Idea Network × Idea Interflowing · Live
Infrastructure for agents, an inspectable workspace for people
Idea Network organizes papers, authors, concepts, citation relationships, source evidence, and research state into an environment agents can call directly. Idea Interflowing applies that environment to pre-experiment direction discovery, proposal formation, and evidence review. It reports what it found while explicitly labeling not-found evidence, uncertainty, and graph blind spots.
How It Works / Three core capabilities
General models excel at retrieving and summarizing within the known. Idea Interflowing works on the structure of the citation network itself — where the gaps are, where the frontier is heading, and how cross-disciplinary connections hold up.
Locate the "voids" in the citation network — the structural gaps surrounded by dense citation yet truly reached by no one. Agents then work out which not-yet-posed research question each void corresponds to.
Identify a field's current research frontier, trace its advance along the time axis, and answer the hardest and most valuable question of all: where is the next breakthrough most likely to appear?
Find inspiration along real academic relationships and generate candidate hypotheses where fields intersect. Not free association, but reasoning along the real structure of the citation network — every hypothesis carries an evidence chain that traces back to the source.
Live Workflows
Idea Creator turns a direction into a structured proposal. Idea Supervisor grounds review judgments in inspectable evidence paths. Both workflows are developed and live.
Start from a research direction and follow connected papers, concepts and citations to find structural gaps worth pursuing. Separate established evidence, refutable hypotheses and open validation work, then deliver a structured proposal ready for review and execution.
Review a paper or completed body of work against target-venue dimensions and expose the evidence path behind every judgment. Explicitly separate graph-confirmed evidence, graph-not-found results and graph blind spots so each score can be challenged and refined.
FAQ / Frequently asked
Idea Network is an agent-native research knowledge environment that organizes papers, authors, concepts, citation relationships, source evidence, and research state. Idea Interflowing is the pre-experiment research-decision SaaS built on it, applying those capabilities to direction discovery, proposal formation, and evidence review.
Ordinary literature tools help find and read relevant content. Idea Network goes on to show how those works connect and evolve; Idea Interflowing applies those relationships and evidence to direction discovery, proposal formation, and review. Key judgments link back to source evidence and distinguish graph-confirmed, not-found, and blind-spot results.
Idea Creator turns a direction and connected evidence into a structured proposal. Idea Supervisor reviews a paper or completed body of work against target-venue dimensions and exposes evidence paths, not-found results and graph blind spots. Both workflows are live.
Yes. Idea Network has a public preview at wentor.ai/network. Idea Interflowing is live at interflowing.ai and continues to iterate in beta.
Citation records retain their sources and can be traced individually. Our deep-research framework and knowledge graph connect citations, claims and source evidence, while marking items not seen in the graph and graph blind spots. This reduces the risk of fabricated references and misattribution; researchers still verify critical judgments.
Both products are live: let agents find evidence in Idea Network, then turn judgments into inspectable deliverables in Interflowing.
Product Feedback / Co-create
The product is live. Share a real research problem and your contact details to help us calibrate the workflow.
Glue literature, code, experiments, and writing into a single local research operating system.
Learn more → Idea NetworkResearch knowledge environmentFollow citation structure, source evidence, and persistent research state through agent-callable tools.
Open product ↗ Research FDEInstitutional field adaptationTranslate one real laboratory task into data boundaries, acceptance metrics, and a procurement scope.
Learn more →