Deploy any machine learning models in minutes
Lowest cold-starts to deploy any machine learning model in production stress-free. Scale from single user to billions and only pay when they use.
Inferless provides detailed call and build logs for monitoring and debugging. Starter tier includes 15-day log retention; Enterprise tier includes 365-day retention. Private Slack support available within 48 working hours. SOC-2 Type II certified with penetration testing and regular vulnerability scans.
Inferless provides custom runtime support allowing users to define containers with specific software and dependencies. Users can customize inference pipelines via app.py and define input schemas. Supports models up to 16GB with NFS-like writable volumes for data sharing across replicas.
Inferless eliminates infrastructure management by providing serverless GPU deployment. Users deploy models from Hugging Face, Git, Docker, or CLI in minutes without provisioning or scaling GPU clusters manually. The platform handles auto-scaling, load balancing, and resource management automatically.
Inferless auto-scales dynamically based on real-time demand with an in-house load balancer. Dynamic batching combines multiple requests to optimize GPU utilization. Supports concurrent scaling up to 5 (Starter) or 50 (Enterprise) GPU instances with minimal overhead.
Inferless charges per-second for actual compute used with no idle costs. Auto-scaling scales from zero to hundreds of GPUs on demand. Users report ~80% cost savings and ~90% savings in specific cases. Pay only when models are running; minimum replicas can be set to zero.