LLM-Powered SaaS Platform with Human-in-the-Loop AI Workflows

Built and integrated LLM-assisted workflows inside a full-stack SaaS product, contributing across AI features, Lovable frontend development, PostgreSQL data flows, APIs, and QA-driven delivery.

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Tech Used

Problem

Modern SaaS products increasingly need AI features that work reliably inside real user workflows rather than as isolated demos. The challenge was to combine user-facing interfaces, persistent application data, backend services, and reviewable AI outputs in one production-oriented system.

Approach

• Developed LLM-assisted workflows that transformed application data into summaries, structured drafts, recommendations, and actionable insights
• Worked on prompt design and structured output generation for application-ready AI responses
• Implemented and refined user-facing interfaces using Lovable together with frontend code
• Connected frontend functionality with persistent PostgreSQL-backed workflows
• Integrated AI features with backend APIs and application data flows
• Collaborated closely with backend developers on API contracts, data structures, debugging, and end-to-end feature behavior
• Worked with QA to reproduce issues, validate AI and frontend behavior, test edge cases, and improve release quality
• Applied human-in-the-loop patterns so generated outputs remained reviewable and editable before final use

Results

• Delivered LLM capabilities as part of a complete multi-user SaaS application rather than standalone prototypes
• Connected AI, frontend, database, and backend services into practical end-to-end user workflows
• Improved product reliability through iterative testing and close collaboration with QA and backend engineering
• Implemented reviewable AI interactions suited to business processes where human oversight is important
• Demonstrated cross-functional product development across AI integration, UI implementation, databases, APIs, testing, and delivery

Demo Videos