White Papers
Evals in Production
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Generative AI is reshaping the enterprise landscape, enabling employees to design domain-specific solutions with unprecedented speed and creativity. Yet, with rapid adoption comes real risk: recent studies reveal that over 60% of enterprises cite governance and compliance as their top concern, while only one-third have responsible controls in place.
This white paper presents a three-pillar governance framework; central registry, continuous monitoring, and policy-driven guardrails that equips enterprises to scale AI responsibly. Backed by research showing that organizations with structured AI governance achieve up to 40% higher adoption rates of approved tools, it provides practical guidance on balancing innovation with accountability.
Download the paper to discover how your enterprise can safeguard trust, ensure regulatory readiness, and turn responsible AI into a strategic business enabler.
Building a Trusted, Conversational Data Layer for Financial Services Financial services companies rely on data to operate. Things like credit ratings are based on data and market intelligence is built using data. The systems that support these things need to be easy to see, secure and well managed. But the information needed to manage all […]
AI Practitioner’s Guide to Building Production-Ready LLM Applicationss Most enterprise LLM projects stall between pilot and production. The difference is rarely the model, it is the architecture. This guide synthesizes what we have learned across 35+ enterprise implementations, organized into seven application patterns we have repeatedly delivered. The focus is on the decisions that determined […]
