Our Blog

October 15, 2025
95% of AI Pilots Fail, and Bad Data is the Culprit

Shashank Saxena, Pantomath CEO, unpacks what’s really behind AI’s 95% failure rate — and why it has nothing to do with model accuracy.

January 18, 2024
Data startup Pantomath more than triples in size with new office in Mason

A Greater Cincinnati startup has relocated to a new office in the suburbs, underscoring its fast growth in a move that more than triples its physical footprint.

October 30, 2023
Top Startups and Tech Companies in Cincinnati to Watch in 2024

Cincinnati may be known for its chili, but it’s also home to beautiful architecture, great cost of living, wonderful people, and yes, you guessed it, great startups.

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Data in Motion Series, Part 1: What is Data in Motion?

Traditional platforms treat data as a static resource which no longer works for today's data demands. Learn more about the importance of monitoring BOTH data at rest and data in motion.

Builder
Observability & Traceability
Why Data Observability is Essential for Generative AI (GenAI)

Discover the real-world benefits and how companies can optimize GenAI applications by implementing robust data observability practices.

Strategist
AI Readiness
Why Most Data Observability Platforms Fall Short

In boardrooms across the globe, executives are grappling with a painful truth: the data tools they've invested in aren't delivering on their promises. Learn why in this blog.

Strategist
Observability & Traceability
The 5 Most Common Data Management Pitfalls

There are five common mistakes that teams often make on their journey toward data observability. Learn how to avoid them!

Operator
Incident Management
10 Essential Metrics for Effective Data Observability

You can’t simply implement data observability and then hope for the best. Learn about the top 10 essential metrics to make your business thrive.

Builder
Observability & Traceability
The Evolution of Data Quality: Why Data Observability is Key

Data quality has a long history, dating back at least to mainframes in the 1960s. Learn about the path Data Quality has taken, and where it's headed.

Strategist
Data Reliability

Automated data operations across your data stack