A persistent AI memory that captures and organizes knowledge for reuse across AI tools.
Product memo
Professionals and researchers using AI tools often struggle with fragmented context and knowledge loss across different platforms. myNeutron AI solves this by creating a persistent AI knowledge base. It captures context from web pages, files, and AI chats, making that information searchable and reusable with any AI model. This approach reduces wasted effort and builds continuity into AI-assisted work.
For who
Professionals and researchers using AI tools
Solves what
Scattered AI context and knowledge loss across tools
- Persistent AI memory
- Context capture from web/files
- Semantic search and recall
In their own words
The AI Knowledge Base That Builds on Everything You Know.
Start with context, not from scratch.
Save anything - pages, files, notes, and your best AI chats - and turn it into searchable, reusable understanding you can use in any AI.
Commercial cues
Model
hybrid
Free tier
Yes
Trial
Available
Pricing Strategy
- • Tiered subscriptions align usage limits with the needs of individual professionals.
- • Annual plans offer significant discounts, driving commitment from power users.
Operator context
Operating setup
Founded
Oct 2025
Platform
Web app
Audience
Creators
Social footprint
Tech stack
Market demand
myNeutron AI keyword demand
5 keywords
Market demand is Starter-tier market intelligence.
Derived from this product’s latest SimilarWeb keyword mix — directional demand, not proof.
Builder Strategy
- Strategy Type
- Niche Specialist
- Stage
- Vc Growth
- Effort
- Small Team
About myNeutron AI Expand
MyNeutron AI helps professionals and researchers overcome the challenge of scattered AI context and knowledge loss. It acts as a centralized AI memory, capturing information from web pages, files, and AI conversations.
This collected data then becomes searchable and reusable, ensuring that valuable insights are not lost across different AI tools. The platform's positioning around persistent memory and context capture aims to reduce redundant work and enhance the continuity of AI-assisted projects, making it easier to maintain a cohesive knowledge base for ongoing research and professional tasks.