Saket Saurabh

In this second episode of DatAInnovators & Builders, BigPanda’s Alexander Page shares how his team designs AI agents that internalize corrections, evaluate tool use, and scale reliably in production.

In this second episode of DatAInnovators & Builders, Ashish Thusoo breaks down how CurieTech AI uses benchmarks-first discipline and AI-driven build loops to achieve 70–80% productivity gains.

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.

In this first episode of DatAInnovators & Builders, Databricks’ Robin Sutara reveals why generic AI training doesn’t stick and how persona-based enablement drives real adoption.

In the News: 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.

In the News: 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.