The Most Overlooked Problem in AI: Data Context LLMs are powerful, but without enterprise context, they remain generic. That’s why RAG, enterprise knowledge graphs, and domain memory layers are becoming essential...
Stop Chasing the Latest Models..
GPT
Claude
Gemini
The models will constantly change. Your competitive advantage will never be the model. It will be:
• proprietary data
• system architecture
• domain expertise.
Build model-agnostic systems. #AI#AgenticAI#AIConsulting
Data science doesn’t fail because of bad models.
It fails because insights aren’t communicated effectively. Many organizations invest heavily in analytics, yet decisions still rely on intuition.
Why? Because the last mile of data science isn’t analysis. It’s persuasion...
Every enterprise still runs legacy systems. The magic happens when AI agents can safely:
• read from legacy systems
• interpret data
• trigger workflows
Modern AI doesn’t replace legacy systems. It connects them intelligently. #AgenticAI#EnterpriseAI#AIConsulting#DataStackX
Using off-the-shelf GenAI is like buying supermarket pizza. Convenient, but generic. 🍕 For real enterprise value, you need to integrate your proprietary data. Yet, 45% of data scientists still use LLMs without connecting them to internal data. Cook at home! #GenAI#DataStrategy
#Hyderabad residents demand urgent repairs to neglected Manjeera Pipeline Road. Since Feb 2024, road condition has worsened, prompting calls for action from authorities to ensure safety, improve infrastructure. https://t.co/HcDaoBuV1j
@AmarKokkanti