BF-Q Inference API
High-throughput REST API for deploying and scaling custom AI models with sub-millisecond latency. Supports PyTorch, TensorFlow, and ONNX formats.
Overview
BF-Q Inference API is a fully managed, cloud-native model-serving platform designed for enterprises that need deterministic performance at any scale. Built on a distributed inference engine, it handles thousands of concurrent requests while maintaining p99 latency under 10 ms. The API natively supports PyTorch, TensorFlow, ONNX, and JAX models, with auto-scaling, canary deployments, and A/B testing baked in.
Use Cases
- Real-time recommendation engines
- NLP API services (classification, summarisation, generation)
- Computer-vision pipelines in production
- Fraud detection & anomaly scoring
Key Features
- Sub-10 ms P99 inference latency
- Auto-scaling from 0 to 10 000 RPS
- Multi-framework: PyTorch, TensorFlow, ONNX, JAX
- Canary & A/B deployment strategies
- Built-in model versioning & rollback
- OpenTelemetry-native observability
- gRPC & REST endpoints
- Edge deployment support (WASM / TensorRT)
Details
- Category
- AI Platform
- Released
- January 15, 2024
Get Started
Talk to our product team
Other Products
QuantumLedger SDK
Open-source SDK for building quantum-resistant blockchain applications. Features post-quantum cryptography and smart contract templates.
NeuroCraft Studio
Visual IDE for designing, training, and deploying neural network architectures. Drag-and-drop interface with real-time performance profiling.
SecureVault Enterprise
Enterprise-grade secrets management and PKI solution with AI-driven threat detection and automated certificate lifecycle management.