AT0M vs jilebi
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
AT0M compared with jilebi
| Detail | A
AT0M | 
jilebi |
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| What it does | A private System One Decision AI that runs locally
| Linux machines in the cloud for AI agents
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| Stage | MVP
| Startup
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| Founded | Not given
| Not given
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| Based in | Not given
| Not given
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| Pricing model | Not given
| Paid
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| Pricing | Not given
| CPU: $0.009/vCPU·hr, Memory: $0.009/GB·hr, Disk: $0.0001/GB·hr. Stopped machines cost $0.0001/GB·hr.
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| Key features | - Non-autoregressive with no free text generation
- Multi-question call support in a single forward pass
- Bounded output within supplied candidate set
- Calibrated probabilities without temperature fitting
- Local inference as a Rust binary executable
- Deterministic inference with reproducible results
- Support for choice, score, and yes-no decision types
- CPU, Apple Metal, and CUDA hardware support
- Trainable on your own decisions locally
| - Launch machines in seconds
- Auto-sleep when not in use
- Wake up in milliseconds
- Dedicated CPU, memory and disk per instance
- Clone machines with same setup
- Automatic routing without IP configuration
- Standard tools support (docker, ssh)
- Share routes with selective access
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| What makes it different | - Bounded output structurally prevents off-list answers, unlike generative models
- Calibration by construction without temperature fitting enables direct threshold-based automation
- Local executable keeps inference in your perimeter with no per-decision API dependency
- Cost structure based on electricity, not output tokens
- Deterministic inference with identical results across repeated requests
| - Machines wake in milliseconds
- No special CLI required
- Fully isolated virtual sandbox for each machine
- No credit card required to start
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 22 ▼ −2 (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) | 3 | 19 |
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| Referring domains (Majestic) | 1 | 10 |
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4 details filled in for both companies.
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