Inferless offers a serverless GPU inference platform that lets AI developers deploy models from Hugging Face, Git, Docker, or a CLI with a single click. The service automatically scales GPU instances from zero to hundreds based on real‑time demand, billing per second to eliminate idle costs, and provides enterprise‑grade security with SOC‑2 Type II compliance.
Funding
$3.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Machine learning teams often face high upfront costs, idle GPU capacity, and operational overhead when deploying inference workloads, especially under variable or spiky demand. Traditional GPU clusters require manual provisioning, lead to underutilized resources, and make it difficult to scale quickly without large capital expenditure.
Solution
Inferless provides a serverless GPU inference platform that lets users deploy models from sources such as Hugging Face, Git, Docker, or a CLI with a single click. The service automatically scales GPU instances from zero to hundreds based on real‑time request volume, eliminating idle capacity and reducing infrastructure management. Billing is per‑second, so customers only pay for the compute they actually use, and a free credit tier enables rapid experimentation without upfront costs. Models run in isolated, encrypted environments and are protected by SOC‑2 Type II certification, penetration testing, and regular vulnerability scans. The platform supports a range of NVIDIA GPUs (A100, A10, T4) and can host custom models up to 16 GB, with dynamic batching to maintain low latency even under heavy load.
Target Audience
Primary users are AI developers, data‑science teams, and product engineers at fast‑growing startups or large enterprises who need on‑demand GPU inference without managing infrastructure.
Features
- One‑click deployment from Hugging Face, Git, Docker, or CLI with automatic redeploy
- In‑house load balancer that auto‑scales GPU instances from zero to hundreds on demand
- Per‑second billing and free $30 credit to eliminate idle costs and lower total spend
- Support for NVIDIA A100, A10, and T4 GPUs with shared and dedicated options
- Dynamic batching and model size support up to 16 GB for consistent low‑latency inference
- SOC‑2 Type II compliance, penetration testing, and encrypted-at‑rest storage for enterprise security
- Unlimited webhook endpoints and configurable concurrency limits for startups and enterprises