Resources
See what teams build, and how they build it.
Customer case studies, engineering deep dives, founder perspectives, and step-by-step guides. Everything here connects back to the work of turning scattered systems into trusted data.
What makes Nexadata hard to replicate isn't the AI
Vibe coding and LLMs both work for moving data, and both are easy. What enterprise integration also asks for is version control, auditability, security, and governance. Here is why you can have both, and why the unglamorous half is the part that takes years to build.
Stop rebuilding the same integration
A founder's take on workflow templates. A template is a standalone file you can keep, hand to another team, and version independently. Fixed, not re-derived.
How a PE-backed clinic group plans across five sets of books without replacing a system
How a three-person finance team at a PE-backed clinic group built one planning model on top of five general ledgers it was never going to consolidate.
Build to MCP once, and the ecosystem plugs in
A founder's take on the MCP Server release. One open protocol replaces the pile of one-off connections, and the reasoning layer keeps it adapting.
How it was built: connecting any OpenAPI system without a static connector
Most integration platforms ship a fixed catalog of connectors. The Connector Copilot reads a system's own API spec and stands up a live connection.
Why our newest release puts a wall between your data and the model
A founder's take on the zero data retention release. Enterprise AI stalls on one fear: that your data trains someone's model. This release removes it.
Watch: connecting, transforming, and mapping data in plain language
A short walkthrough of the three AI copilots that connect a system, reshape its data, and map it to your model, all in plain language with a review step.
Watch: replace Anaplan Connect with no-code, natural-language integration
A demo of moving data into and out of Anaplan without Anaplan Connect scripts. Connect a source, shape the data in plain language, map it to your model.
Watch: connect HubSpot to anything with Nexadata
A three-part walkthrough of extending HubSpot with Nexadata: what it is, a bidirectional integration demo, and cleaning data before pushing it back.
The connector catalog was always the wrong idea
A founder's take on the Connector Copilot beta: connect to a REST API by describing it in plain language, and the long tail stops being a roadmap problem.
Watch: load HubSpot data into Pigment in minutes
A quick demo of integrating HubSpot CRM data directly into Pigment with the AI Copilot: connect to both, map the data, and load it, no custom code.
AI should propose, and a person should approve
A founder's take on the Plan step. The fastest way to make AI trustworthy in the enterprise is a human checkpoint between intent and the work it runs.
Why we moved our reasoning layer to Anthropic Claude
A founder's take on switching the model behind Nexadata to Anthropic Claude and adding bring-your-own-key. We chose the reasoning engine on the merits.
Watch: turn unstructured PDFs into analytics-ready data
A demo of taking invoice and billing data that arrives as PDFs from many vendors and transforming it into structured, tabular, analytics-ready data.
Watch: a full walkthrough of building Anaplan-ready data
A full walkthrough of building Anaplan-ready data: transform, harmonize, and map structured and unstructured data with AI copilots, then load it.
Watch: what is Nexadata?
A brief overview of Nexadata: the no-code platform that lets business users transform, harmonize, and map structured and unstructured data with AI.
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Each Solutions page goes deep on the workflow, sources, and outcomes for a specific team. The posts above link back to whichever one fits.
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