{"slug": "what-is-wity-the-first-system-1-5-model-explained", "title": "What is Wity? The first System 1.5 model, explained.", "summary": "Alphanimble released Wity, a \"System 1.5\" decision model that returns typed answers with a probability for every option instead of prose. Wity answers most questions in a single fast pass of roughly a tenth of a second and switches to deliberation only when an answer is uncertain, exposing per-option probabilities and a confidence score so calling code can act on clear calls and escalate close ones to a human. The company benchmarked Wity against eight fast, low-cost models on the same 200 reasoning tasks.", "body_md": "Software makes thousands of small decisions a day. Which team owns this ticket? Is this scan a receipt or an invoice? Has the page finished loading? Is the customer reporting an accident?\n\nNone of these needs an essay. Each needs an answer your code can act on, and some sense of how sure that answer is. Today those calls usually go to one of two kinds of model, and neither is built for the job. Wity is a System 1.5 model, and it sits between them. This post explains what it is from scratch: the idea, what an answer looks like, and where it fits.\n\n**Two kinds of model, two kinds of problem**\n\n**Large language models think through every question**, even the easy ones. Then they answer in paragraphs your code has to parse. You pay in seconds and tokens for reasoning that a clear-cut question never needed, and you still have to guess how confident the answer was.\n\n**Fast decision models answer in a single glance.** Easy calls come back instantly. Hard ones come back instantly too, and confidently wrong, because the model has no way to slow down.\n\nPsychologists describe two modes of thought. System 1 is fast and intuitive. System 2 is slow and deliberate. Most of what you decide in a day is System 1, and you switch to System 2 only when something feels off.\n\nWity works the same way. It answers most questions in one fast pass, in about a tenth of a second. When an answer is uncertain or unstable, it thinks first and then answers. Either way you get the same thing back: **a typed decision with a probability for every option.** That's why we call it a System 1.5 model. It sits between instinct and deliberation and picks per question.\n\nYou send a *state* (the thing to decide about: text, JSON, an image, or all three) and one or more questions with the options spelled out:\n\n```\ncurl https://api.wity.alphanimble.com/v1/systemone \\\n  -H \"Authorization: Bearer $WITY_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"state\": \"Hi, I was charged twice for my subscription this month. Please refund the duplicate.\",\n    \"questions\": {\n      \"intent\": {\n        \"type\": \"choice\",\n        \"instructions\": \"What does the customer want?\",\n        \"criteria\": {\n          \"billing\": \"A charge, refund, invoice or payment problem\",\n          \"technical_support\": \"Something in the product is broken\",\n          \"account_access\": \"Cannot log in or is locked out\",\n          \"cancellation\": \"Wants to cancel or downgrade\"\n        }\n      }\n    },\n    \"reasoning\": \"auto\"\n  }'\n```\n\nThe answer comes back under the name you gave the question:\n\n```\n{\n  \"model\": \"wity-1\",\n  \"answers\": {\n    \"intent\": {\n      \"type\": \"choice\",\n      \"choice\": \"billing\",\n      \"probabilities\": {\n        \"billing\": 0.9912,\n        \"technical_support\": 0.0031,\n        \"account_access\": 0.0019,\n        \"cancellation\": 0.0038\n      },\n      \"confidence\": 0.93,\n      \"reasoning\": { \"mode\": \"auto\", \"thought\": false, \"reason\": null, \"forecast\": false, \"thought_tokens\": null }\n    }\n  },\n  \"usage\": { \"input_tokens\": 212, \"output_tokens\": 0 },\n  \"metadata\": { \"reasoning\": \"auto\", \"elapsed_ms\": 94.1 }\n}\n```\n\nThere's no prose to parse. `choice` is the option to act on, and `probabilities` covers every option you offered. `reasoning.thought` is `false` here because the question was clear, so Wity answered directly.\n\nEvery question takes one of four shapes. You pick the shape, Wity fills it:\n\nBecause every decision carries its probabilities, your code decides how sure is sure enough:\n\n```\nintent = answers[\"intent\"]\nif intent[\"probabilities\"][intent[\"choice\"]] >= 0.85:\n    route(ticket, intent[\"choice\"])       # sure enough: act on its own\nelse:\n    send_to_triage(ticket)                # close call: a person decides\n```\n\nAct on clear calls, hand close ones to a person, and set that line per question.\n\nA decision model earns its place by being cheap enough to call on every event and fast enough to sit inside a request. We ran Wity and eight fast, low-cost models through the same 200 real-world cases. Wity's typical call took **109 ms**, against 943 ms for the next fastest. 1,000 runs cost **$3.29**, against $17.95 for the next cheapest. That's our own benchmark, and the method is published alongside it.\n\nPricing is one number: **$0.042 per 1M tokens, and failed calls are free.** Thinking isn't billed, so a thought answer costs the same as a direct one.\n\nNo model is perfect. Use the probability on each decision to choose when to act and when to escalate, and validate generated text like any other input.\n\nThis is the first post in a series where we build up from here, one idea a day: System 1 vs System 2, why decisions shouldn't come back as paragraphs, when a model should think, each primitive in depth, and real builds with code.\n\nIf you want to try it now, the [quickstart](https://wity.alphanimble.com/docs/quickstart) gets you to your first decision in about a minute. Every account starts with $5 of free credit to use within 48 hours of signing up, and the [Playground](https://wity.alphanimble.com/console/playground) runs real requests from your browser with no code at all.", "url": "https://wpnews.pro/news/what-is-wity-the-first-system-1-5-model-explained", "canonical_source": "https://dev.to/chillpill_ak/what-is-wity-the-first-system-15-model-explained-55i8", "published_at": "2026-10-19 11:35:46+00:00", "updated_at": "2026-10-19 11:44:35.811488+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "large-language-models", "ai-tools", "ai-agents"], "entities": ["Alphanimble", "Wity", "wity-1"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/what-is-wity-the-first-system-1-5-model-explained", "markdown": "https://wpnews.pro/news/what-is-wity-the-first-system-1-5-model-explained.md", "text": "https://wpnews.pro/news/what-is-wity-the-first-system-1-5-model-explained.txt", "jsonld": "https://wpnews.pro/news/what-is-wity-the-first-system-1-5-model-explained.jsonld"}}