AI System for Money Cleanliness

# AI Architect / OSINT & Risk Intelligence Platform (AML, Due Diligence, Source of Funds) ## Overview I am looking for an exceptional AI Architect / Senior Full-Stack Engineer to design and build what I believe could become the next generation of Risk Intelligence platforms. This is **not** a simple AML tool. The vision is to build an intelligent investigation platform capable of aggregating information from hundreds of data sources in order to generate a transparent risk assessment on an individual or a legal entity. The banking industry is only one application. Swiss banks, for example, perform extensive due diligence and source-of-funds investigations before accepting clients. I want to create a platform that goes even further by centralizing every legally accessible source of information and helping analysts make faster, more informed and evidence-based decisions. The system must never replace human judgment. Instead, it should provide: * relevant evidence, * confidence scores, * explainable reasoning, * complete source traceability, * and a structured risk assessment. --- ## Long-term Vision The platform should become an investigation assistant capable of answering questions such as: * Who is this person? * Who ultimately owns this company? * Are there indications of financial crime? * Is there evidence of sanctions exposure? * Politically exposed person (PEP)? * Negative media? * Litigation? * Regulatory actions? * Corporate network? * Asset ownership? * Previous bankruptcies? * Cryptocurrency exposure? * Source of wealth indicators? * Source of funds indicators? * Hidden relationships between entities? * Network visualization? * Timeline of events? The objective is to significantly reduce investigation time while improving the quality and consistency of risk assessments. --- ## Data Sources The architecture should be designed to connect with many different categories of sources, including for example: * Company registries * Court records * Insolvency databases * Government publications * Sanctions lists * PEP databases * Open corporate registries * News archives * Social media (where legally permissible) * Public procurement data * Leaked datasets where legally usable * Cryptocurrency blockchains * Beneficial ownership registers * International watchlists * Customs/trade data * Aviation and maritime registries * Property registries * Open APIs * Commercial data providers * Future proprietary data connectors The system must remain modular so new connectors can easily be added. --- ## AI Capabilities The platform should include: * Multi-agent AI architecture * Retrieval-Augmented Generation (RAG) * Entity Resolution * Knowledge Graph * Relationship Mapping * Explainable AI * Semantic Search * Risk Scoring Engine * Natural language querying * Timeline generation * Automated report generation * Confidence scoring * Duplicate detection * Identity resolution * Cross-language search --- ## Technical Stack (Open to Suggestions) * Python * FastAPI * React / Next.js * PostgreSQL * Neo4j * Elasticsearch / OpenSearch * Vector Database * Docker * Kubernetes (future) * Cloud-native architecture * LLM integration * Agent framework --- ## Security Requirements Security is critical. The platform should include: * Encryption * Fine-grained access control * Complete audit logs * Data provenance * Source attribution * GDPR-aware architecture * Explainable decisions * Secure API integrations --- ## Who I'm Looking For I am **not** looking for someone who simply writes code. I'm looking for someone who enjoys solving difficult problems and who can contribute to the architecture of a world-class investigation platform. Ideally you have experience in one or more of the following: * AML / KYC * Financial Crime * Risk Intelligence * Due Diligence * OSINT * Knowledge Graphs * AI Agents * LLM Systems * Entity Resolution * Graph Databases * Search Engines * Data Engineering * Cyber Intelligence * Compliance Technology --- ## First Phase The first milestone will consist of designing the overall architecture and building a functional MVP capable of: * searching a person or company; * querying multiple data sources simultaneously; * consolidating the results; * resolving duplicate identities; * presenting the findings in a single interface; * generating an explainable preliminary risk report with complete source attribution. If the collaboration is successful, this will become a long-term project with many additional phases.