Arcanna.ai
Decision Intelligence in Cybersecurity
Overview
Arcanna.ai is an AI-powered cybersecurity platform developed to enhance decision-making and efficiency within Security Operations Centers (SOCs).
By using Decision Intelligence, Arcanna.ai can analyze vast amounts of data that SOCs deal on a daily basis without missing any alerts.
By using deep learning and natural language processing, Arcanna.ai integrates the team's shared knowledge and make efficient decisions reducing the response time to threats, and preventing analyst burnout.
Role & Responsibilities
I am responsible for the entire end-to-end design process and I work closely with cross functional teams, to create experiences from ideation to execution.
My contribution to Arcanna.ai has been wide-ranging, here will provide you with some examples.
User Experience Design
User Interface Design
Interaction Design
User Research
Information Architecture
Design Systems
Prototyping
Challenges
Arcanna.ai's dynamic startup environment is characterized by
constant innovation that demands prompt iterations. As a result,
the platform's user experience frequently faced challenges such as:
constant innovation that demands prompt iterations. As a result,
the platform's user experience frequently faced challenges such as:
Design inconsistencies
Clarity and consistency are essential for a cohesive, user-friendly experience. When icons lack clear meaning, fonts are inconsistent, element sizes vary, the color palette is limited, and components don’t align in style, the result can be confusion and a disrupted user flow.
Lack of user guidance and visibility
Clear visibility into processes is essential for a seamless user experience. When steps lack transparency or guidance, users can be left uncertain about what to do next, causing frustration and slowing their progress.
Agnostic data
Working with agnostic data often leads to massive volumes of data that lack clear patterns or consistency. This makes organizing, analyzing, and extracting insights a complex and time-consuming task, ultimately impacting efficiency and clarity.
Data contextualization with AI-powered insights
Without the right context, agnostic datasets are challenging to analyze, leaving analysts to sift through volumes of information without a clear direction. This often forces them to rely on multiple external tools and screens, costing valuable time and slowing down response efforts.
Solutions
Establish UI consistency & tackle component issues
- Create a design system that standardizes and ensures consistency in UI elements across the entire platform.
- Streamline the user experience by providing a cohesive, intuitive interface.
Improve user guidance and visibility
- Optimize user flows to provide clearer paths and reduce confusion.
- Introduce industry standards and best practices for consistency and clarity.
- Leverage familiarity with other tools to improve ease of use and reduce the learning curve.
Flexible, customizable data tables
- Build adaptable, user-friendly tables capable of handling diverse data types and large volumes, without sacrificing performance or usability.
- Offer dynamic customization options so users can personalize tables based on their specific needs, enhancing the ability to work with different datasets.
- Prioritize intuitive navigation to ensure smooth interaction, even with complex or large datasets, improving the overall user experience.
Contextualize data with flexibility and AI assistance
- Create a component that enables users to enrich alerts with additional context from any external system, providing more comprehensive insights.
- Integrate AI assistance to boost the contextualization process, empowering analysts with smarter, context-aware recommendations.
The design system gives the development team all the needed basic variations, ensures consistency across the UI and streamlines the users experience across the platform.
The Job Overview dashboard delivers critical metrics in a clear and organized manner, enhancing decision-making and reducing the time spent searching for information.
The Integrations section enables users to browse, create, and manage integrations in a cohesive and organized manner, streamlining the overall experience.
The Feedback section table handles all types and volumes of data, helping users stay organized and focused. It enables users to quickly and easily provide feedback, ensuring they never lose track of critical information.
The Code Block component enables users to seamlessly add additional context to their alerts, regardless of whether they are coding experts or beginners, enhancing the relevance and accuracy of their analysis.
The AI Assistant enhances everything on the platform, including the Code Block component, by providing smart context recommendations, helping users make faster, more informed decisions while saving valuable time.
$5.45M
raised by Arcanna.ai in investment funds
