Kuldeep Paul

Healthcare organizations are deploying AI across clinical documentation, diagnostic support, claims processing, patient communication, and drug discovery. The AI in healthcare market is projected to reach $110.61 billion by 2030, growing at a 38.6% CAGR according to MarketsandMarkets. But unlike consumer AI applications, healthcare AI operates under strict

Claude Code is one of the most capable AI coding agents in production today, but it creates a cost visibility problem that catches engineering teams off guard. Each agentic session triggers dozens of API calls for file operations, terminal commands, and code editing, often using high-cost models like Claude

The best enterprise AI gateways for LLM cost tracking give teams hierarchical budget controls, per-request attribution, and real-time enforcement before overages hit. Here are five worth evaluating. LLM API costs are one of the fastest-growing line items in enterprise technology budgets. A customer support agent handling 10,

Claude Code has become one of the most widely adopted AI coding agents in enterprise engineering organizations. Developers use it to scaffold applications, debug complex codebases, refactor legacy systems, and automate routine engineering tasks directly from the terminal. But scaling Claude Code from a handful of developers to an entire

Fintech companies are deploying AI across fraud detection, credit scoring, KYC automation, customer service, and regulatory compliance. McKinsey estimates AI could add $200 to $340 billion in annual value to the global banking industry. But unlike consumer applications where a hallucinated response is merely inconvenient, a wrong answer in financial