Why most enterprise GenAI prototypes fail
They ignore structured data problems! If your structured queries aren’t reliable, no LLM magic will fix bad retrieval or broken joins.
What will it take to make AI enterprise-grade?
That was the topic of focus at last month’s EntreConnect meetup. Leading that deeper conversation was Deepti Srivastava, Snow Leopard founder and CEO.
Here’s a breakdown of top takeaways from her builder-first perspective (originally published by EntreConnect).
5 core insights
The real crown jewels of any business are hidden in structured data — SQL databases, warehouses, internal APIs.
Building a GenAI workflow without connecting to real production data is just a toy project. Demos are easy; integrating live, messy enterprise data is the real challenge.
Multi-agent orchestration isn’t new — it's intelligent routing, retrieval, and transformation done at runtime. We've built these patterns long before “agents” became a buzzword.
Enterprise-grade AI demands reliability: consistent outputs, accuracy, and live data. Hallucinations kill trust and break critical workflows.
Most GenAI prototypes fail because they ignore structured data pipelines. Without getting deep into the tech stack (not just chatting with PDFs), GenAI stays stuck in POC land.
Operator real-talk
Data access is the hardest bottleneck. It's not about model quality — it’s about whether your system can securely and intelligently access the right row, column, and table, to get the right data for real-time decision making.
Prompting tricks won’t save you. If your structured queries aren’t reliable, no LLM magic will fix bad retrieval or broken joins.
Adoption isn’t blocked by excitement — it’s blocked by system integration risks. Enterprises aren’t scared of GenAI; they’re scared of breaking the workflows that actually pay the bills.
Retention matters more than initial, first-use adoption. Quick demos impress, but lasting value only comes when users trust the AI layer as much as they trust Salesforce or ServiceNow.
Key quotes
“Last year, everyone adopted something. But what’s the churn curve?”
"Productivity gains are table stakes. True enterprise AI unlocks new value — and that starts by wiring into your real structured systems."
"If you can't wire into the heartbeat of the business — the structured systems — GenAI will stay a sideshow."
“After every platform shift, it’s the new ideas—not the old winners—that dominate.”
Read more via the EntreConnect newsletter.
Subscribe to the Snow Leopard blog to follow our journey as we share our learnings.
