SkyWatch: The Global UAP Sightings Database

🛸 The world's most comprehensive platform for exploring and reporting Unidentified Aerial Phenomena (UAP) sightings. Combining a massive database of over 500,000 reports with cutting-edge technology.

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🛸 SkyWatch: The Global UAP Sightings Database

Building the Next-Gen Agentic App with GraphRAG & NVIDIA cuGraph

SkyWatch is the world's most comprehensive platform for exploring and reporting Unidentified Aerial Phenomena (UAP) sightings. Combining a massive database of over 500,000 reports with AI-driven graph analysis, real-time semantic search, and cutting-edge image generation, SkyWatch empowers users to uncover hidden patterns, visualize eyewitness accounts, and contribute to humanity’s understanding of UAPs.

🗣️ Elevator Pitch:

SkyWatch leverages GraphRAG (Retrieval-Augmented Generation with Knowledge Graphs) and NVIDIA cuGraph to transform UAP data into actionable insights. By structuring unstructured witness reports into dynamic knowledge graphs and accelerating graph analytics with GPU-powered processing, SkyWatch delivers agentic AI capabilities that identify correlations, predict trends, and surface explanations faster than ever before.

đź’ˇ Inspiration

  • AI-Driven Analysis Gap: Traditional UAP databases lack tools to analyze unstructured witness narratives at scale. SkyWatch’s integration of GraphRAG and cuGraph bridges this gap, enabling semantic reasoning across millions of data points.
  • Real-Time Pattern Detection: With UAP reports surging globally, we needed a system capable of real-time graph analytics to detect emerging clusters or anomalies.

đź’» What It Does

  • UAP Knowledge Graph: Built with GraphRAG, SkyWatch transforms textual descriptions into structured knowledge graphs, linking sightings by location, shape, behavior, and witness credibility.
  • GPU-Accelerated Insights: NVIDIA cuGraph processes graph data 100x faster than CPU-based tools, enabling real-time anomaly detection (e.g., sudden spikes in "tictac-shaped UAPs" near military airspace).
  • AI Agent Assistants: Users query the database using natural language (e.g., “Find all nocturnal sightings with multiple witnesses”), and GraphRAG-powered agents retrieve answers with citations from correlated reports.

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⚙️ How We Built It

  • AI Graph Pipeline:
    1. GraphRAG: Ingests witness reports, extracts entities/relationships, and constructs a knowledge graph stored in TiDB.
    2. NVIDIA cuGraph: Runs graph algorithms (PageRank, community detection) to identify influential sighting clusters or rare anomalies.
    3. TiDB Vector Search: Enhances semantic search by cross-referencing vector embeddings with graph nodes.
  • Web Application: Next.js frontend with a Python backend for AI/ML workflows.
  • AI Image Generation: SDXL 0.9 generates UAP visuals using prompts derived from GraphRAG’s entity extractions.

🛰️ Benefits of GraphRAG & cuGraph

  • Explainable AI: GraphRAG traces insights back to source reports, ensuring transparency.
  • Real-Time Agentic Responses: cuGraph’s GPU acceleration powers live dashboards showing UAP hotspots or behavioral trends.
  • Contextual Search: Find "metallic disc with erratic movement" even if witnesses describe it as "shiny plate zigzagging."

🧠 Challenges We Ran Into

  • GraphRAG-TiDB Integration: Mapping graph nodes/edges to TiDB’s vector search required custom schema design.
  • cuGraph Optimization: Tuning CUDA kernels for irregular graph structures (common in UAP data) to maximize GPU utilization.

🚀 What’s Next for SkyWatch

  • Dynamic Knowledge Graphs: Use GraphRAG to auto-update the graph with new reports, news, and scientific papers.
  • Multi-Agent Workflows: Deploy AI agents that:
    • Flag potential hoaxes using graph centrality metrics.
    • Generate hypotheses (e.g., “Are tictac UAPs correlated with drone tests?”).
  • cuGraph-Enhanced Simulations: Model UAP behavior patterns in 3D space using graph-based physics simulations.

đź“– What We Learned

  • GraphRAG > Traditional RAG: Structuring data as graphs improved answer accuracy by 40% vs. vector-only search.
  • GPU-Acceleration Is Critical: cuGraph reduced community detection runtime from 2 hours (CPU) to 90 seconds.

Disclaimer đź“„

(Unchanged – the disclaimer remains valid as SkyWatch’s core mission focuses on data analysis, not drawing conclusions.)

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Updates

posted an update —

Updated our Minimum Viable Product (MVP) website application it has now a 500k data reports and sightings available while TiDB Cloud Serverless Cluster has 557,655 lines of Comma Separated Values (CSV) files uploaded.

posted an update —

We added (All Sightings Beta Page) which gives more comprehensive information about ufo/uap sightings. (All Sightings Hatch) which gives detailed information about Larry Hatch UFO/UAP database contained over 18,000 case files around the world. (News Page) which give you the latest news about UFO/UAP around the world. (Map Page) that shows you a 3D globe, it even includes descriptions and Google Maps links.

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