Jevtown

Jevtown

Jevtown is a live interactive city simulation of 1,000 citizens driven by a single small AI model called Jev (jev-1.13.0). Visitors can claim a citizen, observe recorded live runs, vote on futures, and use the demo and field guide to lift Jev’s decision-patterns into products.

Jevtown is ai tools software teams evaluate for ai agents. Use this page to review pricing, integration signals, and the best alternatives before you commit.

Paid Enterprise 70/100
#541 in AI Agents (541 tools)
Just launched
Data reviewed Sep 21, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: AI Agents

What it does

AI Tools software for decision-makers comparing workflow fit and alternatives.

Best fit

AI Agents

Pricing snapshot

Paid from Per-request/per-pattern pricing based on measured runs

Next step

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Jevtown

Jevtown is an interactive test rig: a simulated city of 1,000 citizens whose next actions are decided every tick by a single small AI model named Jev (jev-1.13.0). The public demo runs live and also exposes recorded runs and logs so visitors can replay decisions, inspect timings, costs and the model’s probabilities. The project is presented as a demo and a set of reusable patterns for developers and product teams who want to use a lightweight judgment model for tasks such as triage, moderation, panel judgments, profiling, and agent behavior. Visitors can claim a citizen (via X), observe the city's decisions, vote on futures, and read the study and field guide to apply the measured patterns to their own products.

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Key Features

Population-scale decisions

One request can ask the model what each of 1,000 people will do next (1,000 minds a tick), with measured latency (0.98 s median) and cost ($0.015 per full city tick).

Counterfactual futures (copy-and-run)

Before visitors vote, the world is copied and a candidate event is run in the copy; everyone who would witness it is asked what they would do, enabling low-cost counterfactual polling (≈0.6 s per future, a third of a cent).

Small-model judgments only

Jev is described as a System One model that supplies judgments (categorical probabilities for options) rather than producing text or numerics; the model answers plain phrases that game code supplies.

Replayable logs

Runs can be replayed from logs without calling the model again; timings, draws and costs are recorded and replayed exactly as measured during the live run.

Panel/jury judgments

The system can seat twelve citizens as jurors, ask each once whether they would vote guilty, and combine probabilistic votes into a verdict (measured 560 ms per jury).

Typed-event front door

Visitors can type free text events; Jev reads them into a typed event so free text is translated into structured, code-run actions.

Safety screening and moderation

Every message is screened individually for abuse, spam and private details before reaching citizens; the site reports measured block rates for harmful lines and thresholds for hiding hateful handles.

Measured cost and performance ledger

The project publishes measured costs (per-request, per-tick), latency percentiles, total request counts, token usage, and an overall ledger of the experiment's compute and evaluation costs.

Ownership & gamified interaction

Visitors are handed and may claim one citizen (1,000 total) via X; owners score by predicting what their citizen will do next and can participate in the live board.

Pricing

Free Tier Available

Free to try the live city in the browser; no account needed to view replays. Claiming a citizen requires signing in with X.

Pay-as-you-go (measured unit pricing)

Per-request/per-pattern pricing based on measured runs
  • 1,000 people asked about next action: $0.015 per full-city tick (median 0.98 s).
  • Counterfactual future (copy-and-run): ~0.6 s and a third of a cent per future.
  • Free-text sentence -> typed event: $0.0001 per sentence (reported).
  • Moderation example: $0.018 per 1,000 (reported) and 8,000-character judgments for $0.012 (reported).

Full-experiment cost (example)

$21.64
  • Reported total cost to reproduce the public experiment’s runs and evaluations (ledger).

Use Cases

Triage, routing and bulk decisions

Send a large batch (shared context) and ask one question per item (1,000 for $0.015) to surface probabilities across many items at once.

Counterfactual polling

Copy world state, change one fact and re-run to measure how behavior would change (the 'future' mechanism).

Moderation gate

A safe front door that screens each message alone for abuse or private data before it reaches downstream systems or users.

Panel-based decisions and juries

Aggregate multiple individual judgments (e.g., 12 jurors) into a single verdict with measured latency and margins.

Agents, characters and game NPCs

Produce typed actions with odds for agents and characters; sample those actions in code and replay without calling the model.

Bulk profiling and columns

Turn judgments into filterable columns for analysis and product logic (bulk profiling for many individuals).

Integrations

X (sign-in)

Visitors sign in with X to claim ownership of a citizen inside Jevtown.

Claude (Anthropic) noted in engineering

The project reports it was engineered with Claude (Fable 5.1) in Claude Code during development.

Benefits

Low per-request cost and measurable pricing (example: 1,000 people for $0.015 per city tick).
Fast, repeatable judgments at population scale (median ~0.98 s for whole city, best ticks >1,300 decisions/sec).
Replayability and auditable logs: runs replay from recorded draws and timings without re-querying the model.
Safety-first ingestion: messages and handles are screened before reaching citizens; free-text is converted to typed events so raw words do not reach citizens.
Patterns and field guide to lift experimental behaviors into producible features for products.

Limitations

Model can be confidently wrong in population behaviors; multiple examples of well-formed but incorrect behavior were found via replayed tests.
Counting/array-index failure: Jev cannot reliably count past about the twentieth item in a list; answers keyed by array index became incorrect.
Bias in evidence weighting: the model under-weights evidence of innocence in juror scenarios, affecting verdict outcomes.
Domain-specific failures (examples): repeated wrong behavior in scenarios like famine (starving farmers choosing 'eat' when no food), chapel/crowd contagion, and frozen-village reproduction at high confidence.

Frequently Asked Questions

No verified FAQs are available.

Getting Started

  1. 1 Enter Jevtown (https://jevtown.com/) and load the live city or replay recorded days.
  2. 2 Claim a citizen when prompted by signing in with your X account (one owner per citizen; 1,000 total).
  3. 3 Observe the live/replayed run: inspect probabilities, timings and draws for each decision and try rolling the dice against those odds.
  4. 4 Use the field guide and cost calculator ('Build with Jev') to prototype how Jev’s patterns map to your product.

Support

docs

Jev: documentation and 'Jev explained' pages linked from the site for technical and conceptual guidance.

study

The site publishes a study, field guide, ledgers and evaluation methodology for reproducibility and deeper inspection.

site

Primary access and demonstration are via the main site (https://jevtown.com/).

API

Available: No

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