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Mobiloitte delivers multi-chain DeFi analytics platforms with risk scoring, fraud detection, MEV and whale tracking, wallet clustering, compliance tools, and AI copilot for blockchain teams.
High-throughput ingestion from Ethereum, L2s, Cosmos, Solana, BSC, and more unified in a queryable warehouse/lakehouse core.
Wallet clustering and entity resolution link addresses, trace flows, and surface mixers or risky paths.
Models and rules flag rug pulls, flash-loan exploits, oracle issues, wash trading, Sybil patterns, and odd governance moves.
MEV and whale tracking dashboards watch large players, sandwich patterns, and liquidity shifts across DEXs.
Clear views of treasury, runway, protocol revenue, token design, voter activity, and delegate maps.
Sanctions checks, exposure analysis, travel-rule support, and audit-ready lineage for institutions.
Streaming alerts for risks, liquidation plans, hedges, and governance protections.
Natural-language questions over chain data with grounded RAG and safe tool use.
Test strategies and rules on historical data; simulate risk and alpha scenarios before going live.
Combine on-chain, off-chain, social, and news signals for stronger alpha and risk models.
Institutional/DAO dashboards and rate-limited APIs with RBAC.
Air-gapped/on-prem options, secrets management, RBAC, policy enforcement, and full audit logs.
Many DeFi analytics start as dashboards and become data debt. Mobiloitte treats DeFi intelligence like core infrastructure: consistent schemas, aligned streaming and batch, cost-aware lakehouse design, and governance that works for quants and compliance. Copilot interfaces and alerting help portfolios, protocols, and DAOs see and act before the market.
Well coded Tested pipelines, versioned models, and lineage-first architecture.
Responsive Embedded pods ship risk playbooks, dashboards, and models in short cycles.
Fast growing Built for heavy chain, rollup, and sidechain traffic.
MultipurposeOne stack serves compliance, governance, trading, and risk ops.
Mobiloitte Defines Multi-Chain Coverage, Models, Policies, and KPI Frameworks for Risk and Alpha. The Roadmap Aligns Quant, Protocol, and Compliance Teams.
Chain coverage plan and ingestion SLAs
Unified schemas for transactions, events, positions, liquidity, governance
Catalog of alpha, anomaly, and risk KPIs
Policy and compliance plan (sanctions, AML, reporting, audit)
Build/buy/integrate matrix (The Graph, Dune, Flipside, Nansen, etc.)
Streaming and Batch Pipelines, dbt/Lakehouse Models, Graph/Entity Resolution, Risk ML, MEV/Whale Trackers, LLM Copilots, and BI/APIs Wired With Observability and CI/CD.
Kafka/Flink/Spark ingestion; Airflow/Prefect orchestration
Graph DBs and OLAP engines for clustering and flow tracking
ML for liquidity stress, sybil/rug-pull patterns, and anomalies
Governance “kill switches” and real-time alerting
BI for protocol health, treasuries, fees, and market dynamics
Mobiloitte Runs and Improves the Platform: Retraining, Cost Tuning, Lineage Checks, AML/Compliance Reporting, and HA Production.
Model registry, drift detection, retraining jobs
Automated QA for freshness, schema drift, anomalies
Audit logs, RBAC, masking, sanctions/residency compliance
FinOps dashboards and query performance tuning
24/7 SLAs, incident playbooks, and joint roadmap planning
Agree on chains, KPIs, governance, compliance, and budget. Define schemas, contracts, and scalable pipelines.
Implement multi-chain ingestion, entity resolution, risk/anomaly ML, MEV/whale trackers, and LLM copilots. Validate on history and live streams.
Run the platform with monitoring, documentation, and continuous additions for alpha, risk, and compliance.
EVM (Ethereum, L2s), Solana, Cosmos, Substrate • The Graph, Dune, Flipside, Tenderly • Kafka, Flink, Spark • dbt, Delta/Iceberg/Hudi • ClickHouse, DuckDB, BigQuery, Snowflake • Neo4j/JanusGraph • MLflow, W&B • LangChain/LlamaIndex for LLM copilots
Mobiloitte supports sanctions screening, AML heuristics, exposure analysis, FATF-aligned policies, and end-to-end traceability. The platform lowers risk for institutional funds, DAOs with regulatory exposure, and growing protocols without adding new risk.
They use a normalised schema and a standard event model that hide chain quirks while keeping raw details for deep queries. Pipelines track chain IDs, contract addresses, and decoded events with lineage. Analysts and models can query consistently across ecosystems.
They combine rules for known patterns with anomaly detection and graph analysis for new behaviour. Historical exploits are replayed to test detectors. Models are retrained as tactics change.
Yes. They screen sanctions and exposure, trace the source of funds, and tier risk with audit-ready lineage. Compliance teams get reports, alerts, and role-based access built to pass due diligence.
Real-time streams watch large wallets, validators, pool concentration, sandwich patterns, and gas-market signals. Alerts are threshold-based and tied to risk/alpha dashboards. Models are tuned with client input.
They use graph heuristics, flow similarity, label propagation, and pattern checks over time. Each label has provenance and a confidence score. Client intelligence can be merged with third-party labels.
They start with reconciled revenue, treasury, and fee models, then add governance, token design, and liquidity risk. Views are organised by stakeholder (quant, ops, compliance, DAO). Code is versioned with clear assumptions.
Signals come with explanations, traces, and linked entities, plus suggested playbooks. Feedback loops reduce false positives. Teams see fewer noisy alerts and clearer actions.
Yes. Delegate maps, voting block analysis, proposal simulations, turnout modelling, and incentive-leak checks are included. Cross-protocol views reveal influence networks.
They use ClickHouse/DuckDB, compressed lake formats, partitioning, z-ordering, and vectorisation to speed OLAP. FinOps budgets, auto-scaling, and query SLAs keep latency low and ROI high.
Yes. Air-gapped/on-prem/sovereign setups use open-source LLMs, vector DBs, graph engines, and zero-trust practices. Compliance stays traceable without public-cloud risk.
A multi-chain ingestion plus basic risk/MEV/whale dashboard MVP typically lands in 6–10 weeks, depending on chain coverage. Advanced ML, LLM copilots, compliance workflows, and deep graph analytics follow in 6–12 weeks. Work is phased for early wins.
A governed MVP often ships in 4-8 weeks with clear scope and data; full hardening and scale follow in 8-12 weeks or more.
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If slow dashboards and shallow heuristics hide the truth, Mobiloitte delivers a real on-chain intelligence backbone fast, explainable, and aligned to P&L and risk limits.