Built and integrated a production-ready AI support orchestration console, making complex backend workflows usable through a clean, operator-first frontend.
TL;DR
Timeline
Dec 2025
Industry
AI · Enterprise · SaaS
Contribution
Frontend Developer
Problem Space
The core challenge was exposing hybrid RAG orchestration logic in a way agents could trust instantly: confidence cues, citations, escalation outcomes, persona behavior, and ticket context all had to be visible without clutter or state confusion.
Core Interaction Shifts
Key design decisions that shaped the experience.
Operator-Friendly Chat Experience
Mapped orchestration behavior into readable UI states including typing progress, citations/sources, confidence signals, and escalation outcomes.
End-to-End API Integration
Integrated frontend flows with backend endpoints for chat, personas, routing, review actions, analytics, feedback, and health checks with robust error handling.
Scalable State + Component Architecture
Implemented predictable multi-step state flows and reusable typed components so the console remains maintainable as personas, KB sources, and analytics views expand.
Influence & Validation
The orchestration engine became a practical day-to-day product: fast, understandable, and reliable for real operators handling live support workflows.
Complex backend capabilities surfaced clearly without overwhelming the UI
Improved reliability through resilient loading/error handling and edge-case coverage
Reusable typed frontend foundations established for continued feature growth
Read the research at obvix.io/research/obvix-lake
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