Everyone is building AI agents… but very few are talking about the biggest blocker: fragmented data. I sat down with Ravi Marwaha, Chief Product & Technology Officer at Arango, on The Ravit Show to unpack what’s really going on beneath the surface.
This was not a typical “AI hype” conversation. We went deep into why agents that are supposed to reason, decide, and act are still struggling in real enterprise environments. And it comes down to one thing: context.
Here’s what stood out from the conversation:
- Ravi’s journey and why he chose to build at the intersection of data and AI
- How fast the space has evolved and why most architectures are already outdated
- The real problem with fragmented data when it comes to building reliable agents
- The rise of the “context layer” and why everyone is suddenly talking about it
- Where Arango fits in vs vector databases, graph databases, and data catalogs
- Real customer use cases that go beyond theory
- And what the next 18 months could look like for this entire space
One thing became very clear to me:
The definition of a data platform is changing in real time. It is no longer just about storing or querying data. It is about enabling AI systems to actually understand and use that data in context.
If you are building anything in AI right now, this is a conversation worth paying attention to.
#data #ai #context #arango #theravitshow
