DecisionsApi vs maap
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
DecisionsApi compared with maap
| Detail | 
DecisionsApi | 
maap |
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| What it does | Text in. Decisions out.
| A 4B model that estimates numbers from text with calibrated intervals
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| Stage | MVP
| Not given
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| Founded | Not given
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| Based in | Not given
| Not given
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| Pricing model | Paid
| Freemium
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| Pricing | One-time plans starting at $10 (100,000 credits), $100 (1,000,000 credits), and $1,000 (11,000,000 credits with 10% extra). Credits do not expire.
| First 1,000 estimates free. Pricing for additional estimates available upon request.
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| Key features | - Structured answers with probability signals
- Online playground for testing models
- Choice, score, and yes-no decision types
- Multiple models available for comparison
- API key management
- Usage and request history tracking
| - Returns median, quantiles, and calibrated intervals for numerical estimates
- Processes text records in a single forward pass without text generation
- Responds in approximately 160 milliseconds
- Flags when targets are outside training distribution or intervals lack calibration guarantees
- Supports few-shot learning with at least eight labeled examples
- Trained on 36 public sources
- Calculates probability of exceeding user-specified thresholds
- For count targets can return probability of each whole number
- Accepts text input without requiring schema declaration or preprocessing
- Costs roughly two orders of magnitude less per prediction than frontier models
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| What makes it different | - Multiple decision models in one playground and API
- Structured answers instead of generated text
- Probability signals with confidence scores
| - Provides calibrated uncertainty quantification where language models cannot
- Transparently reports when calibration guarantees are absent
- Dramatically faster inference than text-generating alternatives at 160ms
- Designed for unstructured text without requiring labeled training data
- Explicitly signals new, unseen targets with fallback capability for code
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 51 ▲ +51 (up) since last check | 2 ● no change since last check |
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| Trust Flow (Majestic) | 0 | 4 |
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| Citation Flow (Majestic) | 15 | 23 |
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| Referring domains (Majestic) | 8 | 23 |
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5 details filled in for both companies.
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