Ephany is a standardized framework for your asset data that you can own, extend, and build upon. Your organization can finally own your data and the source code to boot.
Most organizations treat naming conventions as a manual chore, which is why their catalogs eventually become a mess of “2-Sided” vs “Two-Sided” inconsistencies. I decided to stop fighting that battle by hand and used AI to build a logic-based “wrangler” script, then used the Ephany API to push those standards across our entire catalog in seconds.
Today, we’re excited to introduce Ephany Framework, an open-source platform for managing assets, their metadata, and their relationships to projects. This is the backbone of the entire Ephany ecosystem: the data structure, the REST API, and the relational logic that ties it all together.
Artificial intelligence might seem like magic, but even magic needs rules. One of the biggest misconceptions about AI is that it always gets things right.…
Despite the rise of e-commerce, physical retail in the U.S. is proving far more resilient than many expected — especially in the big-box and grocery sectors. Over the past three years, retailers like Walmart, Target, Costco, and Aldi have not only maintained but strategically expanded their physical footprints. While 2022 and 2023 saw more store openings than closures, 2024 brought a wave of store closings driven mostly by bankruptcies and weak specialty chains — not the major players in grocery or big-box retail.
Building out physical retail stores is a high-stakes game—one where a single misstep can cost thousands (or even millions). Have you ever had a store…
McDonaldization describes how industries optimize for efficiency, predictability, uniformity, and control. This principle doesn’t just apply to burgers, it’s the secret sauce behind how companies like Walmart, Dollar General, and Wegmans scale their physical stores to thousands of locations worldwide.
Imagine your home is overflowing with clutter. You hire a professional organizer who tidies everything up—but without proper shelves and storage, the clean items just end up in a neat pile on the floor. That’s what happens when you rely solely on AI to clean up your asset data, especially when managing furniture, fixtures, and equipment (FF&E) for owner-furnished items in repeatable commercial spaces.
Let me tell you a little secret about working in BIM: the more data you cram into your model, the more of a nightmare it becomes to manage. Early in my career as a BIM Manager, I thought it was smart to add as much data as possible to Revit Families for owner-furnished items (OFI).
It’s 2025 and we’re still doing manual data entry? Check out this video demo of how Kit, our AI copilot in Ephany, is now able to solve this problem.