See wallet behavior.
Predict churn.
Engage automatically.
BlockSight profiles wallet behavior and predicts churn, purchases, and engagement risk. The platform acts on those signals automatically — retaining at-risk users, surfacing recommendations, and coordinating incentives in real time.
See. Capture. Act. Repeat.
Facebook built engagement graphs. Amazon built recommendation engines. Netflix built retention systems. In Web2, that's three companies with three data silos. BlockSight unifies all three on-chain — and closes the loop by acting on the intelligence autonomously.
Behavioral Intelligence
The engine profiles every wallet — engagement patterns, churn risk, cross-protocol behavior. Deep predictive modeling across wallets.
Commerce Data
The engine captures purchase behavior in real time. Every transaction feeds the model. Every checkout becomes a data point.
Autonomous Engagement
The agent acts on predictions — triggering retention workflows, surfacing recommendations, adjusting incentives. Protocols plug it in instead of hiring a growth team.
Two products. One behavioral engine. Full-stack intelligence.
BlockSight sees. The agent acts. Each product feeds the next. Accuracy compounds with every interaction.
Behavioral Risk Profiling
Predictive churn modeling, behavioral profiling, on-chain credit scoring. The inference engine that understands who your users are and what they'll do next.
Autonomous Engagement Agent
The action layer. The agent uses BlockSight's predictions to engage users autonomously — retaining the at-risk, converting the interested, and rewarding the loyal.
NASA-Heritage AI Applied to On-Chain Behavior
Our Chief Scientist Dr. Petrus C. Martens spent 30+ years building predictive ML systems for NASA's Artemis program. The same longitudinal modeling techniques now power wallet behavior prediction.
Behavior & Commerce Data Infrastructure
Continuous ingestion from on-chain engagement activity and payment checkouts. Normalized into a unified behavioral schema across multiple chains.
Multi-Task Prediction Engine
Shared behavioral encoder branching into two prediction heads — churn (LSTM + GNN + XGBoost) and purchase (collaborative filtering + sequence model). Multi-task learning where each product improves the other.
Autonomous Engagement Layer
Predictions flow into the decision engine. The AI agent evaluates risk scores, purchase probabilities, and behavioral segments — then autonomously triggers the right engagement action for each wallet.
Infrastructure for institutional participants
Credit Infrastructure
On-chain credit scoring and borrower evaluation beyond simple collateral ratios. Behavioral underwriting for lending protocols and RWA platforms.
Commerce Intelligence
Next-purchase prediction, buyer segmentation, and revenue forecasting for token-gated storefronts and decentralized marketplaces.
Incentive Coordination
Dynamic reward allocation for airdrops and liquidity mining based on behavioral contribution quality — not volume, not sybils.
Institutional Crypto
Counterparty assessment, yield product targeting, and compliance-enhanced analytics for institutional DeFi participants.
Retention Infrastructure
Predictive attrition modeling with automated retention workflows. The platform detects disengagement and acts — weeks before users become permanent churn.
Agentic Commerce
Reputation and service discovery layers for autonomous AI agent coordination. Behavioral intelligence powering the agent economy.
Others analyze. BlockSight acts.
Analytics tools show you what happened. Payment processors move tokens. BlockSight predicts what's next and acts on it autonomously.
Behavioral profiling
Predictive churn modeling
Purchase prediction
On-chain credit scoring
Autonomous engagement
Composable prediction API
Closed-loop data flywheel
Competitive comparison matrix
| Capability | Dune / Nansen | Kaito | Moonpay / Crossmint | BlockSight |
|---|---|---|---|---|
| Behavioral profiling | Basic labels | Attention metrics | — | Deep behavioral embeddings |
| Predictive churn modeling | — | — | — | ✓ |
| Purchase prediction | — | — | — | ✓ |
| On-chain credit scoring | — | — | — | ✓ |
| Autonomous engagement | — | — | — | ✓ |
| Composable prediction API | — | Partial | — | ✓ Full |
| Closed-loop data flywheel | — | — | — | ✓ |
Competitive comparison matrix
Execution to date
Behavioral prediction infrastructure built
Multi-chain ingestion and inference pipeline operational. Models trained across multiple EVM chains.
Private beta — live with first partners
Prediction models deployed to partner protocols.
Public launch — full platform + engagement agent beta
Full platform open. The autonomous engagement agent enters private beta with select protocols. Composable API live.
Engagement agent public launch & enterprise tier
Autonomous engagement open to all. White-label engagement infrastructure. Institutional analytics. Custom model deployments.
Cross-chain expansion & agent APIs
Non-EVM support. Portable behavioral profiles. Agent-to-agent coordination APIs.
Operators and researchers
Domain expertise across blockchain commerce, machine learning, and venture-scale product building.
Devon Martens
- →Architected AI-driven trading engines managing $50M+ in liquidity
- →Led Studio Chain, a Layer 2 for adaptive game economies
- →Unites blockchain commerce, ML, and decentralized reasoning
Adam Cottrell
- →20+ years building distributed systems and real-time infrastructure
- →Aerospace and aviation background; founder of Axonara
- →Deep expertise in AI, RTOS, networking, and production-grade systems
Dr. Petrus C. Martens
- →30+ years of NASA- and NSF-funded research in ML and predictive modeling
- →Large-scale data infrastructure across scientific computing
- →Professor at Georgia State University
Build with BlockSight.
If you're running a protocol, marketplace, or wallet and want behavioral intelligence + autonomous engagement on-chain, drop your details. We read every submission personally.