Version 3.0 available now
Two self-hosted bots. One visual dashboard. Full Python source.
Full source · One-time purchase · No paid data APIs
Illustrative interface. Not recorded results.
Monitor your Kalshi account, Weather activity, Inflation activity, trades, positions, model output, risk, reconciliation and system health from one place.
1 min 9 sec · Narrated walkthrough · English captions
Use fullscreen for a closer look at the dashboard. Open the video.
Actual dashboard screenshots, supplied by Steve. Captured October 13, 2026. Status labels and figures show the captured state, not current live readings or a verified performance summary.
The Weather Signal Reactor shows the scan pipeline, recorded decisions, input availability and safety state.
Open full-size screenshot of Weather reactor in a new tab
The U.S. Weather Network shows the city watchlist, station map and the selected market’s recorded model comparison and decision.
Open full-size screenshot of Weather network in a new tab
Economics intelligence shows the recorded safety evaluation, execution ledger, CPI and PCE nowcasts, and latest decision funnel.
Open full-size screenshot of Economics in a new tab
The Weather order ledger shows submitted orders, recorded fills, settlements, fees and results, including wins and losses.
Open full-size screenshot of Weather trades in a new tab
The dashboard is for monitoring and visibility. It reports what the bots did and what state the system is in. It does not place trades of its own and it does not bypass the bots' risk controls.
The weather bot prices contracts from NOAA's National Blend of Models: calibrated, station-level guidance published for the exact stations Kalshi settles against. Five further forecast systems stay in the model as a disagreement check.
Forecast data
Execution and risk
Most markets should not result in a trade.
The bot is built to reject a market when the required data, liquidity, pricing or risk conditions are not there. A scan that places nothing is the system working, not the system idle.
The inflation bot scores CPI, Core CPI and PCE markets against the Cleveland Fed Inflation Nowcast and an internal weighted nowcast, then compares that estimate to where the market is actually pricing the strike.
Signal
Markets and controls
Inflation is a strategy, not a bonus.
Weather and Inflation are the two halves of the product. They run as separate components against the same Kalshi account, under the same shared risk engine, with the same confirmed-fill and settlement accounting behind both.
Submitting an order is the easy part. Any weekend script can authenticate with Kalshi and send one. The hard part starts immediately afterwards.
Predict & Profit 3.0 was built around those problems. Most of the release history is not new signals. It is the accounting, the identity handling and the failure paths underneath them.
Not a signal feed. Not a hosted black box. You install the whole thing on your own machine, you hold the source, and nothing calls home.
3.0 keeps one permanent installation root. Each release lands beside the last as its own immutable version and is selected atomically, while your configuration, data and logs stay where they are. An upgrade swaps the code, not your trading history.
A guided installer sets up PostgreSQL, the risk policy and the dashboard. A management CLI starts, stops, upgrades and diagnoses the installation, and can install user services so it comes back after a reboot. Nothing starts trading on its own.
The interesting failures in an automated trading system are not bad forecasts. They are a fill you did not record, a settlement that happened while you were offline, and two strategies disagreeing about what the account holds. This is what gets qualified before a release ships.
Fresh-install qualification
A clean installation is exercised end to end against a disposable PostgreSQL cluster and a real browser before a release ships.
Migration qualification
Upgrades from supported earlier layouts are rehearsed against realistic historical data, not an empty database.
Shared account risk
Weather and Inflation are tested trading the same account together, because that is where two-strategy bugs actually live.
Order identity handling
Orders are bound to authenticated account evidence. Ambiguous or foreign identities are rejected rather than guessed at.
Fill and settlement reconciliation
Fills, actual fill cost, fees and settlements are taken from exchange evidence. Missing evidence is not filled in with an assumption.
Immutable release packaging
Each release is a fixed archive with a published checksum and a declared compatibility contract. A changed build gets a new version.
Production migration validation
3.0.0 is functionally identical to the release candidate that was qualified and then run in production before the final version was cut.
Fail-closed behaviour
Unresolved exposure, an incomplete account snapshot or a state mismatch pauses trading. The default is to stop, not to continue.
No representative profitability record for the current release has been verified. The checks above establish release behavior, not profitable trading. Historical experiments and illustrative dashboard figures do not establish what a buyer can expect to earn.
The 10 latest verified, settled Weather bot positions in this snapshot, ordered by settlement time. All outcomes in the selected sequence are included.
These trades come from Steve’s development account, where settings and strategies are regularly tested. Customer settings and trade sizes vary. Examples demonstrate bot activity and individual outcomes; they are not a typical-return forecast.
Market question: High above 85°F?
Kalshi published a settlement value of 83°F. That is not above 85°F, so the market settled NO. The bot held NO, so this position won.
Settled
Kalshi market recordMarket question: Low below 51°F?
Kalshi published a settlement value of 52°F. That is not below 51°F, so the market settled NO. The bot held NO, so this position won.
Settled
Kalshi market recordMarket question: High above 71°F?
Kalshi published a settlement value of 71°F. That is not above 71°F, so the market settled NO. The bot held NO, so this position won.
Settled
Kalshi market recordMarket question: High below 62°F?
Kalshi published a settlement value of 60°F. That is below 62°F, so the market settled YES. The bot held NO, so this position lost.
Settled
Kalshi market recordMarket question: Low below 60°F?
Kalshi published a settlement value of 57°F. That is below 60°F, so the market settled YES. The bot held NO, so this position lost.
Settled
Kalshi market recordMarket question: High above 82°F?
Kalshi published a settlement value of 81°F. That is not above 82°F, so the market settled NO. The bot held NO, so this position won.
Settled
Kalshi market recordMarket question: Low below 58°F?
Kalshi published a settlement value of 59°F. That is not below 58°F, so the market settled NO. The bot held NO, so this position won.
Settled
Kalshi market recordMarket question: High below 71°F?
Kalshi published a settlement value of 74°F. That is not below 71°F, so the market settled NO. The bot held YES, so this position lost.
Settled
Kalshi market recordMarket question: Low below 60°F?
Kalshi published a settlement value of 62°F. That is not below 60°F, so the market settled NO. The bot held NO, so this position won.
Settled
Kalshi market recordMarket question: Low below 61°F?
Kalshi published a settlement value of 60°F. That is below 61°F, so the market settled YES. The bot held NO, so this position lost.
Settled
Kalshi market recordEntry prices are verified average fill prices per contract, before fees. Partial fills are combined into one position. Settlement explanations use Kalshi’s final values and market rules, which name The Weather Company as the settlement source.
A complete history of each trade’s experiment settings was not verified. These examples do not establish representative results for the current release. This is a fixed snapshot, not an automatically updating trade feed.
Read the validation limitsNo subscription, no licence server, no usage tier, and no paid market-data bill waiting behind the install.
Complete bundle: Weather + Inflation (Econ), dashboard and full Python source
US$99One-time purchase
Requires Ubuntu 24.04, Python 3.12 or 3.13, PostgreSQL 16 or 17, an eligible Kalshi account and command-line setup. Hosting and trading capital are separate from the software purchase.
Get Complete Bundle - US$99Self-hosted on your own machine, traded through your own Kalshi account. Purchase includes six months of updates.
Want to learn first?
The educational ebook covers the market theory and the manual version of the strategy. It is not the software.
Already a customer? 3.0 is a new release with a guided migration path. Find your Gumroad download.
What changed in 3.0 →Predict & Profit 3.0 is self-hosted source code for technically comfortable Kalshi users. These are the questions that matter before you purchase it.
Check your eligibility before buying. This software requires a Kalshi account, and Kalshi restricts access from some jurisdictions. Verify that you can use Kalshi where you live in the current Kalshi Member Agreement.
Predict & Profit 3.0: the full Python source for the Weather bot and the Inflation (Econ) bot, the visual dashboard, the shared account-level risk engine, order and settlement reconciliation, the guided installer, the management CLI, diagnostics, migration and recovery tooling, and the customer documentation. The purchase is a personal, non-transferable licence.
Ubuntu 24.04 with Python 3.12 or 3.13 and PostgreSQL 16 or 17. Linux is the supported platform for running the application. Windows is fine as your browser or SSH client, and Windows users who want to run it locally should use WSL2. Native Windows lifecycle operation is not supported in 3.0.
You should be comfortable on a Linux command line, following setup instructions and reading an error message. The installer is guided and the documentation gives exact commands, but this is self-hosted source code you run yourself, not a desktop application with an installer wizard and a tray icon.
No. The complete bundle is a one-time purchase of US$99. There is no licence server, no metering, and the software does not phone home. You run it on your own infrastructure against your own Kalshi account.
No. It automates data collection, probability estimation, risk checks, order handling, accounting and settlement tracking. It cannot guarantee that a model is correct, that a market is mispriced, that an order fills, or that a trade makes money. Most scanned markets are expected to produce no trade at all.
No representative profitability record for the current release has been verified. Release qualification checks installation, risk controls and accounting; it does not establish profitable trading. Historical experiments and illustrative dashboard figures are not evidence of current-release returns.
No. Kalshi API access and the NOAA and Cleveland Fed data the bots rely on are free. FRED and BLS inputs are optional and also free.
Kalshi weather markets across 20 cities, plus CPI, Core CPI, PCE and related inflation markets. Polymarket is not supported, and neither is any other exchange.
Purchase includes six months of updates. Each update installs as a new immutable release beside your existing data rather than overwriting it. Setup support is available at support@predictandprofit.io. I personally review support requests and aim to send an initial reply within two business days.
3.0 ships migration tooling for supported earlier layouts. It inspects your existing installation, validates credentials and order ownership without modifying the source, converts the schema, and reconciles against Kalshi before anything is activated. Ambiguous ownership, missing history or precision loss blocks activation rather than guessing.
The software requires an eligible Kalshi account. Kalshi restricts access from some jurisdictions and may change its eligibility rules. Before purchasing, check the current Kalshi Member Agreement. If Kalshi does not permit access where you live, the trading features will not be usable.
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Questions about the bot, the data, or licensing? Send us a message.
