Capture and query your entire system.
Modality combines a system-level trace database with a powerful query language to give you a complete and continuous picture of your system's operation and behavior.
Systems of any shape and size.
Modality is designed to handle all your system data regardless of its source and complexity. Whether it's sensor samples, high-fidelity microcontroller traces, or high-level application traces, Modality unifies it all into a common abstraction. This way you have a centralized, data rich model of how your systems actually work throughout their lifecycle.View the Docs
Connect all the dots
Modality correlates interactions from every level of your technology stack in a clear and intuitive way.
Follow the breadcrumbs
Data in Modality is richly annotated so you can easily identify its origin.
What's happening in your system? Just ask.
Modality's powerful query language, SpeQTr, lets you ask questions about your system, such as events, actions, and their relationships to one another. This allows you to think and work from the perspective of your systems' high-level behavior, rather than manually combing through log files and low-context database tables to understand what's happening.Learn about SpeQTr
Easily search data for patterns based on causal and time-bound relationships across systems of any complexity.
Reuse what you’ve learned
Leverage SpeQTr queries in your system and integration tests to prevent regressions.
It's like having a Universal Translator for your entire system.
Behavioral insights at a glance
Modality uses the data captured throughout your system's lifecycle to give you a clear understanding of the decisions your system is making, the location of unexpected feedback loops, and how components are interacting.View the Docs
Forks in the road
Automatically identify features of your system behavior, such as branching paths of operation and how often each path is taken.
Reduce, reuse, recycle
Modality can provide analysis results in an annotated SpeQTr query, so you can immediately dig into the relevant data.