Private AI inference and confidential GPU computing infrastructure
Pick your AI model based on evaluation results, not intuition
Stage
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Founded
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Based in
US
US
Pricing model
Paid
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Pricing
Confidential Inference: DeepSeek V4.1 Flash $0.30 input and $1.20 output per 1M tokens; Kimi K3 $3.00 input and $15.00 output per 1M tokens; GLM 5.3 $1.40 input and $4.40 output per 1M tokens; Qwen3.8 27B $0.30 input and $1.80 output per 1M tokens. Confidential VMs: B300 at $7.50 per GPU-hour, B200
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Key features
OpenAI-compatible endpoint for private LLM inference
Hardware-encrypted VMs on Intel TDX, AMD SEV-SNP and NVIDIA GPUs
Client attestation verification before sending requests
Support for multiple open-weight models including DeepSeek, Kimi, GLM, Qwen
Confidential Kubernetes for data center scale deployments
Confidential training and fine-tuning on licensed stack
Root access over SSH to confidential VMs
Encrypted GPU communications with NVLink encryption on B200 and B300
Confidential agents runtime support
Prompt caching with cached input billing
Automatic model routing based on evaluation results
GitHub repository integration for eval workflows
Stores evidence of evaluation results
Automatic re-evaluation when new models are released
Dashboard for monitoring routes
MCP server integration with ChatGPT, Claude, and Cursor
Configurable evaluation checks and criteria
What makes it different
Prompts and model weights verified by clients with cryptographic attestation before any data is sent
Operator-blind inference: data remains unreadable to the company and hosting provider
Flexible deployment: choice of hosted cloud, rented VMs, or licensed stack on own infrastructure
Open-weight models only, no closed-source frontier models
Full cryptographic verification stack including open-source tools
Test your own LLM applications against real models automatically
Routes requests to the best-performing model in real time
Automatically updates routing when new models are released
Keeps your eval results and configurations under your control