© 2025 Constellation AI, Inc.
The Constellation AI Platform
We're creating entirely new paradigms in data ingestion, routing management, regulatory compliance and environment resource management. Learn more below.
Product Background
The Constellation AI platform is built by an experienced team of enterprise software experts with a history of building high performance mission critical applications at scale.
We deliver proprietary, event-driven-architecture with high concurrency that enables customers to accelerate time-to-value and reduce the training and operations cost of AI models while maintaining data privacy and governance in their own environments.
Product Features
Resource Conservation
Using advanced concurrency management, adaptive quantization, real-time pruning and real-time hardware orchestration, the Constellation AI Platform delivers measurable reductions in resource usage for model training, retrieval-augmented generation and inference operations.
Security, Privacy & Governance
Our "security and privacy first" architecture ensures that customers can maintain control of their data, in their own environments while applying relevant regulatory and compliance policies to it, including automated GDPR data removal when needed.
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Security teams can bring or manage their own encryption keys, or make use of our quantum-proof encryption service, built right in.
Model Optimization
Each piece of discrete data within our platform is directly traceable to model performance impacts, enabling our platform to dynamically adapt the quantization and weighting of data as it flows through the services. For data that negatively impacts models, the platform will automatically re-quantize and re-weight until performance is stabilized, or full fidelity data is ingested.
Our platform also optimizes for model performance in context of the hardware resources available and dynamically adjust CPU, GPU, TPU or QPU configurations & allocations for peak efficiency.
Model Explainability
Constellation AI's Governance modules enable immutable origin tagging and full lifecycle traceability of each piece of data in the platform, how it was used, what regulatory or compliance policies apply to it and the historical performance impact it had on a deployed model.