% reduction in token costs and significantly lower energy consumption. By integrating Retrieval Augmented Fine-Tuning (RAFT) and capturing agentic traces for reinforcement learning, organizations can establish a self-improving flywheel of intelligence. This approach effectively disrupts the traditional "Forward Deployed Engineer" model, enabling faster, more scalable, and cost-efficient AI deployment across global enterprises.