IDFC First Bank needed to build an enterprise-grade conversational AI platform from scratch to deliver personalized customer experiences at scale. The platform had to handle complex challenges: slow response times (20+ seconds), fragmented customer data across 8 different propensity models, probabilistic drift in LLM outputs, and the need for robust safety guardrails in a highly regulated banking environment. Without a cohesive platform strategy, we risked launching a system that would frustrate users with slow, inconsistent, and potentially non-compliant responses.
I owned the complete platform development charter and organized platform steering committee discussions to align stakeholders. I developed a comprehensive 11-layered context engine that enabled true multi-turn conversations and integrated 8 fragmented customer propensity models into an evolving customer DNA (cDNA) system that powered 6 layers of personalization. To address latency, I balanced cost, latency, and response quality through prompt and context engineering. I designed sub-second ensemble systems for language identification (improving speed from 3s+ to 100ms) and intent classification with hierarchical mapping to reduce disambiguation rates. For safety and compliance, I incorporated an agentic guardrail system with closed feedback loops and automated red-teaming. I also established a comprehensive LLMOps strategy with technical and business observability requirements, multi-turn automated regression testing, and 8 self-serve dashboards to track impact against baseline metrics from the incumbent NLP bot.
Key trade-offs included balancing response quality against latency and cost through prompt engineering rather than always using the most powerful (and expensive) models. I chose an ensemble approach for language detection and intent classification to reduce probabilistic drift, accepting additional system complexity for reliability. For personalization, I had to integrate 8 fragmented propensity models into a unified cDNA system rather than building from scratch, prioritizing speed to market. I implemented HITL (human-in-the-loop) fallback strategies for edge cases rather than trying to automate everything, recognizing that some scenarios require human judgment in a banking context.
This thought me i should work hard
This thought me i should work hard