The Future Is Not One MCP Server Per Application
A separate MCP server per app doesn’t scale. See why task-specific, governed MCP servers across your systems are the future, with Nexla MCP Studio.
A research-backed framework for evaluating LLM-generated data transformations. Learn how datasets, sandboxed execution, and automated judging reveal failure patterns and model performance across real-world data engineering tasks.
Explore how Express.dev makes AI agents capable of generating rich, interactive UI for structured data workflows. From XML-driven forms to real-time validation and OAuth flows, generative UI turns chat into a truly collaborative experience.
While it is true that AI offers enormous opportunities for innovation and success, its reliance on personal data raises urgent concerns about privacy, ethics, and governance
A podcast for data leaders looking for real conversations on AI adoption and data architecture, hosted by Nexla CEO Saket Saurabh.
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.
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.
Learn how to choose the right automated ETL tools for your startup. Discover key selection factors, compare top platforms, and find solutions that scale with your business growth.
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.
When data quality drops, revenue follows. Automated ETL fixes that by eliminating errors, enforcing standards, and ensuring consistency across systems to deliver trustworthy analytics and business insights.
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.
The Fivetran–dbt merger is creating ripples across the data world. Customers face rising costs and vendor lock-in, while platform giants gain leverage. Learn what the market really thinks and how to stay flexible amid the change.