Monitor Your Models, Trust Your Inferences
How do you know your machine learning models are effective in production? Track model health—status, requests, resource usage, data drift—for your entire catalog with the Striveworks MLOps platform.
View all models in production and drill down to see individual performance for both unstructured and structured data models. Then, use our integrated remediation tools to resolve problems as quickly as they arise.
Comprehensive Performance Monitoring
Striveworks provides observability across every phase of your machine learning life cycle.
Monitor Your Full Model Catalog
Investigate Individual Model Performance
Detect—and Defeat—Data Drift
Understand Performance Across All Available Models
Monitor your entire catalog of models and inference servers from development through production with Striveworks. Easy-to-read dashboards let you track all models, so you can monitor deployment status, data drift, requests, uptime, and more at a glance.
Filter dashboards by:
- Model task (object detection, image classification, named-entity recognition)
- Framework
- Architecture
- Evaluation metrics
Observe crucial deployment details:
- Data drift alerts
- Average latency
- CPU/GPU/RAM usage
- Total requests
- Requests per second
Drill Down Into Individual Model Health
When a model’s performance raises eyebrows, swiftly drill down to investigate the specifics. Explore both real-time data pipelines and model training details:
- Failed and successful requests
- Training hyperparameters
- Training dataset versions
- Recent project contributors
Automate Drift Detection on Unstructured Data
Other platforms struggle to detect drift on data types like images and text. Striveworks is built for unstructured data first, delivering best-in-class tools that show you where and why your models are underperforming.
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Automate drift detection for computer vision and natural language processing (NLP) models
- Detect drift in real time or batch on a custom cadence
- Understand drift characteristics down to individual datums with our inference store
Take Immediate Action
![Man working on a laptop fine-tuning models](https://www.striveworks.com/hs-fs/hubfs/Web%20Pages/Model%20Performance%20Monitoring/202405-W-Monitoring-VP-TakeAction.png?width=800&height=600&name=202405-W-Monitoring-VP-TakeAction.png)
Underperforming models must be fixed or retired before they impact business decisions. Striveworks makes model remediation fast and easy.
Use the best data—your production data—to retrain your models. Easily build new datasets from real-world data to quickly retrain models and to evaluate and compare performance across models.
Monitor, retrain, and evaluate—that’s remediation.
![Man working on a laptop fine-tuning models](https://www.striveworks.com/hs-fs/hubfs/Web%20Pages/Model%20Performance%20Monitoring/202405-W-Monitoring-VP-TakeAction.png?width=800&height=600&name=202405-W-Monitoring-VP-TakeAction.png)
Deep Dive Individual Inferences
![The Striveworks user interface showing a model's inference history](https://www.striveworks.com/hs-fs/hubfs/Web%20Pages/Model%20Performance%20Monitoring/202402-W-ModelPerformance-ValueProp-ExploreModelInferences-800x600.png?width=800&height=600&name=202402-W-ModelPerformance-ValueProp-ExploreModelInferences-800x600.png)
The Striveworks inference store gives your team full access to your entire inference history. Examine the data and metadata of all model outputs for the most granular understanding of model performance and to identify opportunities for improvement.
- Validate inferences and inspect data flagged as out of distribution.
- Search and filter inferences based on model architecture, labels, drift metrics, and other metadata.
- Assemble and use training datasets from recent production data.
![The Striveworks user interface showing a model's inference history](https://www.striveworks.com/hs-fs/hubfs/Web%20Pages/Model%20Performance%20Monitoring/202402-W-ModelPerformance-ValueProp-ExploreModelInferences-800x600.png?width=800&height=600&name=202402-W-ModelPerformance-ValueProp-ExploreModelInferences-800x600.png)
Related Resources
![Model Drift and The Day 3 Problem preview image](https://www.striveworks.com/hs-fs/hubfs/Landing%20Pages/Model%20Drift%20and%20the%20Day%203%20Problem%20LP/Model%20Drift%20and%20The%20Day%203%20Problem%20Feature%20Image%20PNG.png?width=1200&height=628&name=Model%20Drift%20and%20The%20Day%203%20Problem%20Feature%20Image%20PNG.png)
Model Drift and The Day 3 Problem
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