Deploy any open model from Ollama or Hugging Face as a private, OpenAI-compatible API
Stage
Not given
Not given
Founded
Not given
Not given
Based in
LT
US
Pricing model
Freemium
Paid
Pricing
Proxy API: 15% of savings on provider bill. Models API: $0.40 per 1M tokens removed (Helene 1.1), $0.90 per 1M tokens removed (Adeline 1). Free tier available with Condense Lite (approximately 20% compression).
Pay as you go: $0/month with prepaid credits from $10. Pro: $29/month with $29 monthly credits. Business: $299/month with $299 monthly credits. GPU pricing: NVIDIA L4 $0.95/hour ($0.000264/second, $1,180/month always-on); NVIDIA L40S $3.20/hour ($0.000889/second, $3,974/month always-on); 4x NVIDIA L
Key features
Proxy API for seamless integration requiring only one base URL and header change
Maintains 98.6% cache hit rate
Preserves instructions, questions, answers, code and error messages
Direct billing from provider with no stored API keys
SOC 2 Type II and ISO 27001 compliance in progress
Zero data retention with GDPR export and erasure support
Deploy models with one command via CLI
OpenAI and Ollama API compatibility
Scales to zero with configurable idle timeout (60 seconds to 60 minutes)
Private endpoints with no prompt logging
Supports GGUF and safetensors model formats
Free model storage (10GB to 1TB depending on plan)
Always-on option for no cold starts
Batch jobs pricing 30-50% cheaper
What makes it different
Removes 37.3% of bills on average sessions and 66-72% on sessions over 800k tokens
Pay only 15% of savings on Proxy API with no fee if no savings occur
Built around cache architecture rather than against it
Public benchmark allowing comparison with alternatives before purchase
Operates transparently with audit logs and ability to inspect rewritten requests
No Dockerfile or server management required
Use your existing OpenAI or Ollama client with one URL change
Pay only for actual compute seconds used, not monthly subscription
Cold start time never billed and requests wait instead of failing
Prompts and outputs never logged or used for training
condense
BitsRun