Streamlined Environmental Assessments with accurate, compliant documentation
EnvironmentalAI
Highlights
We developed an intelligent system leveraging AI to significantly improve the efficiency and accuracy of environmental assessment documentation
This platform enables environmental specialists to rapidly generate compliant, standardized reports by analyzing regulatory documents and project specifications. Our solution employs a specialized Retrieval-Augmented Generation (RAG) architecture, ensuring factual integrity by exclusively utilizing verified source materials – drawing upon a knowledge base of over 4,000 documents scraped from public sources – thereby mitigating the risk of inaccuracies.
Key features include modular document generation with user feedback integration,
secure document storage with preference-based retrieval, transparent source visualization, and exportable final reports. Users can upload project specifications, select pertinent context documents, review and refine content iteratively, and export formatted environmental assessments.
By strictly grounding content generation in relevant, verifiable sources, our system produces reliable, high-quality documentation suitable for regulatory submissions.
Tech Stack:
Frontend
Next.js
Firebase
ShadCN
RTK Query
Backend
Python
FastAPI (API, WebSocket)
Postgres
Pinecone
S3
OpenAI
LangChain
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