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decision-machine-1

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Structured-answer model from CloudRaker that returns labels, yes or no results, scores and extracted fields from text or images

About decision-machine-1

Behind Milliseconds.ai, the API that CloudRaker Inc. of Montreal offers for compact, typed decisions about text and images, sits decision-machine-1. Instead of writing prose, it returns structured answers, which makes it suited to classification, extraction and checking steps inside larger software.

What a request can return

The result types are specific. A yes/no question comes back with a probability. A label comes with the full score distribution. Other outputs include a rating on a scale, answer spans with character offsets, named entities, fields extracted to fit a JSON Schema, and verification of a value against the source text. CloudRaker's own blog posts date the API's launch to 19 September 2026, and it grew out of models the company already used in its Paperwork document API.

What sits underneath

CloudRaker explains that the name denotes the product surface, not one newly trained model. Constrained choices are handled by a small instruction-following model, Qwen2.5-1.5B-Instruct, and span extraction by GLiNER2.5. The company publishes neither a parameter count nor a context window. One text may be up to 20,000 characters long, and up to 32 texts can be batched in a request. Images (JPEG, PNG or WebP, up to 5 MB) are not stored and are billed as a fixed token count that depends on detail level. Labels and instructions are best written in English, while the input text may be in other languages.

Integration

An endpoint compatible with the OpenAI interface covers tool calls and extraction against a JSON schema, but not plain chat. Production use is billed on input tokens only, with no charge for output, and test keys include a monthly allowance of free input tokens. For an image decision at medium detail, the vendor quotes roughly 90 ms of model time.

Caveats from the vendor

CloudRaker is clear that neither a probability nor well-formed output guarantees a correct answer. It recommends testing on the customer's own data and having people review ambiguous or high-stakes cases. The service is proprietary and available only as a hosted service.

TrustList summary

CloudRaker's hosted decision model, decision-machine-1, sits behind Milliseconds.ai, an API for small, typed decisions on text and images. CloudRaker Inc., based in Montréal, built the API, which returns structured answers such as labels and scores rather than prose.

What decision-machine-1 does

  • Yes or no and labels: yes or no answers with a probability, or a label with its full score distribution.
  • Ratings and spans: ratings on a scale, and answer spans with character offsets into the source text.
  • Structured extraction: fields that match a JSON Schema, named entities, and checks of a value against its source text.
  • Compatible endpoint: an OpenAI-compatible interface that supports JSON-schema extraction and tool calls, though not plain chat.

Who it works with

Teams that need typed results from text or images at volume. The vendor advises checking results on the customer's own data and reviewing ambiguous or consequential cases.

Key facts

  • Launch: 19 September 2026, the date of CloudRaker's own blog posts.
  • Limits: up to 20,000 characters per text and 32 texts per request, with images up to 5 MB in JPEG, PNG or WebP.
  • Speed: the vendor quotes about 90 ms of model time for an image decision at medium detail.
  • Underlying models: Qwen2.5-1.5B-Instruct handles constrained choices, and GLiNER2.5 handles span extraction.
  • Label language: labels and instructions should be written in English.

Summary written by TrustList from the business's own published information, Nov 2026.

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Trust Score

4/ 100
Trust Score: New

An earned signal from verification, reviews, awards, transparency and engagement - the vendor can't buy it.

Verification
0/100 · 20%
Reviews
0/100 · 30%
Awards
0/100 · 15%
Transparency
18/100 · 20%
Engagement
0/100 · 15%
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Updated 9/22/2026

What the business tells TrustList

Founded
2026 (0 years) evidence sent

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