| What it does | AutoML that just works. Keep training local.
| AI execution infrastructure that turns mission-critical manual tasks into reliable, paid AI services
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| Stage | MVP
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Free trial
| Contact for pricing
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| Pricing | Free beta with no billing. Paid plans launching in the future; pricing not yet announced. Join the waitlist for paid plans without payment or purchase commitment.
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| Key features | - Python SDK for tuning suggestions
- Local model training with remote suggestions
- Supports classification and regression
- Included CPU demo workloads
- Efficient observation budget allocation
- Model ranking and selection
- Reference scheduler implementations
- HTTPS secure communication
| - Job of Work Mapper: identifies valuable processes and maps required outcomes, steps, systems and stakeholders
- Execution Engine: manages multi-week or multi-month workflows with fault tolerance, checkpoints and error recovery
- Built-in stakeholder management: communicates with stakeholders across channels and escalates exceptions
- Intelligence flywheel: captures execution data to benchmark models, improve accuracy and optimise costs
- Small focused AI models in deterministic graph: reduces errors and cost vs single large models
- Fully auditable and explainable execution
- Durable execution engine with checkpoints and automated recovery
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| What makes it different | - Trains locally, not on the service—your models and data stay on your computer
- Efficient tuning using only half the observation budget of full training
- Outperforms reference schedulers in benchmarks on diverse datasets
- Free beta with no billing or account costs
| - Handles multi-stakeholder workflows spanning days, weeks or months without requiring core product rebuild
- Partners keep control of brand and customer relationships while using platform for execution
- Usage-based pricing aligns fees with completed outcomes rather than features
- Small focused AI models designed for accuracy and repeatability in high-trust workflows
- Includes mapping stage to validate commercial viability before significant investment
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | 12 ● no change since last check |
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| Trust Flow (Majestic) | 3 | 8 |
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| Citation Flow (Majestic) | 13 | 29 |
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| Referring domains (Majestic) | 2 | 64 |
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hyperopt.dev
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