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.
How a multi-entity finance team collapsed five ERPs into one planning model
A finance organization running five general ledgers across acquired entities now closes on one trusted model. Here is how they connected, harmonized, and mapped the data without a custom integration project.
We shipped an MCP server, so now your AI agents can run real data work
A founder's take on the MCP Server release. The conversation moved from chatbots to agents that do work. With Model Context Protocol support, an agent can now reach into Nexadata, run a governed pipeline, and get trusted data back.
How it was built: connecting any OpenAPI system without a static connector
Most integration platforms ship a fixed catalog of connectors. We took a different path: the Connector Copilot reads a system's own API specification and stands up a live connection. Here is the engineering behind it.
Why our newest release puts a wall between your data and the model
A founder's take on the zero data retention release. AI in the enterprise stalls on one fear: that your data ends up training someone's model. We built the release that removes the fear instead of asking you to accept 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 driven by plain-language instructions with a human 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, and map it to your model, no code required.
Watch: connect HubSpot to anything with Nexadata
A three-part walkthrough of using Nexadata to extend HubSpot: what it is, a bidirectional integration demo, and using Nexadata as a data source to clean and harmonize data before pushing it back into HubSpot.
The connector catalog was always the wrong idea
A founder's take on the Connector Copilot beta. Instead of shipping a fixed list of integrations, we shipped the ability to connect to a REST API by describing it in plain language. 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 release that added the Plan step and plain-English business logic. The fastest way to make AI trustworthy in the enterprise is to put a human checkpoint between the model's intent and the work it runs.
Why we moved our reasoning layer to Anthropic Claude
A founder's take on the release that switched the model behind Nexadata to Anthropic Claude and added bring-your-own-key. The reasoning engine is the most important component we run, so we chose it on the merits and gave customers control of it.
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 longer walkthrough of Nexadata as a no-code data quality platform: transform, harmonize, and map both structured and unstructured data with AI-powered copilots, ready for Anaplan.
Watch: what is Nexadata?
A brief overview of Nexadata, the no-code data quality platform that lets business users transform, harmonize, and map structured and unstructured data with AI-powered copilots.
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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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