What you need to bring
Nothing but your Jev request. One real example of the state your program sends, your questions exactly as you send them to Jev, and, if you like, your rules in plain words. No past decisions or answers needed; a few examples of what you send Jev make it better: 5-20 more real states in examples. That's enough for your own model, in minutes: see Start with no data.
Your decisions make it better. Past cases with the answers they got, answers to cases your model was unsure about, reported outcomes, or recorded play: whatever you have, whenever you have it. See Make it better with your history.
What that looks like
| Your decisions | What the model reads | Examples | To start | Makes it better |
|---|---|---|---|---|
| On human language | free text | support tickets, claims, complaints, moderation | your Jev request | past cases and how each was handled |
| On data | numbers and fields | fraud flags, eligibility, reorders, alert triage | your Jev request | reported outcomes and decisions marked wrong |
| Step by step | a changing state | game opponents, NPCs, agents in a simulator | your game's Jev request | recorded play |
| Mixed | fields plus some text | a bank case with account details and a message | your Jev request | past cases, for the text part |
Decisions on text
Tickets, emails, chats, claims, reviews. Close to Jev on day one for short messages; give it past cases or answer a few reviews to pull clearly ahead. On 3,080 real bank messages:
| Accuracy | |
|---|---|
| Your model, day one with no data (10 automatic builds) | 85.5% (84.6–86.8%) |
| Your model, after about 400 reviewed cases | 91.7% |
| Your model, with the bank's history | about 95% (94.9–96.0%) |
| Jev, few-shot | 86.6% |
| Jev, zero-shot | 83.9% |
On long texts, like complaint narratives, a model built with no data is well below Jev; there, start from your past cases. With history, on real consumer complaints (CFPB): 77.7% against Jev's 65.0% few-shot.
- The answers you already record are enough. The outcome or category you already keep for each past case is what your model learns from. A column named like a question holds how the case went.
- Rules on what a message is about ("Always block-card when topic is lost_stolen") are enforced whenever there's a real chance they apply, and unsure cases go to review. With your history, your model reads those messages better too. See Decisions and rules.
- Answering the unsure cases helps most. Each answer to a case your model was least sure about teaches the next retrain the most: see Improve your model.
- It reads about 100 languages; accuracy is measured in 51. See Languages.
The numbers and every step: Bank support, from day one and with history.
Decisions on data and state
Transactions, account fields, sensor readings, schedules. Your Jev request is all there is to bring. Numbers go into the model as numbers, so it can tell £4,999 from £5,001, and your rules on fields are enforced on every decision, whatever the model thinks.
Games
A move in a game is a decision on data. Send the request your game sends Jev: its state, with each move's facts if you have them, and a Choice question over the moves. Call your model like Jev, or download it and run it inside the game loop.
Built automatically with zero data from their Jev requests, a Doom player beat Jev at the same decision rate (45 kills to 39, 2 deaths to 5, won 7 of 13 against its default style and 12 of 13 against its aggressive one), and a Snake player out-ate Jev's (42.0 to 40.0 food at equal steps, never died). See the Doom and Snake cookbooks.
Recorded play makes it better: moments from a scripted bot, a designer or your best players, each with the right move. See the history cookbooks for Doom and Snake.
The shape of past cases
When you have them: a CSV with your state fields and one column per question you have answers for:
message,amount,tier,fraud_flag,action
"Refund my order please",40,pro,0,approve
"I was charged 900 twice",900,enterprise,0,escalateOr JSONL, one case per line, with the state exactly as your program sends it: {"state": {...}, "answers": {"action": "approve"}}. Send them in history with your build, or upload them: see Make it better with your history.