A conversational AI assistant built inside Smarteeva’s Docusaurus ecosystem to transform how implementation specialists, support engineers, and QA teams find technical answers. Smart Assist reduces search time from minutes to seconds using a hybrid RAG pipeline, version-aware retrieval, and citation-backed responses.

A full-stack automation platform that enables both technical and non-technical users to create, enhance, and execute stable Playwright tests using natural language or recorded browser scripts. The system uses AI to normalize unstable Salesforce selectors, runs tests on GitLab CI via Docker, and returns full video evidence and HTML reports in a clean, human-readable UI.

A unified, AI-powered internal platform that generates, reviews, and publishes release notes automatically from Jira stories across multiple Salesforce-based product packages. Designed to eliminate manual documentation work, enforce consistency, and give non-technical teams full control over release communication.

A React Native mobile app that enables field teams, quality specialists, and support staff to submit, review, and track MDR-related complaints instantly from anywhere. Designed to reduce reporting delays, simplify data entry, and modernize Smarteeva’s complaint-management workflow for on-site use.

A complete end-to-end redesign of Smarteeva’s internal Admin Portal — including dashboards, data tables, notifications, billing, user management, MDR search, and foundational UI patterns. The new design system streamlined daily operations, reduced navigation steps, and established a scalable enterprise interface for future AI-driven tools.

A complete transformation of Smarteeva’s legacy decision-tree tool into a modern, visual rule-building environment with instant preview, guardrails, and intuitive branching. The redesign reduced configuration errors, accelerated admin workflows, and became the core logic engine powering multiple regulatory modules.

A unified platform for testing, comparing, and validating LLM outputs across multiple models and environments. Designed to help engineering, QA, and R&D teams benchmark model performance, diagnose failures faster, and centralize all prompt testing workflows into one predictive, visual system.