What If Your Case Studies Could Talk Back?
We’re opening up a new opportunity to explore AI-powered simulations to a small group of higher ed instructors.
Participants will get 90 days of access to the Mixta authoring platform, along with a strategy session led by a learning scientist. The goal is simple: build and run a simulation in a real course.
Build Capable and Yet Analytics Announce Partnership to Bring Learning into the AI Age… Without the LMS
Build Capable and Yet Analytics have announced a new partnership aimed at helping organizations design, deliver, and scale learning in the AI era without relying on a traditional Learning Management System (LMS).
Three Ways Mixta Changes the Game for Simulation
Mixta is one of the few things that actually feels like a step forward, not because it adds AI to simulation, but because it changes what simulation is.
Meet Mixta: AI-Powered Simulation Built through Learning Engineering
Mixta is one of the most compelling advances in simulation for the learning space that we’ve seen. It was designed by learning scientists and was developed through a learning engineering mindset.
We think that by this time next year, it will be the most commonly used simulation platform in the learning and training space.
SQL LRS Is Widely Adopted. Now Let’s Talk About What That Means.
Many organizations today are running SQL LRS in production environments.
That means it is collecting and processing mission-critical data, feeding downstream analytics and reporting systems, and supporting compliance, certification, and operational decision-making.
In other words, SQL LRS is not a side tool. It is part of the system of record.
At the same time, many of these deployments are operating without a formal support relationship.
That creates a gap. And it’s one that’s easy to overlook until it matters.
SQL LRS and the Future of Learning Data: From Storage to Intelligence
We are now operating in an AI-driven landscape where raw activity data is no longer sufficient. Logging events is easy. Extracting meaning is hard.
Machine learning systems don’t need more noise—they need:
Structured signals
Verified outcomes
Aggregated performance
Deterministic logic
In other words, they need preprocessed intelligence.
SQL LRS is designed to deliver exactly that.
Free Is Not Free: The Hidden Cost of “Free” Infrastructure
Entire ecosystems of modern software now advertise free tiers as the starting point for adoption. For experimentation and early development, these offerings can be incredibly useful. They lower barriers, encourage exploration, and help teams get projects off the ground quickly.
But there is a subtle shift that happens as systems mature. What begins as a convenient free tool can gradually become something far more significant: the place where an organization’s data lives.
At that point, the economics of “free” start to look very different.
Because infrastructure—real infrastructure—has never actually been free.
Two Game-Changing AI Advantages of SQL LRS
For organizations working with learning and performance data, the biggest barrier to using AI effectively is rarely the models themselves—it’s the friction between data collection, transformation, and usable features.
This is where SQL LRS creates a significant advantage.
From LMS Lock-In to Enterprise Analytics: Unlocking Partner Training Data with SQL LRS and LRSPipe
A few years ago, big LMSs started shipping with the availability of their own internal Learning Record Stores. But more often than not, this only resulted in more frustration. Because even when the LMS captured rich activity data using xAPI, the data remained locked inside the system’s built-in LRS. Just getting access to your own data became an endless game of phone-tag.
So, while the training data exists, businesses can't easily use it.
This is where LRSPipe and SQL LRS provide a powerful solution.
Ten Ways SQL LRS Turns xAPI Data Into AI-Ready Intelligence
Many Learning Record Stores still treat xAPI as a storage format: collect statements, store them, display a dashboard. That was sufficient when reporting was the goal. But AI systems don’t need dashboards. They need clean signals, structured sequences, and verified outcomes.
Mixta.ai and the Rise of 4th Generation Simulation Platforms
Simulation has always been one of the most powerful tools in learning and workforce development.
But not all simulations are created equal. From static branching scenarios to fully immersive AI-driven conversations, the technology has evolved in waves.
Mixta.ai has developed what we can confidently call a 4th generation simulation platform — AI-enabled, analytics-native, and architected for transparency from the ground up.
Why xAPI Is a High-Value Data Format for AI in Learning
Most AI initiatives in learning focus on surface-level capabilities.
Few focus on data foundations.
But AI doesn’t magically create insight. It amplifies whatever data architecture you give it.
If your activity data is fragmented, mutable, and loosely defined, AI will amplify that chaos.
If your activity data is:
Structured
Deterministic
Immutable
Standardized
AI can become a durable, scalable capability.
That’s where xAPI shines.
Let’s Get Real About xAPI
If you’ve spent any time in the learning technology space, you’ve probably encountered xAPI — and you’ve probably also heard someone struggle to explain why it matters.
That’s not because xAPI lacks value.
It’s because xAPI has been, at various points in its life, too early, too narrowly positioned, too slow to standardize, and too misunderstood.
Let’s talk about it.
INFERable: Leveraging xAPI to power AI Inference from Learning Activity Data
Imagine connecting xAPI instrumentation with real-time AI inference. INFERable is doing it. And they are helping organizations move from capturing learning activity to optimizing learning performance.
From Job Descriptions to Task Portfolios
A modular blueprint for early‑career resilience and organizational talent optimization in the wake of AI
What is SQL LRS and Why Does Your Organization Need It?
Enterprise learning organizations are increasingly looking to harness the power of learning data to improve training, performance, and decision making. But with the vast amounts of learning activity data being generated across various platforms and systems, managing and analyzing that data can quickly become overwhelming. This is where SQL LRS comes in.
Pro Tip: Automating Pre-Requisite Checks and Course Eligibility with SQL LRS Reactions
Did you know that you can use Reactions in SQL LRS to automate pre-requisite checks and course eligibility?
Let’s talk about Yet’s xAPI Advisory Services — for XR Learning Companies
XR is a perfect use case for xAPI. Because most events that occur within an XR learning experience are activity-based, it’s easy to instrument an XR system to produce activity data aligned with xAPI. And because so much of the interesting information about learning that occurs in XR is behavioral and experiential, xAPI’s semantic data model — purpose-built for activities that occur during learning — is both a clear fit and a natural value-add.
Yet Analytics’ solution now available through the Department of Defense CDAO’s Tradewinds Solutions Marketplace - SBIR Aisle
Yet Analytics, a leading provider of enterprise learning data software solutions today announced that its solutions package for the Total Learning Architecture is now available through the SBIR Aisle program from the Chief Digital and Artificial Intelligence Office’s (CDAO) Tradewinds Solutions Marketplace.
Unlocking B2B Learning Data: How Yet Analytics Supports Interconnection and Accessibility for XR and LMS Providers
Whether you're delivering immersive XR training experiences or managing complex learning requirements through an LMS, the ability to design, implement, and operationalize xAPI is no longer a “nice to have” – it’s a competitive advantage.