Reliability Calls #3: AI Automation that actually works: $100M, messy data, zero surprises

Every month, we unpack what it takes to build reliable AI – AI that doesn’t just demo well, but works reliably in production, handles edge cases, and earns trust over time.

Here’s this month’s agenda:

AI Automation that actually works: $100M, messy data, zero surprises

PromptQL CEO Tanmai Gopal shares how enterprise teams are using PromptQL to drive over $100M in expected annual impact through AI-powered automations of business-critical workflows.

For AI to take on business tasks, it must meet a very high bar for reliability. Most GenAI systems fall short—too brittle, too unpredictable for production. PromptQL changes that.

In this session, Tanmai will walk through how teams are using PromptQL to deploy AI that actually works in the enterprises—reliably.

You’ll learn:

• How PromptQL’s agentic semantic layer lets you build reliable AI on existing messy, distributed data—without expensive clean ups or centralization projects
• How PromptQL eliminates the non-determinism inherent in GenAI systems and prevents surprise failure modes in production
• All the automation initiatives that PromptQL makes possible