TrueEra AI Observability Helps Drive AI Quality and Performance

TruEra is releasing TruEra AI Observability, a full-lifecycle AI observability solution providing monitoring, debugging, and testing for ML models in a single SaaS offering along with covering both generative and traditional (discriminative) ML models.

According to the company, the solution is aimed to meet customer needs for observability across their full portfolio of AI applications, as interest in developing and monitoring LLM-based apps accelerates.

Initial development of LLM-based applications has dramatically increased since the launch of ChatGPT. However, LLM-based applications have well-known risks for hallucinations, toxicity, and bias.

TruEra AI Observability offers new capabilities for testing and tracking LLM apps in development and in live use, so that risks are minimized while accelerating LLM app development. The product capabilities were informed by the traction of TruLens—TruEra’s open source library for evaluating LLM applications.

According to the company, until the launch of TruEra AI Observability, observability tools generally focused on providing ML operations (MLOps) support for development or production, but not both. TruEra is the only software vendor providing a solution for driving high-performing, trustworthy AI across the full model lifecycle.

TruEra, which previously only offered its full-lifecycle observability solutions either on-premises or virtual private cloud, now provides customers with the flexibility of SaaS or deploying within their own private cloud.

“TruEra’s initial success was driven by customers in banking, insurance, and other financial services, whose high security requirements were well met by existing TruEra on-prem solutions,” said TruEra co-founder, president, and chief scientist Anupam Datta. “Now, with TruEra AI Observability, we are bringing ML monitoring, debugging, and testing to a broader range of organizations, who prefer the rapid deployment, scalability, and flexibility of SaaS. We were excited to see hundreds of users sign up in the early beta period, while thousands have engaged with our hands-on educational offerings and community. The solution brings incredible monitoring and testing capabilities to everyone developing machine learning models and LLM applications.”

TruEra AI Observability helps data scientists and ML engineers to:

  • Monitor models in production via customizable dashboards to ensure that they meet KPI and performance targets, as well as prevent failure scenarios such as model drift
  • Debug quickly, using powerful feature and segment root cause analysis (RCA)
  • Automatically run performance, quality and responsible AI tests to efficiently evaluate AI applications, validate improvements, and prevent regressions
  • Proactively identify predictive and generative AI application improvements using automated performance and quality analysis, RCA, AI explainability and model comparison
  • Identify high-impact problems and then debug and optimize models quickly
  • A comprehensive approach to AI Observability – with powerful root cause analysis

Tru Era’s full lifecycle AI Observability approach ensures that teams are able to quickly identify emerging issues, isolate their root causes, and then debug and test quickly.

TruEra also introduced a free version of TruEra AI Observability focused on model testing, debugging, and evaluation.

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