MLDS speaker · 2026

Ravindra Babu Katiki

Strategic Technology Advisor, vriksha.ai

About Ravindra Babu Katiki

I’m a hands-on technology leader with 27+ years in gaming, focused on building products players enjoy and platforms teams can trust. I’ve led portfolios with over $1B in revenue impact, partnered closely with product, compliance, and business, and operated systems at multi-billion daily service-call scale—all while mentoring engineers and keeping delivery predictable and calm. Launched No-Limit Hold’em (~$150K/day) and collapsible multi-table tournaments (~$100K/day). Re-engineered Hand History into a single source of truth; ~70% faster page-launch time and a markedly better UX. Modernized Bingo to support ~100K concurrent players in one room via a service-oriented architecture. Moved the right workloads from RDBMS to NoSQL; enabled ~150M spins/day on the Casino platform. Operated platforms at 4B+ service calls/day and scaled systems to 125K+ CCU with high availability. Cut incident-resolution SLAs by ~50% through focused squads, better observability, and workflow redesign. Built capabilities: Poker BOT detection, Bingo player-sentiment analysis, and personalized Casino recommendations. Led architecture due diligence and consolidation during the bwin–Party merger; selected best-of-breed components for a unified platform. Drove B2B/B2G integrations and regulatory frameworks to launch Poker across multiple European markets. Known for scalability, stability, clean enterprise architecture, and pragmatic Agile/Lean delivery. Among TradeFlock’s Top 10 Tech Leaders in India (2025)

1 edition on the MLDS stage · 1 session on record

Ravindra Babu Katiki, Strategic Technology Advisor, vriksha.ai

Talks at MLDS

Sessions from the MLDS agendas, newest first.

  1. MLDS 2026

    Bengaluru
    26–27 Mar 2026

    • Mar 27, 2026 · 15:55–16:15 · Hall 2 · Bengaluru

      Exclusive Workshops

      From Chatbots to Agentic AI: How Conversations Became Actions

      Evolution from conversational bots to action-oriented AI agents Core agentic patterns (intent → plan → act → observe) How agents access knowledge and integrate with real-world systems Agent system architecture and multi-agent collaboration Challenges, failures, and productionizing agentic AI systems

    MLDS 2026 agenda MLDS 2026 talk recordings on YouTube (opens in a new tab)

MLDS 2027Feb 25–26 / Mar 4–5Early bird till 15 Dec

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