Designing each customer’s solution, turning use cases such as KYC status, employee or student IDs, qualifications, age checks, membership and AI-agent payment mandates into a Developer Toolkit design (issuance and presentation flows, wallet model and build method) that the customer’s architects can sign off
AI architecture and context engineering. Design the context augmentation pipelines, spanning vector RAG, CAG, agentic file exploration, Text-to-SQL, knowledge graphs, fine-tuning, and MCP-based context engineering, and select the right approach for each use case. Select chunking strategy, embedding models, and retrieval architecture for user-owned document systems with multi-tenant isolation. Privacy and security guides each decision.
