Smart Data Discovery

Training high-performance models requires more than just more data — it requires the right data. Smart Data Discovery is Javelin AI’s intelligent indexing and surfacing system designed to help teams identify and extract the most impactful data points from massive, often noisy, datasets.

Key Capabilities:

• Impact Scoring & Relevance Ranking: Automatically scores data segments based on predicted utility to downstream model performance. Techniques include influence functions, loss-based prioritization, and model uncertainty estimation.

• Semantic Clustering & Deduplication: Group similar documents or utterances to reduce redundancy, identify low-value examples, and improve diversity in your dataset.

• Data Slice Exploration: Create and manage dynamic slices based on metadata, embeddings, keyword queries, or performance metrics. This allows for targeted inspection and fine-tuning of subsets that influence specific behaviors.

• Outlier & Anomaly Detection: Detect edge cases or mislabeled data that may introduce instability into the model. Integration with model metrics allows identification of "hard" examples that degrade performance.

• Signal-to-Noise Optimization: Filter out irrelevant or low-impact examples that contribute to training cost but not model improvement — enabling higher efficiency with fewer labeled examples.

Supported Workflows:

• Identifying the 5% of a dataset that drives 80% of performance gains

• Pinpointing failure cases in model predictions for corrective feedback

• Extracting domain-specific examples for targeted fine-tuning

• Building clean, balanced datasets with diverse examples and minimal noise

Smart Data Discovery enables teams to operate with surgical precision — transforming raw data into a high-leverage asset for model development, evaluation, and alignment.