AI models are only as good as the data that trains them. But getting the right data to your models is harder than it should be.
Your training data is scattered across S3 buckets, Google Drive folders, databases, and real-time streams. Each requires different APIs, authentication, and processing logic.
Direct access to data sources from training environments creates security risks. Hard to audit, control access, or ensure compliance with data governance policies.
Building and maintaining custom ETL pipelines for each data source. No standardization, frequent breakages, and hours spent on data engineering instead of model development.
Real impact on AI development teams
Everything you need to connect, process, and stream data to your AI models
Pre-built connectors for major data sources with automatic authentication, retry logic, and error handling. No custom API integration required.
Process live data streams for real-time model training and inference. Automatic buffering, batching, and backpressure handling for optimal performance.
Enterprise-grade security with encryption in transit and at rest, fine-grained access controls, and comprehensive audit logging for compliance.
Automatic data format conversion, schema mapping, and validation. AI-powered data quality checks and anomaly detection built-in.
Data Input Streams works seamlessly with ZeroCore and CortexFlow to power your AI workflows
Stream data directly to ZeroCore's secure Python sandbox environment for custom model development and experimentation.
Feed high-quality, processed data directly into CortexFlow's ML pipeline for scalable model training and deployment.
See how Data Input Streams powers different AI applications and workflows
Stream transaction data from multiple payment processors to train and update fraud detection models in real-time using CortexFlow.
Process images from Google Drive and real-time camera feeds to train custom object detection models in ZeroCore.
Combine vector database embeddings with document storage to create custom training datasets for domain-specific language models.
Stream sensor data from IoT devices via custom APIs to train predictive maintenance models for industrial equipment.
Aggregate market data from multiple financial APIs to train algorithmic trading models with real-time price feeds.
Process audio files from cloud storage and real-time audio streams to train speech recognition and audio classification models.
Stop struggling with fragmented data sources. Connect, process, and stream your data to AI models with enterprise-grade security and zero-code configuration.
Trusted data pipeline for AI teams