Field notes on on-chain forensics, trading intelligence, and the tools shaping both.
Long-form analysis from the people building the forensic stack. We cover the things we live inside every day: holder maps, cluster detection, the TON and Hyperliquid intelligence landscape, and where AI is actually useful (vs. where it's noise). No press releases. No paid mentions.
Why Intel Maps: the TON forensic stack in 2026
Three forensic platforms. Three philosophies about what an on-chain investigation should look like. We pull each one apart on the dimensions that actually decide a trade: chain coverage, cluster math, infrastructure labeling, and what it costs to keep using it past month one.
Methodology
How to Spot a Cabal: A Forensic Field Guide
The signals we look for in every token before we'd let anyone we know touch it: cluster shape, co-funding pattern, KOL entry timing, infrastructure mislabels. With math.
Analysis
AI in On-Chain Forensics: What's Real, What's Hype in 2026
Every analytics tool now ships an "AI" pill. We separate the genuinely load-bearing applications (clustering, labeling, narrative summarization) from the marketing.
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