White Paper: Harnessing AI-Native Data Logistics in the Enterprise

Genai Enterprise Data Wp.pdf

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The prompts:

1. This video: https://www.youtube.com/watch?v=d93obltJg88

2. This insight: Data build-up will change when the data segregation & routing agents mature. SaaS must prepare the backend for an entirely different workflow of having GenAI in the loop that is inevitable at the frontend. Generating, labeling, sorting, securing, storing, fetching and interpreting data becomes a SOTA challenge and the first to figure it out might be able to secure a sustainable moat. Retrofit is going to be a nightmare strategy and an outcome that must be dreaded in the enterprise software space.

3. This follow-up: That's how data richness and precision confidence can be achieved in the enterprise space - where substantial amount of AI money is. Occasional hallucination will be an exciting feature than a trust issue.

4. Bonus insight: Further on this, sovereign AI need not be the most powerful LLM - but it must be built from ones strongest core even if with much less parameter count. Domain expertise at the core of a tiny model is a moat. What do you think?