A complete Web3 security toolkit combining AI-powered token auditing, ML-based deployer reputation scoring, and live Etherscan V2 data. Includes static analysis for rugpull detection, RandomForest reputation modeling, contract-fetching automation, and Solidity on-chain registries for transparent, reproducible security insights.

A customer intelligence engine that predicts subscription probability, models purchase frequency, and computes a unified loyalty risk score. Includes explainability, segment insights, and a scenario simulator, all integrated into an interactive Streamlit dashboard.

OpenSiteTrust is an open, explainable, and reusable website scoring ecosystem

Actuarial data science project analyzing insurance claims to identify potential fraud and assess customer risk. Includes Python preprocessing, feature engineering, and a stakeholder-ready Tableau dashboard.

AI-powered KYC automation platform with adaptive risk scoring, multi-layer biometrics, OCR, deepfake detection, and cryptographic credentialing. Reduces verification time from 48–72 hours to 8–12 minutes while improving fraud detection to 98.5%.

A production-grade data pipeline that ingests real-time data from government APIs (USGS, NASA, NOAA) to assess natural disaster risk across earthquakes, wildfires, and severe weather.

A collection of medical calculations in Python. Example: MELD score for liver disease.

CryptGuardian is a zero-dependency, advanced blockchain security module designed to detect, analyze, and mitigate threats in real-time. It integrates threat intelligence, pattern-based analysis, timing detection, and deep security alerts, making it a robust tool for monitoring blockchain data integrity.

A multi-agent AI system using Google AI Agent SDK and Gemini to analyze real-time route safety (crime, weather, lighting) and optimize navigation.

Python-based enterprise risk engine for log analysis, anomaly detection, KRI-based scoring and automated narrative reporting. Designed for SMEs, cybersecurity teams and governance functions as part of UK Global Talent technical evidence. A collaborative project by Ibrahim Akinyera (AI/ML Lead) and Busayo Odukoya (Technology Risk Expert).

Full-stack digital payments compliance engine—UPI/RTGS simulator, AML rule engine, ML-based STR detection, SHAP explainability, and audit-ready dashboards.

End-to-end ML demo for clinical risk scoring on synthetic tabular patient data (data → features → models → metrics → FastAPI /predict).

Fake review detection using TF-IDF & SVM (AUC 0.98), plus Counterfeit Risk Score with clustering & anomaly detection.

reinforcement Learning for Vulnerability Prioritization using CISA KEV - DQN achieves 98.4% accuracy with 3,587.50 reward

A lightweight cyber monitoring dashboard for OCI WAF with MITRE mapping, risk-based severity, and multi-tenant attack analytics.

An AI-driven risk assessment tool that evaluates users' login input data (e.g. timing, user label and behavior) to calculate a dynamic risk score. Features include mock data generation, labeled training sets, weighted scoring, and deep learning-based predictions.

A heuristic risk scorer for cloud assets leveraging MITRE ATT&CK mappings and tags to evaluate and score risks. This tool helps in identifying, prioritizing, and mitigating potential vulnerabilities within cloud environments.

🛡️ Strengthen Web3 security with our AI-driven token auditor and reputation engine, ensuring safer transactions and reliable smart contracts.