Hashwei’s Solution: Smarter, Faster, Cleaner Analytics
Hashwei is built from the ground up to eliminate these problems and empower data-driven decisions:
1. Reduce Latency
Hashwei captures all market-moving data, classifies and streams it in real-time.
(L1) Market Entities, Data Streams
(L2) EVM-Based Streaming, Intelligent Caching, Early Alerts
(L3) Real-time data, faster reactions, superior execution
2. Reduce Noise
Automatically detect and filter data that does not impact actual market movements
(L1) Detect Wash Trading, Eliminate Spam/Bots/MEV/Fake Airdrops
(L2) Low-noise data, clear signals, trustworthy analytics
3. Reduce Fragmentation
Integrate aggregated On-Chain, Off-Chain, and Market Sentiment data all-in-one platform, no need to switch data analytics tools
(L1) On-Chain, Off-Chain Data, and Market Sentiment
(L2) Seamless Integration & Visualization
(L3) All insights in Hashwei
=> Hashwei delivers real-time, verifiable on-chain flow intelligence powered by Agentic AI. With sub-second latency, full multi-chain coverage, and systematic noise elimination, we provide the smartest, cleanest, fastest entity tracking, orderflow heatmaps, and liquidation signals available today.
User Research Report: The Hidden Costs Dragging Crypto Analytics into a $92M Crisis by 2030
Over the past 12 months, the Hashwei Foundation conducted an in-depth behavioral study across thousands of traders, funds, and power users of leading crypto analytics platforms. The findings are stark and costly.
It's systemic failure quietly eroding capital, confidence, and conviction in data-driven decision-making.
These 4 Problems are killing users and the crypto analytics
1. Data Latency: Market movements happen faster than the data arrives, missing the edge
A 15s (Second) Delay = A $10K Liquidation
Crypto doesn’t wait. A single 15–30 second lag in On-Chain or Derivatives data can trigger:
- Missed entries during pump/dump
- Forced liquidations in volatility spikes
- Chasing false breakouts
EX: “I watched BTC break $108K on my chart, 45 seconds after it happened On-Chain.” (Anonymous Whale, $21M AUM)
2. Data Noise: 99% Junk, 1% Signal, and you’re drowning
Users are bombarded with:
- Wash trading loops
- Spam transactions
- MEV bot spam
- Fake airdrop txs
- Sybil wallet clusters
=> Result? Alert fatigue. FOMO trades. Rug-pull exposure. The real alpha? Buried under digital garbage.
3. Data Fragmentation: Insights are scattered across too many tools
Average user's workflow:
Check volume => Tool A
Check whale flow => Tool B
Check DEX liquidity => Tool C
Check CEX orderbook => Tool D
Check On-Chain holders => Tool E
Check metric => Tool G
Manually sync in Notion/Excel 🥲
Cost of fragmentation:
=> 2 - 3 hours lost per deep analysis session
=> 41% of insights are outdated by the time they’re compiled
=> Zero cross-validation = blind spots = rug pulls
Fragmentation doesn’t just waste time. It creates dangerous blind spots.
4. High Cost, Negative ROI: Users pay premium (SaaS model) prices for data that delivers subpar value and negative ROI.
Average yearly spend on analytics: $1,200 (retail) → Over $10,000 (funds)
Average ROI from current tools: -12% to +3% (self-reported P&L attribution)
Industry-wide waste (GetLatka, 2024):
=> $35M–$50M/year on inaccurate, delayed, noisy data
=> Projected 2030: $75M–$92M, a growing black hole
Users are not investing in intelligence. Users are subsidizing inefficiency.