How Forecast AI reads Polymarket's smart money with Bravado

Forecast AI × Bravado

When you're forecasting whether a market resolves YES or NO, the price tells you what the crowd believes. It doesn't tell you whether the people behind that price actually know what they're doing. Forecast AI is an intelligence platform for Polymarket and Kalshi. A user selects a live market, and seven specialised AI agents independently analyse market structure, news, research, social narratives, community discussions, macro conditions, and onchain activity. Their outputs are combined into an explainable forecast with probabilities, confidence, counter-signals, risks, and cited sources. Every forecast is committed to Robinhood Chain before the market resolves, then scored with a Brier score once the outcome is known, so each agent builds an immutable track record that anyone can verify.

For every market it analyses, Forecast AI cross-checks that seven-agent verdict against up to 30 of Polymarket's top-ranked human traders, screened, deduplicated, and scored through Bravado.

30 top-ranked non-bot traders screened per market via Bravado

3 leaderboard windows checked every time: 24h, 7d, 30d

7 AI agents cross-checked against live trader positioning

Products used: Bravado Data API

The setup: a forecast is only as good as the people behind the price

Most users can't continuously monitor every relevant source, evaluate who the sophisticated traders are, and compare information across multiple platforms at once. That fragmentation is the problem Forecast AI set out to solve, making the process more accessible, transparent, and verifiable.

That verifiability is the whole point. Because every forecast lands on Robinhood Chain with a Brier score attached, the analysis behind it has to be defensible, not just plausible. And a forecast is only as defensible as its read on the people moving the market, which is exactly where raw market data runs out.

The challenge: native APIs price the market, they don't profile the players

Polymarket and Kalshi ship the essential native APIs: prices, order books, volume, liquidity, resolution data. But building one consistent product on top of them is harder than it looks:

Every platform uses different schemas, identifiers, outcome formats, and market structures, so building anything coherent means extensive normalisation, market matching, caching, and reliability monitoring.
Native APIs say almost nothing about who is behind the activity. They can't tell you whether a position comes from an experienced trader, a bot, or a single concentrated wallet.

Raw market data shows the shape of the money. It doesn't show the quality of it. For a product whose entire value is credible, explainable analysis, that gap matters.

Why Forecast AI chose Bravado

Forecast AI pairs the native platform APIs with a small set of carefully selected intelligence providers, chosen on reliability, data quality, transparency, and their ability to solve one specific part of the analysis well. Bravado provides the trader-intelligence layer for Polymarket: the leaderboards, wallet-level performance, and live positioning that native APIs leave out.

"Bravado gives our agents valuable context that raw market data cannot provide on its own. It helps us understand who is taking risk, whether those traders have a credible history, and how their positioning compares with our AI forecast."
Founder, Forecast AI

The solution: turning wallet data into a smart-money signal

On Polymarket, Forecast AI's own integration is read-only market data: prices, order books, volume, liquidity, resolution. That tells the agents where the market is, not who put it there. Bravado provides the trader-intelligence layer that fills the gap.

For each market, Forecast AI reviews up to 30 ranked non-bot traders across the 24-hour, 7-day, and 30-day Bravado leaderboards, removes duplicates, and checks whether those traders hold matching active positions in that market.

From there it reads the things that actually indicate conviction: YES or NO direction, position value, win rate, PnL, and leaderboard presence. That feeds directly into the Market Agent and Opportunity Radar, which surface whether proven traders confirm or contradict the seven-agent forecast. It's a smart-money signal a user can read at a glance instead of reverse-engineering from wallet addresses.

By the numbers, on Bravado:

7 specialised agents per forecast, each cross-referenced against real trader positioning
Up to 30 ranked non-bot traders screened per market
3 leaderboard windows checked every time: 24-hour, 7-day, and 30-day
Duplicate removal and active-position matching applied before any trader counts toward the signal

The result: Bravado turns complex wallet and performance data into a practical, human-readable smart-money signal, one that either backs up Forecast AI's agents or gives users a reason to look twice.

What's next

Forecast AI is moving toward letting users build and operate their own forecasting agents, which makes a reliable trader-intelligence layer more important, not less. As Bravado expands its coverage of leaderboards, wallet performance, and live positioning across Polymarket, that data becomes a standing input every user-built agent can draw on.

If you're building on prediction-market data and need a trader-intelligence layer that native APIs can't give you, explore the Bravado Data API or talk to us. And if you want to see the smart-money signal in action, try Forecast AI.