pravar srivastava

Building the memory & control plane for enterprise AI Systems
Founder @ FabricMind

[pravar srivastava @pravar]

@CashApp @CashSupport I received funds that were confirmed 3-4 times by your support team — and the money is nowhere in my account. This is unacceptable. I have documentation of every confirmation. Escalating to @CFPB_Director if not resolved immediately. #CashApp #CashAppScam

[pravar srivastava @pravar]

@Jason I am in

[pravar srivastava @pravar]

Check out my latest article: Post 5/5 — What enterprise AI readiness actually takes. The timeline nobody wants to hear https://t.co/j3zyPm8nCt via @LinkedIn

[pravar srivastava @pravar]

7/ I wrote the full breakdown on LinkedIn — why it happens, what the semantic layer actually is technically, and why nobody builds it.
Link in comments.
https://t.co/PKbkAGNyvQ

[pravar srivastava @pravar]

🧵 Your AI pilot crushed the demo.
Six months later — quietly shelved.
This is the most common story in enterprise AI. The real reason nobody names.

[pravar srivastava @pravar]

6/ Until that layer exists:
Your pilots will keep working in demos. And dying in production.
Every time.

[pravar srivastava @pravar]

The companies winning the AI transition aren't launching the most pilots.

They're the ones who recognized 18 months ago that foundation > model.

The model is the easy part. It always was.

[pravar srivastava @pravar]

Everyone's talking about enterprise AI readiness.
Most of the conversation is wrong.
After years inside enterprise data platforms across insurance and finserv — here's the honest diagnosis. 🧵

[pravar srivastava @pravar]

Uncomfortable timeline:

Layer 1: 2-3 years.

Layer 2: 2-5 years. Most aren't treating it with that urgency.

Layer 3: No industry solution exists yet.