SpatialRead

SpatialRead is a powerful, nonlinear desktop application designed for researchers, students, and lifelong learners who need to quickly and deeply understand complex academic materials. Moving beyond the limitations of linear "Chat with PDF" tools, SpatialRead transforms passive reading into an active, visual process, helping you structure complex ideas and build a verifiable, connected map of knowledge. It is built for those who require ultimate control over their research data, AI models, and associated costs.

Key Features

SpatialRead combines advanced document analysis with an intuitive spatial canvas, ensuring your insights are never lost in a chat log.

• 🧠 Nonlinear Spatial Canvas: Unlike traditional linear chat interfaces, SpatialRead places every insight, explanation, and connection onto an infinite canvas as a distinct, movable node. This allows you to visually map relationships between concepts, turning scattered highlights into an organized and growing knowledge graph that reflects your natural thought process.
• 💡 Contextual AI Insights: Select any text—from the original document or an existing AI-generated node—to instantly activate research actions like Simplify, Explain, or Expand. This contextual diving capability ensures you can immediately resolve confusion, explore related concepts, and build out deep understanding without losing your place in the primary document.
• 📸 Capture and Analyze Figures: Utilize the integrated Screenshot feature to capture diagrams, charts, tables, and complex figures directly from your research papers. These visuals can then be analyzed by the AI, providing deep, contextual explanations that are essential for truly understanding the methodology and results within technical documents.
• 🔒 Complete Data Privacy (Local Storage): Maintain full control over your confidential research. All uploaded documents and generated knowledge graphs are stored exclusively on your local device. SpatialRead operates without external servers or cloud storage, ensuring maximum privacy and data security.
• ⚙️ Flexible Model Integration (BYOK & Ollama): Choose the best AI assistant for your specific task. SpatialRead supports major cloud providers (OpenAI, Perplexity, Claude, Gemini) via the Bring Your Own Keys (BYOK) model for complete cost control, and offers free, unlimited use of high-quality local models through Ollama and LM Studio integration.

Use Cases

SpatialRead is engineered to streamline and deepen your research workflow, delivering tangible outcomes across various academic and professional settings.

• Accelerate Interdisciplinary Literature Review: When encountering research outside your core domain (e.g., a software engineer reading a bioenergetics paper), quickly highlight complex jargon or formulas. Use the AI to generate simplified explanations that appear as connected nodes, allowing you to establish a foundational understanding of the new field without leaving the context of the paper.
• Synthesize Knowledge Across Multiple Sources: Upload several documents (PDFs, essays, reports) on a related topic. As you read, extract key findings and connect them visually on the spatial canvas. This allows you to synthesize a comprehensive overview of a subject, identifying patterns, contradictions, and critical links between disparate sources that would be difficult to spot in isolated chat logs.
• Cost-Optimized AI Research: For users who conduct heavy research, the Bring Your Own Keys (BYOK) model provides significant cost savings compared to fixed subscription services. By using lower-cost, high-performance models (like Gemini 2.5 Flash Lite) for high-volume tasks, you only pay for the specific AI tokens you consume, ensuring budget efficiency while maintaining access to world-class analysis.

SpatialRead provides structural and functional advantages that redefine how you interact with complex documents, prioritizing user control, insight, and sustainability.

• The Nonlinear Advantage: Traditional "Chat with PDF" apps treat research as a single, disposable conversation. SpatialRead treats research as a permanent, growing knowledge structure. You don't lose insights; you build upon them, fostering genuine information gain by visually linking new concepts to existing understanding.
• Unprecedented Cost Control via BYOK: Instead of being locked into flat monthly fees, SpatialRead empowers you to use your own API keys. This means you can select the most powerful models for critical tasks or leverage highly efficient, low-cost models for routine queries, paying only for the exact computational resources you utilize. This approach often results in substantially lower monthly costs for high-volume users.
• Free, Unlimited Local Model Use: SpatialRead is completely free to use with local, self-hosted models via Ollama. This ensures that every learner has access to powerful AI research assistance without any financial barrier or subscription lock-in, provided they have a capable machine.

Conclusion

SpatialRead is the essential tool for active researchers and dedicated learners seeking to move beyond passive document consumption. By combining visual knowledge mapping, deep contextual AI analysis, and robust control over data and costs, SpatialRead ensures that your research process is as dynamic and interconnected as your own thinking.