Laya AI
Laya AI is an open source family of non-autoregressive System 1 decision models built for fast, typed decisions instead of free-form text generation. Given a state and structured questions, Laya evaluates them in a single forward pass and returns outputs that application code can use directly. It supports three decision types: choice, which selects among named options and returns probabilities; score, which places an input on an ordered rubric such as urgency or severity; and noul, which estimates the probability that a proposition is true. Laya is designed for workloads such as agent and model routing, support ticket triage, guardrails, intent classification, risk and fraud scoring, workflow escalation, RAG filtering, moderation, and phishing detection. It can route requests by department, score urgency, flag refund or churn signals, detect policy or abuse conditions, and escalate uncertain cases to a larger model or human reviewer.
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Clef
Clef is a 27B multimodal decision model that turns a state and a schema of typed questions into structured decisions. It can read state information as text, JSON, images, or video and return a probability for every allowed option of every question. The model supports a 65,536-token context window and vision inputs, allowing developers to evaluate both structured application data and visual content in the same decision workflow. Clef supports three typed question formats: noul for estimating the probability that a proposition is true, choice for selecting among predefined options and returning per-option probabilities, and score for evaluating an input against ordered criteria and producing a probability-weighted score. Applications can submit between 1 and 64 questions in a single request, with answers returned under the same question IDs.
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Clef-flash
Clef-flash is a fast 9B multimodal decision model that turns a state and a schema of typed questions into structured decisions. It can read state information as text, JSON, images, or video and returns a probability for every allowed option of every question. The model supports a 24,576-token context window and vision input, allowing developers to evaluate structured application data and visual content within the same workflow. Clef Flash supports three typed question formats: noul for estimating the probability that a proposition is true, choice for selecting among predefined options with per-option probabilities, and score for evaluating an input against ordered criteria and returning a probability-weighted score. Applications can submit from 1 to 64 questions in a single request, with answers returned under the same question IDs. Example uses include deciding whether a support request is urgent, routing it to the correct team, and scoring the severity of customer impact.
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Parallel Decisions API
Parallel Decisions API is a hosted, web-grounded classification API for developers building software, data-enrichment pipelines, and AI-agent workflows. A request supplies context and one or more bounded questions; the API returns typed answers with probabilities and citations to supporting web sources. Multiple questions can share context in a single request, supporting uses such as company or vendor qualification, lead routing, compliance screening, content filtering, and agent guardrails. By retrieving current web evidence, it can assess facts that may have changed since a model's training data. Developers call the REST endpoint with an API key or access the web_decisions tool through Parallel's MCP server. A hosted playground and documentation support testing and implementation.
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