OpenAI Fine tunning Model and Geo-visual Survey Analysis
Budget: $250 – $750 USD
Project Title:
AI Model Developer with OpenAI Fine-Tuning for Survey Data Analysis and Geolocation Visualization
Project Description:
I’m looking for an experienced AI model developer to design and implement a system capable of analyzing survey responses through an API using OpenAI fine-tuning.
The project involves:
Uploading and linking curated information (~1,500 pages) and multiple datasets.
Use vector matrix for complementary documentation for semantic retrieval and contextual analysis.
Enabling respondents to select a geographic location directly on a Google Maps-based interface.
Each location must be automatically identified via geolocation coordinates (x, y).
The system must generate an automated PDF report that highlights the most frequently selected areas, along with:
A visual map (Google Maps link) showing the most marked zones in red for hotspot identification.
Key Deliverables:
Fine-tuned OpenAI model integrated with API for survey data processing.
Vectorized database for text analysis and retrieval.
Google Maps integration for respondent geolocation input.
Automated PDF reporting system summarizing key geospatial insights.
Dynamic Google Maps link showing red-zone hotspots.
Required Skills:
OpenAI API and fine-tuning
Python (FastAPI or Flask preferred)
LangChain or similar RAG frameworks
Vector databases (Pinecone, Chroma, FAISS, or similar)
Google Maps API and geolocation handling
PDF report generation (e.g., ReportLab, FPDF, or equivalent)
Strong understanding of data visualization and geospatial analysis
Ideal Candidate:
Someone who has previously worked on AI-powered survey analytics, geospatial visualization, or interactive dashboards. Must be able to integrate AI processing with real-world mapping and reporting systems.
AI Model Developer with OpenAI Fine-Tuning for Survey Data Analysis and Geolocation Visualization
Project Description:
I’m looking for an experienced AI model developer to design and implement a system capable of analyzing survey responses through an API using OpenAI fine-tuning.
The project involves:
Uploading and linking curated information (~1,500 pages) and multiple datasets.
Use vector matrix for complementary documentation for semantic retrieval and contextual analysis.
Enabling respondents to select a geographic location directly on a Google Maps-based interface.
Each location must be automatically identified via geolocation coordinates (x, y).
The system must generate an automated PDF report that highlights the most frequently selected areas, along with:
A visual map (Google Maps link) showing the most marked zones in red for hotspot identification.
Key Deliverables:
Fine-tuned OpenAI model integrated with API for survey data processing.
Vectorized database for text analysis and retrieval.
Google Maps integration for respondent geolocation input.
Automated PDF reporting system summarizing key geospatial insights.
Dynamic Google Maps link showing red-zone hotspots.
Required Skills:
OpenAI API and fine-tuning
Python (FastAPI or Flask preferred)
LangChain or similar RAG frameworks
Vector databases (Pinecone, Chroma, FAISS, or similar)
Google Maps API and geolocation handling
PDF report generation (e.g., ReportLab, FPDF, or equivalent)
Strong understanding of data visualization and geospatial analysis
Ideal Candidate:
Someone who has previously worked on AI-powered survey analytics, geospatial visualization, or interactive dashboards. Must be able to integrate AI processing with real-world mapping and reporting systems.