Visual AI Research Assistant for Insight Generation
Reveal hidden patterns in your knowledge and find gaps to generate new ideas.
Watch an Introduction
Works for Humans and LLMs
InfraNodus uses network science to represent your ideas as a knowledge graph and reveal the most important topics, concepts, and relations. This representation helps you (or your LLMs) see latent clusters of ideas that you can develop further and reveal structural gaps in your knowledge. Use the built-in AI to bridge these gaps and generate new ideas and insights.
Ecological Dynamics for Your Research Process
InfraNodus analyzes the structure of a discourse you study to optimize its variability: when the ideas are dispersed, it will recommend new connections; when they're too dense, it will encourage disruptive thinking.
You can use our live text editor, or copy and paste an existing text, import research papers or Google Scholar / PubMed / arXiv search results. InfraNodus will provide direct visual feedback to reveal recurrent patterns and themes, so that you (and your LLM) get a structured high-level overview of the main ideas and relations between them.
Seeing the text as a network graph will encourage you think of the new connections. Take particular notice of the gaps as these are connections you haven't thought of before that are relevant to the discourse because they connect the existing topics in a new way.
Remove the most obvious terms from your discourse to reveal what's hinding behind them. Use the network as an heuristic tool to stimulate your thinking process by focusing on the concepts and relations you find interesting.
Use the buit-in AI (any model, all included in subscription) and network structure insights to generate research questions and innovative ideas.
MCP Server or n8n Node for Your Favorite LLM
You can use InfraNodus in your favorite LLM client like Claude Web or ChatGPT via our MCP server.
https://mcp.infranodus.com
{
"mcpServers": {
"infranodus": {
"command": "npx",
"args": ["-y", "infranodus-mcp-server"],
"env": {
"INFRANODUS_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
You can also connect InfraNodus to n8n via our official n8n node.
Use Cases for Research and Ideation
Here are some of the workflows we propose for research and ideation:
-
Generate New Ideas from Patents
Import patent search data and reveal the gaps to generate new ideas.
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InfraNodus MCP Server to Boost Your LLM
Steer your LLM's thinking process and generate new ideas.
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Uncover Hidden Research Gaps
Use the graph to reveal the structural gaps in any discourse.
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Analyze Spreadsheets with Graphs
Scraping data with Manus AI and analyzing it with InfraNodus.
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Use Case: Generate New Ideas from Patents
Problem: Need to generate new ideas from patent search results?
Patent applications contain a lot of information, but how do you generate new ideas from them?
Solution: Use InfraNodus to visualize the patent search results and reveal the gaps.
When you visualize the patent search results as a knowledge graph, you can reveal the gaps between claims and clusters of ideas. This is where the new inventions are hiding.
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Use Case: Boost Your LLM with InfraNodus
Problem: Your LLM is not able to generate original ideas and gets stuck with generic responses?
Standard LLM RAG workflows are not suitable for generating original ideas. They will generate the most probably content and you want the most original content.
Solution: Connect the InfraNodus MCP server to your favorite LLM to guide its thinking process and generate new ideas.
InfraNodus will convert user prompts into graphs and overlay them on top of the knowledge base graph. It will then follow the graph's edges to retrieve important relational context and add it to the LLM context window to improve the response quality. This is usually referred to as GraphRAG and enables you to get more original and relevant responses.
Watch the Video
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Use Case: Uncover Hidden Research Gaps in Any Discourse
Problem: What is the discourse missing? How could it be developed further?
Most AI tools provide an overview of the discourse, but what about what's actually missing?
Solution: Use InfraNodus to visualize the discourse as a knowledge graph and reveal the structural gaps.
Revealing the gaps helps you see how the existing ideas could be connected in a new way, generating creative insights and new ideas.
Learn More
Try It Out
Use Case: Analyze Research Spreadsheets with Knowledge Graphs
Problem: How to reveal patterns in large datasets?
Large datasets are hard to analyze. We can build a tagcloud from spreadsheets, but it won't reveal any structural insight about our dataset.
Solution: Use InfraNodus to visualize the data as a knowledge graph and reveal the patterns and relationships.
When you visualize the data as a knowledge graph, you can reveal the patterns and relationships between the data. This is where the new insights are hiding.
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Examples of the Public Graphs Made with InfraNodus
Below are some of my ideas I made public to showcase how InfraNodus can be used for creative thinking
Start Using InfraNodus
Sign up for an account now, so you can try this tool for brainstorming and idea generation.
How Text Network Analysis Works
Network analysis and graph visualization help you cope with the informational overload and make sense of data.
Here is how it works:
1. Add Any Text or Data
You can use this approach for your research, creative writing, marketing feedback study, SEO purposes, news analysis, etc.
Add any text (speech-to-text available), notes, or import your Gephi graph, Evernote data, Twitter feed, or Google search results snippets.
The text is converted into a graph where the words are the nodes and the co-occurrences are the connections between them, so you can see all your disjointed bits and pieces of data at once, as a big picture.
2. Get a Visual Overview
The network will then be generated from the text or data you added. The most influential words in the graph (nodes with the highest betweenness centrality) are shown bigger, while the words (nodes) that occur more often together are aligned into topical clusters and have distinct colors.
The graph will show you not only the main topics and the most influential terms, but also the relations between them, making it a much better visual summary tool than the traditional tagclouds.
3. Generate Insight
InfraNodus will identify the structural gaps in the network: parts of the graph that could be connected but are not.
It will propose you the different ways how you can bridge these gaps to produce insight and generate new ideas.
You can use GPT AI to generate research questions, facts, or ideas based on the structural gap identified in your discourse using network analysis.
Our Methodology in Detail
To learn more about the algorithms used in InfraNodus and for citations, please, refer to this peer-reviewed paper:Paranyushkin, D (2019). InfraNodus: Generating Insight Using Text Network Analysis, Proceedings of WWW'19 The Web Conference, www.infranodus.com (ACM library, PDF).
If you want to know more about the algorithms used, here is the first paper we published on the subject:
Paranyushkin, D (2011). Identifying the pathways for meaning circulation using text network analysis, Nodus Labs. (Google scholar)
More InfraNodus Use Cases
InfraNodus can be used for many other purposes. Here are just some of them:
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Sentiment Analysis of Product Reviews (topic modeling)
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Text Mining with Networks (discourse structure analysis)
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Visual Google Search (a great way to get an overview of any topic)
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Network Analysis (community detection and node ranking algorithms)
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Visual Arts and Music (sculpt your thoughts and play music with graphs)
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Search Engine Optimization / SEO (finding the untapped keywords)
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Scientific Research (generate insight from your writing)
Become a Supporter!
InfraNodus is open-source software and is developed without external funds or investors. We develop and maintain this tool and the associated research based on your contributions only. We believe it is a working model for crowdfunded software made by users for users.
You can support our work if you become a subscriber and get access to the cloud version or if you become our patron on Patreon. Enterpise, government, and educational versions are also available.
Pricing Options
Your support is what makes it possible for us to develop this tool. All quotas are per each text. There is no limitation on the number of texts you can process every month. Prices do not include VAT for EU private customers.
Lock in current prices for life and save up to 35% (€100-€200) on our annual plans.
Advanced Account
saving €204 or 35%
- 14-day free trial
- everything on the Basic +
- API access
- Dedicated support
- 2 Mb per upload
- 5 Mb per PDF upload
- Extended data import quotas
- 100 GPT-4 credits / hour
- Live graph updates (max 5)
- Commercial use
Basic Account
saving €84 or 35%
- 14-day free trial
- Community support
- Full graph analytics
- Chrome / Firefox extension
- Obsidian graph view plugin
- Import data from web sources
- Max 40 imports per source
- 300 Kb per file upload
- 1Mb per PDF upload
- 40 GPT-4 AI credits / hour
- Personal / Academic use
Premium Account
- 14-day free trial
- everything on Advanced +
- API integration support
- Training: 1 hour / month
- 10 Mb per upload
- 50 Mb per PDF upload
- Max import quotas
- 500 GPT-4 credits / hour
- Live graph updates (max 20)
- Fast-track required features
InfraNodus vs. Other Tools
Traditional tools focus on keywords and not the relations. They use tables, not graphs, and lack search intent data.
without InfraNodus
- No visual insights, just text
- AI thinks for you and leads your thinking
- Generic ideas based on most likely next token predictions
- Not possible to plug into your LLM workflows
- No custom reasoning logic
with InfraNodus
- Beautiful interactive knowledge graphs
- AI thinks with you, you lead the AI
- Original ideas based on content gaps and missing connections
- Use API to plug into your LLM workflows
- Create reasoning ontologies
About InfraNodus
Gregory Bateson coined a beautiful term: "ecology of the mind". What is a mind that is ecological? It has the ability to have an overview, but it can also zoom into any idea. It embraces diversity, but it can also obsess over one thing when needed. It can discover the obvious, but it can also reveal the things that are hidden and ponder the gaps that have not yet been bridged. Rational and poetic.
InfraNodus is a tool that is developed to help you think this way. It is made to promote ecological dynamics and diversity on the cognitive level. InfraNodus visualises and analyses ideas as a network, revealing the relations and patterns within them, so you can understand the dynamic complexity of how knowledge evolves and explore the nuances of meaning.
We believe that it is especially important today to make this kind of instruments available to everybody. That's why we develop InfraNodus so that it can accessible to everyone, solely thanks to our users' monthly contributions and based on their feedback. This is not a start-up, we don't have investors and an exit strategy. We are here to stay and to evolve.
We are constantly improving InfraNodus based on our users' feedback. We are also currently developing an API to make this way of thinking available to other applications and to enable the use of InfraNodus insights for machine learning and AI applications.
If you like our cause, please, sign up for an account and give it a try, support us on Patreon, or simply let us know that it resonates, because this is the best way to motivate each other.
Dmitry Paranyushkin, the founder
Testimonials
InfraNodus is used by researchers, writers, marketing professionals and corporations. Here's what some of our supporters have to say:
Technical Support
Check out our support pages, so you can see how to create the new network graphs, how to read and interpret them, how to discover the hidden patterns in your data and share the results of your research.
1. How to Create a Knowledge Graph
The most basic way to create a new graph is to use plain text or [[wiki links]] (for detailed ontologies). Each concept / [[wiki link]] is a node, their co-occurrence is the connection between them. Based on this representation, you can build complex reasoning ontologies and knowledge bases which can then be used for ideation and creative thinking and writing. More on Creating the Graphs
2. How to Read and Interpret Knowledge Graphs
Studies have shown that knowledge graph representation makes you think more of connections in your data. You can identify the main elements as well as the relations between them and — most importantly — discover the gaps in your knowledge using the graphs. More on Reading the Graphs
3. How to Develop Your Ideas Using the Knowledge Graphs
Knowledge graphs are great for non-linear reading. Look at the graph, find the part you like, click on the nodes, and you'll see the excerpt of your original data that contains this exact combination. More on Nonlinear Reading
4. How to Import Your Data to Knowledge Graphs
You can import and visualize your text files or PDF documents. In order to do that, just upload the file and InfraNodus will do the rest. More on Visualizing PDFs