Visier Engineering Blog

This blog covers how Visier builds, operates, and evolves the technology behind its analytics and AI platform.

Latest post

Why Visier’s Semantic Model Makes Hard Analytics Easier for Humans and AI Agents

How Visier’s semantic model turns time, relationships, concepts, and metrics into shared analytical context for human analysts and AI agents.

Semantic modeling • Temporal analytics • AI context

Earlier posts

Building and Maintaining Visier DB: One Cached Copy, Security, and Engineering Discipline

Part 3 and conclusion of the series on how Visier’s cache-copy architecture preserves source-of-truth semantics and how test automation, code quality, and dependency discipline help keep Visier DB sustainable.

Cache-copy architecture • Security and governance • Engineering discipline

Inside Visier DB: Event Streams, Temporal Queries, Metrics, and Cohorts

Part 2 of the series on how Visier ingests data as states and events, executes temporal analytics in Visier DB, and models metrics and cohorts as reusable time-aware concepts.

Event streams • Temporal queries • Metrics and cohorts

Why Analytics Breaks Under Change

Part 1 of the series on why row-centric BI pipelines become fragile under schema drift, source churn, and temporal complexity and how Visier’s subject model addresses that problem.

Data modeling • Temporal analytics • Platform architecture

About Visier

Visier builds AI-powered workforce intelligence. Its platform brings people and work data together so organizations can make better decisions across hiring, mobility, compensation, productivity, and organizational change.

What to expect

For product information or company news, visit Visier’s public website.