Dioptra is an MLOps tool that observes models in production, detects where the training data fell short, and mines the best retraining data so your team can maximize model improvements. Dioptra is backed by YCombinator and Engineering Capital. We observe your production serving data, determine where your training data fell short, and help you fix it. Dioptra learns from production patterns, and live, and mines the best retraining data so your team can maximize model improvements. Dioptra helps you explore and visualize your data. Whether you work with images, text, audio, or multi-modal streams Dioptra has you covered. We work with any model and platform as Lightweight SDKs, up and running in minutes, with or without ground truth. Source edge cases to improve text classification recall. A nonprofit increased the recall of their hate speech classification model by automatically sourcing edge cases with Dioptra. Monitor speech transcription bias. A transcription company detected bias against accented female speakers on voice models. Generalize the safety computer vision model. A company deploying safety vision models on the edge was able to source the next data to generalize their models to new locations. Measure your model performance and detect failure modes. Detect and root cause model failure modes with our monitoring and diagnostic frameworks. Optimize your data curation and costs of retraining & labeling. Whether you care about precision or recall or edge cases, tailor fit your data curation to maximize model impact. Control your data quality by automatically identifying potential outliers and mislabeling. Automate your data engine to continuously adapt to the latest production patterns. Get alerted when model performance drops, and trigger curation, labeling, and retraining jobs with our APIs. Keep your data safe and secure.