On-Chain Surveillance Platform
Real-Time Protocol Surveillance & AI-Powered Intelligence
Raksha gives blockchain foundations, regulators, and capital deployers a single pane of glass to monitor the protocols they care about. From oracle manipulation and access control violations to protocol health risks, every alert is enriched by AI agents and delivered through configurable workflows — so your team can investigate faster and your non-technical staff can create custom alerts using plain language.
SURVEILLANCE MODULES
Every detection module is continuously fine-tuned by AI agents based on what's actually happening on-chain — new attack patterns, shifting market conditions, emerging vulnerabilities. Set your own thresholds, choose which protocols to watch, and let the platform adapt.
Cross-validates Chainlink, Pyth, and Uniswap TWAP prices simultaneously. Flags divergences above your configured thresholds before they can be exploited as arbitrage vectors.
MVPDetects anomalous single-transaction borrowing patterns, rapid borrow-repay cycles, and correlated price movements across monitored protocols. Fires before the next block confirms.
MVPTracks admin key usage, ownership transfers, proxy upgrades, and privileged function calls across your watched protocols. Surfaces unexpected governance changes in real time.
MVPUnified surveillance across Ethereum, Base, and Arbitrum. Detects coordinated multi-chain activity that exploits bridge messaging latency and cross-chain price gaps.
MVPSurfaces suspicious activity that didn't result in an exploit — yet. Identifies probing transactions, failed attack attempts, and abnormal position build-ups before they escalate.
MVPWhen an alert fires, AI agents automatically correlate on-chain data, governance events, and historical patterns to deliver a root-cause summary — not just a number, but a narrative your team can act on.
MVPNon-technical staff can create custom surveillance rules using plain English. Describe what you want to watch — the platform translates it into on-chain monitoring logic automatically.
MVPTracks USDC, USDT, DAI and algorithmic stablecoins for depeg events. Critical for foundations and vaults where stablecoin collateral is the primary risk surface.
MVPContinuous monitoring of Total Value Locked across protocol contracts. Detects sudden outflows, deposit spikes, and anomalous TVL shifts that may indicate an active or impending exploit.
MVPTracks undercollateralised positions and bad debt accumulation across lending markets. Surfaces accounts where collateral value has fallen below outstanding borrows before liquidations cascade.
MVPMonitors utilisation ratios across lending vaults and yield strategies. Alerts when pool utilisation approaches critical thresholds that constrain withdrawals or amplify liquidation risk.
MVPTriage, acknowledge, and escalate alerts via Telegram, Discord, Slack, or REST webhooks. Configurable severity routing with team-level access controls and full API access for custom integrations.
MVPSEE IT IN ACTION
PRICING
Raksha is built for ecosystem foundations managing dozens of protocols, regulators who need visibility across chains, and capital deployers like vaults who need to monitor their exposure — without the overhead of enterprise security suites.
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FOUNDING TEAM
Raksha is founded by operators with deep roots in capital markets surveillance, blockchain infrastructure, and AI research.
Built trade surveillance systems for tier-1 exchanges at LSEG/Millennium IT across Europe, Africa, and Asia. Deep expertise in manipulation detection, real-time monitoring, and regulatory-grade alerting.
Applied machine learning across anomaly detection, time-series forecasting, and risk scoring models. Building the intelligence layer that separates signal from noise in on-chain data.
Scaled oracle infrastructure to $1B+ TVS across 80+ chains at Supra Oracles. Hands-on experience with attack surfaces from the inside — not just the theoretical level.
GET INVOLVED
Join the waitlist for early access or become a design partner to shape the platform alongside our founding team.
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