AI compute from the edge to cloud with breakthrough efficiency and sustainability
Confidential and open LLM inference for agents, paid per request in USDC
Stage
Not given
Not given
Founded
2022
Not given
Based in
US
US
Pricing model
Not given
Paid
Pricing
Not given
LLM inference: Models priced per million tokens input and output, ranging from $0.043 to $3.63 for input and $0.22 to $18.15 for output (e.g., Qwen3.8 27B route C: $0.043/$1.375, Kimi K3 route B: $3.63/$18.15). Virtual machines: Starter $0.159-$0.169/hour, Standard $0.318-$0.335/hour, Pro $0.636-$0.
Key features
Analog in-memory computing architecture
Multiple form factors from chiplets to PCIe cards
20x higher efficiency than industry-leading products
9x higher compute density than industry-leading products
10x lower total cost of ownership for inference
100x lower CO2 emissions versus cloud
On-device and local processing for data privacy
Seamless edge-to-cloud orchestration
Attested confidential model execution on Intel TDX hardware
Open tier LLM inference without attestation
Price shown before model execution
No account or API key required
Virtual machines for AI swarms by the hour
Phone numbers and calling with metered pricing
Email inboxes with sending allowances
Access via HTTP without signup
416 open source models available
What makes it different
Only scalable analog in-memory computing platform overcoming fundamental limits of digital approaches
Unmatched efficiency enabling advanced AI models without power or space constraints
Extreme cost savings with 10x lower TCO compared to cloud-based inference
Drastically reduced environmental impact with 100x lower CO2 emissions
Leadership team with 20+ years of AI hardware and semiconductor innovation
Encrypted memory and disk in processor with no company access to keys
Price transparent and settled before request execution
No account signup, payment via wallet address
Automatic enforcement of calling and messaging consent rules
EnCharge AI
Agentgates