AI compute from the edge to cloud with breakthrough efficiency and sustainability
Context optimization for production AI
Stage
Not given
MVP
Founded
2022
Not given
Based in
US
GB
Pricing model
Not given
Freemium
Pricing
Not given
Free: 1M context tokens (one-time). Pro: $15/month for 100M tokens/month, $0.18 per extra 1M tokens. Scale: $49/month for 350M tokens/month, $0.15 per extra 1M tokens. 30% off Pro or Scale for the first year for early access teams.
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
Removes duplicate context and off-topic results
Works with any LLM provider
API and SDK integrations
Quality guard checks if kept context is sufficient
Local cleanup of tool output and JSON fields
Fallback to original context on service failure
Per-agent budgets and token limits
Savings report showing cost avoided
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
Reduces input tokens to LLMs by 56–71% on average
Optimizes in milliseconds without slowing requests
EnCharge AI
Contextwaise