Jayashree Rajan

Raw RAG systems still hallucinate because they lack business context. Learn how semantic abstraction and Nexsets improve AI agent reliability.

Batch data breaks AI agents in production. Real-time context ensures fresh, reliable decisions powered by CDC, streaming, and data products.

Bigger context windows do not always improve AI agents. Learn why targeted context engineering delivers better enterprise AI performance.

Developers built real AI apps in hours with Express.dev. See how hackathon teams turned messy data into production-ready solutions.

See how Nexla’s Org Intelligence turns every new data connection into smarter, faster, AI-ready enterprise data products.

Most “AI-ready” platforms aren’t. Learn how Nexla MCP outperforms traditional data stacks for real-time, agentic AI workflows.

Explore how a multimodal AI pipeline built with NVIDIA models, Nebius infrastructure, and Nexla orchestration converts social media travel videos into structured itineraries.

Customer API and CSV feeds create engineering bottlenecks. Learn how to standardize raw customer data into governed, reusable data products using Common Data Models—eliminating custom integrations and scaling onboarding.

The Fivetran–dbt merger tests the future of open source in a SaaS-dominated world. Can dbt Core stay community-driven as corporate incentives reshape the modern data stack? Here’s what’s at stake—and what comes next.

Uncover how Fivetran’s pricing shifts and the dbt merger reveal the hidden costs of modern data integration. Learn how to predict changes, protect budgets, and avoid costly surprises.

The modern data stack has failed. The Fivetran–dbt merger highlights tool sprawl, rising costs, and integration complexity, forcing data leaders to rethink their infrastructure strategy. Choose wisely.

Poor data management can cost organizations 15–20% of revenue. Reusable, scalable data products help—but only if they’re consistent and reliable. A Common Data Model (CDM) standardizes and structures data, ensuring accuracy, scalability, and long-term value.