Private AI inference and confidential GPU computing infrastructure
Self-hosted AI infrastructure with measurable returns
Stage
Not given
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Founded
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Based in
US
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Pricing model
Paid
Contact for pricing
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
Model provider support through a single common gateway
Usage attribution to teams, tasks, and agents
Agent workflows in Scala for repositories and code
Apache-2.0 open-source core with enterprise deployment option
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
Full visibility into AI costs attributed to specific teams, tasks and agents
Self-hosted deployment keeps data and models under company control
Model agnostic with support for multiple providers through one gateway
Structured four-step implementation path with clear ownership and baselines
Confidential AI
YABANIN