Lepton AI
Build and deploy high-performance AI applications at scale with zero infrastructure management.
The AI-Native Distributed SQL Engine for RAG and High-Performance Predictive Analytics.
DeepSQL represents the 2026 frontier of database technology, functioning as a high-performance, distributed relational database engine with native AI orchestration capabilities. Unlike traditional SQL databases that require external middleware for machine learning, DeepSQL embeds inference engines directly into the query execution plan. This architecture allows for real-time model serving and vector operations within standard SQL syntax (e.g., SELECT PREDICT...). Built on a distributed consensus protocol, it maintains ACID compliance while scaling to petabyte-level workloads. For the 2026 market, DeepSQL's primary advantage lies in its 'Zero-ETL' approach to AI, where data remains within the transactional layer while being accessible for LLM context windows and vector-based retrieval. It significantly reduces latency in Retrieval-Augmented Generation (RAG) pipelines by co-locating metadata, relational data, and vector embeddings in a single unified storage layer, optimized for both OLTP and OLAP workloads with an AI-first priority queue.
Executes ONNX and TorchScript models directly within the database engine during query runtime.
Build and deploy high-performance AI applications at scale with zero infrastructure management.
The search foundation for multimodal AI and RAG applications.
Accelerating the journey from frontier AI research to hardware-optimized production scale.
The Enterprise-Grade RAG Pipeline for Seamless Unstructured Data Synchronization.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Combines BM25 keyword ranking with HNSW vector similarity in a single execution plan.
Distributes vector index builds across multiple compute nodes to handle billions of embeddings.
Maintains historical versions of vector embeddings for time-series semantic analysis.
Change Data Capture that automatically triggers embedding updates and LLM cache invalidation.
Integrated differential privacy layers that mask PII during AI-driven analytical queries.
Automatically moves infrequently accessed vector data to cold S3-compatible storage.
Latency in fetching user history and converting it to recommendations via external ML services.
Registry Updated:2/7/2026
Detecting fraudulent patterns across millions of transactions in sub-second timeframes.
Managing billions of legal clauses with semantic search and strict versioning.