One API for hundreds of AI models with unified billing and refundable balance
Everything has an algorithm
Stage
Startup
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Founded
2026
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Based in
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Pricing model
Paid
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Pricing
Usage-based prepaid credits with transparent per-token pricing. Examples: GPT-6.1 Terra from $0.15 input / $0.75 output per 1M tokens; Claude Haiku 5.5 from $0.03/M input / $0.12/M output; Claude Opus 5.5 from $1.12/M input / $5.6/M output. First top-up receives 10% bonus credits (up to $200, minimu
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Key features
One API for hundreds of models across OpenAI, Anthropic, Google, DeepSeek, MiniMax and more
OpenAI, Anthropic, and Vertex protocol compatibility
Multi-layer redundancy with automatic failover
Usage-based billing with no monthly minimum
Only successful requests are billed, failures are free
Refundable balance at any time
Visible rate limits per account
Support for text, image and video workloads
Constant-state attention: models serve any context length from the same memory per request
HCGM: models run from disk storage instead of memory
M-Rail: context processed by a model can be reused instantly in future requests
CPUDA/sGPU: run unmodified CUDA programs on CPUs with bit-identical results
Organ grafting: transfer capabilities between models without training
Personal instruction set (ISA) compiled on device from phone signals
Population ISA: compile laws from many people without personal records
Digital twins of customers, fleets, cities or markets
Results identical across all machines and architectures
Computation cost follows novelty not data size
What makes it different
Reliability-first architecture with multi-layer redundancy across network, gateway and model layers
Transparent, refundable balance instead of locked-in subscriptions
Unified billing across all model families with one invoice
Health-aware routing across vendors with automatic failover
Constant memory cost regardless of context length or data size
Exact reuse: every computed result is kept and reused instantly
Portable execution with bit-identical results across all hardware
Models run from storage without retraining or fitting in memory
Privacy-preserving: raw data never leaves the device
RouteMux
Wirkung