kibbu vs Wirkung
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
kibbu compared with Wirkung
| Detail | 
kibbu | 
Wirkung |
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| What it does | Run your product's AI features on machines you already own
| Everything has an algorithm
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| Stage | Not given
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| Founded | Not given
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| Based in | IL
| Not given
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| Pricing model | Not given
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| Pricing | Not given
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| Key features | - OpenAI-compatible API
- Zero data retention
- Automatic idle detection and workload routing
- MDM-based agent installation
- Cloud fallback with transparent logging
- Support for Macs, Windows and Linux
- Memory and speed estimation for models
- Optional on-premises deployment
- Data routing controls for sensitive 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
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| What makes it different | - Costs stay flat as you grow because you pay for electricity instead of per-token cloud fees
- Only uses idle time, stepping back immediately when users return
- Code stays the same - just change the API base URL and key
- Works with hardware you already own without buying new equipment
- No data storage of prompts or responses
| - 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
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ▼ −1 (down) since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 0 | 0 |
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| Citation Flow (Majestic) | 16 | 0 |
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| Referring domains (Majestic) | 3 | 0 |
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3 details filled in for both companies.
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