Explore early tokens (higher risk) — Dex / v2 feed; not the primary curated list on Home. Home picks are hidden here when the ranked workspace has loaded. Back to Home
Paste any token address — we sniff risk, safety, sniper activity and bundle buys.
Add personal (human) wallet addresses only — we track when they buy so you get alerts. Contracts, LP pools, and program accounts are not supported.
Beaglei is your hound for crypto alpha. We help you sniff out smart money, hunt trending meme coins, and catch early pumps — with wallet tracking, insider detection, and token analysis across Solana, Ethereum, and BSC.
Beaglei is named after Dexter, my dog — a Beagle. Beagles sniff for food; we sniff for good tokens.
Track wallets that buy before pumps, scan top holders and insiders per token, and analyze any contract for risk and safety. Not financial advice; always DYOR.
Built by 0xHD5
Stage: Advanced MVP — discovery, enrichment, scoring, ranked views, alerts, and ML plumbing are in place; we’re focused on data volume, trained models in production, polish, and monetization.
Path: production-ready signal → best-in-class UX → paid product → deeper wallet & narrative edge → enterprise-grade ops.
Automate metrics, feature snapshots, labels, training, and predictions on a schedule. Ship a real model to production (not placeholder scores), guardrails so prod never silently falls back to mock ML, and targets like strong prediction coverage on ranked tokens.
Decision dashboard and terminal as one workflow: data freshness, last rebuild time, score breakdowns and “why this rank,” resilient empty/error states, and tighter navigation between the fast ranked view and the main app.
Accounts, API keys, scoped access to ranked views and alerts, plan tiers with quotas (aligned with our existing rate limits and cost protection), and billing so teams can adopt safely.
Deeper wallet graph and history for discovery tokens (not only live-tracked flows), sharper narrative quality and timeliness, insider and cluster signals in scoring and alerts, and hardened real-time discovery where it still matters (e.g. new launch streams).
Reliable alert delivery from the batch pipeline (Telegram/Discord/cron), observability and job health dashboards, DB performance for hot paths, backups/runbooks, and SLO-style monitoring for workers and APIs.
Background discovery and DB-backed reads where possible; narrative ingestion and token→narrative tagging; precomputed ranked views (best overall, by chain, by narrative, smart money, etc.); adaptive budget and rate limits to stay within provider limits. Trending still may hit live discovery when the cache/DB bar isn’t met — we’re pushing more load to background jobs over time.
Next focus: scheduled ML pipeline + production model artifact → no-mock guard + UI clarity on model mode → wire alert notifications for the precomputed pipeline → widen wallet-history coverage → dashboard freshness & explainability.