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#AI adoption is a behavior change 👫 problem, not a technical problem. Download this AI adoption scorecard 🎯 to help you measure AI progress in a way that drives better decisions. Move beyond simple vanity metrics and establish an “operating system” for AI adoption, focusing on the leading signals that predict success. Download now using the link in the comments below: ⬇️ #digitaltransformation #AIadoption #AIforbusiness

Join our webinar on Mon, Nov 24 at 10am PT with Dr. Tim Oates, Co-Founder and Chief Data Scientist at Synaptiq, to learn practical ways to evaluate value of AI, align results with organizational priorities, and build a business case that earns executive buy-in. Register today using the link in the comments ⬇️ In this webinar, you will learn: - How to define success metrics that tie AI performance to business goals - Methods to evaluate the short and long-term returns of AI initiatives - Strategies for communicating AI value to senior leadership and stakeholders #roiofaiI #AIForBusinesss #DigitalTransformation

Discover how Synaptiq helped a healthcare company integrate data sources, improve forecasting, and enhance operational efficiency across facilities nationwide.

Discover how Synaptiq helped predict reherniation risks faster and more accurately with machine learning and vision.

How Do You Know If an AI Model Actually Works on Your Data? Almost every organization runs on documents: contracts, clinical notes, claims, filings, reports, policies, correspondence. Every AI vendor says their model can read them. But the question that matters is narrower and harder: how well does it work on our documents, for our tasks, measured how, and compared with what? What if you could measure any AI system on your own tasks, under conditions you control, and get numbers you can trust? Synaptiq has built an evaluation bench on Databricks to do exactly that. You describe in plain English what you want to measure, such as “how well does this model extract key terms from these documents?” The bench finds suitable data and checks whether the metrics can actually be computed from it. Then it either scores the run or tells you what’s missing and what it would cost to fill the gap. See a demo of how Synaptiq's evaluation bench works with our Chief Data Scientist, Dr. Tim Oates: Wednesday, October 28, 2026 2:00 PM EST Register today: https://hubs.la/Q04Ck8dG0 We’ll cover: - The why: why leaderboard scores and vendor claims don’t tell you how a model will perform on your dataThe approach: how we define what “measurable” means. Datasets provide certain kinds of ground truth and metrics require certain kinds, and that simple rule keeps the bench from producing flattering numbers. - The demo: public document collections and their annotations governed in Unity Catalog, models called through Databricks’ model gateway, and every run, including failed ones, logged back to Delta tables so every score can be traced to the items behind it. - The lessons: benchmark contamination, how a single accuracy number can hide the errors that actually matter in your domain, and why a “relevant-looking” dataset often can’t support the metric you want FYI The demo uses only public datasets, and the same pipeline can be pointed at an organization’s own governed data. #AIforbusiness #AIreadiness #Datareadiness #BusinessIntelligence

Are you in healthcare and looking for ways to improve your operations and revenue cycle management? Want: Less scheduling friction ? Less workflow stress ? Northstar Anesthesia collaborated with Synaptiq to put its Databricks ecosystem to work, streamlining staff scheduling and making day-to-day operations more efficient. For healthcare leaders looking to simplify workforce management, this is a practical example worth exploring. See how they did it: https://bit.ly/47jvJEx #HealthcareIT #HealthcareInnovation #HealthTech