🚩Addressed Problems
Web3 research and agentic development are bottlenecked by fragmented data, time-consuming workflows, and unreliable infrastructure. Arbus simplifies this landscape by providing a unified access layer that connects consumers, developers, and contributors—transforming overwhelming market signals into clear, actionable context for both research and autonomous execution.
Inefficient & Time-Heavy Research
Endless market noise makes it difficult to access meaningful insights
Manual workflows create barriers for investors and developers
Real-time monitoring of trends, narratives, and data shifts is practically impossible without AI-driven tools
Fragmented and Unstructured Data Landscape
Market data is scattered across disconnected platforms and tools
Lack of a unified access layer slows down research and integration
Inconsistencies in data quality lead to flawed or incomplete analysis
Poor Use of Social Data
Social media signals are underutilized, reducing intelligence depth
Missed trends and narratives due to lack of structured sentiment analysis
Poor visibility into the actual influence of creators, agents, and projects
High Entry Barriers for Emerging Users
Web3 tools are fragmented and require steep onboarding curves
Non-technical users struggle with data accessibility and tool complexity
Knowledge gaps reduce market participation and speed of adoption
Limited Use of AI in Web3 Research
AI is not effectively leveraged for market analysis and decision-making
Existing tools lack real-time, intelligent insight generation
Developers and users face barriers in accessing AI-powered research capabilities
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