Upload PDFs, extract text, build a GraphRAG knowledge graph, identify content gaps, and generate research questions and prompts for immediate use.
The AI agent ingests uploaded PDFs, converts them to plain text, and builds a structured knowledge graph of concepts and their relationships. It analyzes gaps between topic clusters to surface under-connected areas and missing connections. It then generates focused research questions and prompts that bridge those gaps and guide deeper inquiry.
Concrete steps the AI agent takes to transform PDFs into research-ready prompts.
Uploads PDFs to start processing.
Converts PDFs to plain text for analysis.
Constructs a GraphRAG knowledge graph from the text.
Identifies content gaps across topic clusters.
Generates research questions and prompts to bridge gaps.
Presents results in the web interface and supports exporting prompts.
Before using this AI agent, you often rely on manual, time-consuming methods to find questions and gaps across PDFs. The response surface is limited by cognitive biases and fragmented notes. The process can take hours per project with uncertain payoff. You also struggle to connect ideas across disparate sources. Finally, you lack a repeatable way to generate prompts tied to observable gaps.
Three-step system flow that converts PDFs into targeted questions.
Users upload PDFs via the web form or an automated path, triggering the AI agent to begin processing.
The AI agent converts PDFs to plain text and prepares data for graph construction.
The AI agent builds a knowledge graph, identifies structural gaps, and generates research questions and prompts.
A realistic scenario showing time-to-value.
Scenario: A researcher uploads five PDFs (market reports and papers) totaling ~1,500 pages. In about 5–7 minutes, the AI agent returns 18 high-value research questions and 12 prompts ready to deploy in a literature review or an initial study.
Roles that gain measurable advantages from this AI agent.
Need to derive diverse, testable questions across multiple papers quickly.
Must uncover gaps in industry reports and competitive analyses.
Seek gaps in discourse across regulations and public documents.
Require structured prompts to bootstrap research projects.
Need to bridge internal documents with new ideas.
Want to align content plans with uncovered topics and gaps.
Tools and platforms the AI agent works with to run end-to-end.
Builds the knowledge graph, detects gaps, and drives question generation.
Converts PDFs to plain text for graph construction and analysis.
Orchestrates the AI agent into existing workflows and routes results.
Saves PDFs and results for later re-use and collaboration.
Concrete scenarios where this AI agent shines.
Answers to common concerns about using this AI agent.
The AI agent accepts standard PDF documents. You upload files via the web form or connect via an automation path. PDFs are converted to plain text and then analyzed to build the knowledge graph. The results include generated questions and prompts aligned to the identified gaps.
No. This workflow uses InfraNodus GraphRAG APIs for knowledge graph generation and prompt creation, so OpenAI keys are not required. If you choose to hand off prompts to an external AI model, you can configure that integration separately. Data handling remains within the InfraNodus-enabled chain.
Yes. The AI agent is designed to route generated questions to external AI models or experts via your automation setup. This enables seamless handoff and collaboration without leaving your workflow.
The primary deployment uses InfraNodus GraphRAG APIs hosted by InfraNodus. Local or on-premise options depend on your InfraNodus plan. You can operate within your own secure environment if your deployment supports API access to InfraNodus.
Processing time depends on the number and size of PDFs. Uploads trigger parallel text extraction and graph construction, typically delivering results within minutes for moderate workloads. Large corpora may take longer, but the agent returns a structured set of questions and prompts as soon as gaps are identified.
Results are displayed in the AI agent interface and can be exported as prompts or integrated into downstream tasks via your automation platform. You can re-run the analysis with updated PDFs to refresh gaps and questions. The export format is designed to be immediately usable in research workflows.
Data privacy depends on your InfraNodus plan and your chosen deployment. The agent processes PDFs through InfraNodus GraphRAG and your automation connectors; ensure proper access controls and data governance. If handling highly sensitive materials, use on-premise or private-cloud options and limit access to trusted users.
Upload PDFs, extract text, build a GraphRAG knowledge graph, identify content gaps, and generate research questions and prompts for immediate use.
