Case study / Project archive
ResearchPilot
A research-assistance prototype exploring Amazon Nova, document context, and cited reports.
Historical team prototype; individual contribution is not independently established. AI-assisted portfolio development.
The idea
The problem
A research answer should retain its source context. Explore query planning, source collection, ranking, and report assembly as inspectable stages.
The implementation
What I built
The README attributes team lead, backend, Nova Act integration, and orchestration to Gaurav; this is a historical self-described role, not an independently audited commit attribution.
Features
- Decompose a research query, gather web/document context, and synthesize a cited report.
- Rank source embeddings with FAISS or an in-memory cosine-similarity fallback.
- Keep report formatting and optional voice input/output in separate modules.
Architecture
- A Python orchestrator coordinates Bedrock, web search, document reading, synthesis, embeddings, and output formatting.
- Search has a Nova Act path plus a requests/BeautifulSoup fallback; configured services and a no-key demo are distinct execution modes.
Engineering decisions
- Keep no-key demonstration output separate from a live provider-backed research run.
Validation and measured results
- Source reviewed on 15 October 2026. The application and its external integrations were not executed in this review.
- Reviewed orchestration, embedding ranking, and both web-search paths. No Nova/Bedrock call, citation audit, or end-to-end research run was performed.
Limits and unfinished work
- A formatted report and confidence field do not establish factual accuracy, source completeness, or research quality.
- Older source can contain superseded descriptions. Numerical impact, adoption, awards, and deployment claims are not carried into this entry.
Evidence and sources
- Reviewed source and implementation
Public README and selected implementation files; source inspection only, without a reproduced runtime or benchmark. Inspected files: src/orchestrator.py, tools/embedding_search.py, agents/web_search_agent.py.