Saket Saurabh

AI systems fail when context doesn’t scale. This article explains the limits of context graphs, why static relationships break for enterprise AI, and what’s needed to deliver accurate, trustworthy AI outputs at scale.

betanews.com: In this Q&A, Saket Saurabh explains why context engineering is key to reliable, compliant, and intelligent enterprise AI workflows.

In this episode of The SaaS Podcast, host Omer Khan talks with Nexla’s founder, Saket Saurabh, about live‑coded demos, consultative outreach, and bold moves that drove multi‑7‑figure deals.

Saket Saurabh, Nexla CEO, explains why enterprise AI’s future lies in context engineering: building the right data, memory, and workflows for smarter, more reliable AI.

After years of solving data variety, we built Express, a conversational data engineering platform that turns complex data work into simple, prompt-driven pipelines making data engineering accessible to everyone.

Success now hinges on how well businesses share data beyond their walls. Seamless intercompany data flow fuels smarter decisions, faster collaboration, and real growth. In this new era, connection is the key to competitiveness.

Co-founder and CEO at Nexla, discusses how data engineering is evolving to support generative AI—highlighting data quality, governance, and human-in-the-loop workflows for building trustworthy AI systems.

Discover how Nexla and NVIDIA simplify AI adoption with seamless data integration, accelerated GenAI workflows, and scalable solutions for business success.

Even Fivetran, the largest of the ELT vendors, isn’t even close to being a leader….

In the rapidly evolving world of data integration, the recent Nexla Data Integration Summit provided…

From GenAI prototypes to production: the contributions of integration engineers in model management, vector pipelines, RAG workflows, GPT quality control, & LLM governance.

As we step into 2024, we partnered with Database Trends & Applications (DBTA.com) to take…