A focused set of systems that show end-to-end execution: problem framing, architecture decisions, and measurable outcome.
AI Document Assistant
Problem: Teams spent too much time manually searching long documents.
Solution: Built a retrieval system that extracts context and answers user questions instantly.
Technical Approach: Python backend, embeddings pipeline, vector retrieval, and a lightweight chat interface.
Outcome: Reduced document lookup time and improved daily workflow speed.
PythonRAGEmbeddingsSupabase
Voice-to-Content Engine
Problem: Capturing ideas from meetings and voice notes was inconsistent and slow.
Solution: Developed an AI pipeline that transcribes speech and structures it into usable content.
Technical Approach: Audio ingestion API, transcription service, prompt orchestration, and storage for reusable outputs.
Outcome: Automated repetitive documentation and improved publishing turnaround.
PythonAPIsPostgreSQLVercel
Market Research Summarizer
Problem: Manually collecting and summarizing web research across sources was time-intensive.
Solution: Built a workflow that gathers source data, processes content, and generates concise summaries.
Technical Approach: Data collection scripts, normalization, summarization prompts, and API-first delivery.
Outcome: Saved hours of repetitive analysis and improved consistency of reports.
JavaScriptNode.jsNLPAutomation
Workflow Automation Dashboard
Problem: Repetitive status updates and manual process checks slowed internal teams.
Solution: Created a dashboard that tracks workflow states and triggers automated actions.
Technical Approach: Event-driven backend, webhooks, database triggers, and role-based front-end views.
Outcome: Improved process visibility and reduced manual follow-up work.
SupabasePostgreSQLWebhooksHTML/CSS