Overview
When evaluating prediction market analytics tools, the filarm vs Predly comparison reveals two distinct approaches to extracting value from platforms like Polymarket. Filarm is a Dune analytics dashboard created by data analyst Filippo Armani, designed to surface comprehensive metrics around user activity and market insights. As of this writing, filarm is still listed as coming soon, meaning its full feature set has not yet launched publicly.
Predly, also currently in a coming soon phase, takes a different angle by positioning itself as an AI-powered analytics platform that spans both Polymarket and Kalshi. Its stated focus is on identifying mispricings — situations where market prices diverge from AI-calculated probabilities — and alerting users to potentially profitable opportunities. Predly claims an 89% alert accuracy rate, which, if borne out in practice, would represent a meaningful signal for active traders and researchers alike.
filarm vs Predly: Key Differences
| Category | filarm | Predly |
|---|---|---|
| Primary Function | Dune-based analytics dashboard tracking Polymarket metrics and user activity | AI-driven mispricing detection and opportunity alerts across Polymarket and Kalshi |
| Target User | Data analysts, researchers, and on-chain market observers | Active traders and market participants seeking an edge through AI signals |
| Platform / Interface | Web app built on Dune Analytics infrastructure | Standalone web platform at predly.ai |
| Automation Level | Passive — displays data and metrics for user interpretation | Active — generates automated alerts when mispricings are detected |
| Markets Covered | Polymarket (primary focus) | Polymarket and Kalshi |
| Key Strength | Transparent, on-chain data aggregation by a named analyst with community credibility | AI probability modeling with a claimed 89% alert accuracy rate |
| Best For | Deep market research, trend analysis, and understanding user behavior patterns | Identifying actionable trading opportunities and mispriced contracts quickly |
When to Choose filarm
Filarm is best suited for users who want a transparent, data-rich view of Polymarket's ecosystem rather than trading signals. Because it is built on Dune Analytics, it inherits a level of on-chain verifiability that appeals to researchers and analysts who want to dig into raw metrics themselves. Once the tool officially launches, it could serve as a strong foundation for understanding market structure and participant behavior over time.
- You are a researcher or analyst who wants to study Polymarket user activity, volume trends, and market health metrics in depth.
- You prefer working with verifiable on-chain data rather than relying on AI-generated probability scores.
- You are interested in the work of a specific analyst — Filippo Armani — and want curated dashboards reflecting his analytical perspective.
When to Choose Predly
Predly is the more action-oriented choice, aimed at users who want to act on market inefficiencies rather than simply observe them. Its multi-platform coverage of both Polymarket and Kalshi gives it broader utility for traders active across prediction market ecosystems. The AI-driven alert system is its defining feature, though users should note the platform has not yet launched and the 89% accuracy claim should be evaluated against real-world performance once live.
- You actively trade on Polymarket and/or Kalshi and want timely alerts when AI models detect potentially mispriced contracts.
- You value automation and want to reduce the time spent manually scanning markets for opportunities.
- You are comfortable incorporating AI probability estimates as one signal in your broader trading or research process.
Verdict
Both filarm and Predly are coming soon, which means any comparison at this stage is necessarily based on stated intentions rather than proven track records. Filarm appears to be the stronger choice for market observers and data-driven researchers who want transparent, on-chain insights into Polymarket's dynamics. Predly is better positioned for traders who want AI-assisted signals and cross-platform coverage. Neither tool should be evaluated definitively until both have launched and users can assess real performance — but based on their described approaches, they serve meaningfully different audiences and are not direct competitors so much as complementary tools for different stages of the prediction market workflow.