Overview
Integrated an OpenAPI-first documentation process with an AI-powered chatbot to improve the developer experience and reduce onboarding time for third-party integrators using the Card Issuing Platform. The system allowed developers to query API documentation in natural language, retrieve live examples, and explore code snippets — all powered by semantic search and AI reasoning.
Implementation Components
- All APIs for Issuing (Auth, Clearing, Cards, Bank, Report) documented using OpenAPI 3.0
- Hosted static documentation on S3 and routed via Amazon API Gateway
- Embedded chatbot UI in documentation pages to assist with real-time queries
- AI agent trained on Swagger/OpenAPI spec, Postman collections, and implementation FAQs
- Backend AI workflow included semantic indexing (FAISS), embedding models, and query ranking logic
AI Architecture
- API specs and documentation parsed and vectorized using embedding models
- Developer queries passed to AI agent via React widget and routed through AWS Lambda proxy
- Best-match endpoints, parameters, and code examples returned instantly
- Logs and user feedback captured to retrain and tune AI performance
Flow Diagram: Developer query → vector search → semantic matching → OpenAPI snippet response → AI chat UI
CI/CD Practices
- Docs deployed via CodePipeline on each Swagger update
- Versioned APIs automatically discovered and linked via semantic tags
Results
- Reduced average time-to-first-successful-integration from 5 days to < 2 days
- Decreased email support volume by 40% through chatbot-led resolutions
- Provided faster contextual help, boosting developer confidence and sandbox engagement
Highlights
- Blended OpenAPI rigor with conversational UX
- Built with extensibility for future LLM upgrades
- Empowered non-experts to navigate a complex platform autonomously