Logo

Advanced platform for data management, development, and analytics

Problem

  • Challenge: Companies face challenges in data migration, analysis, and development processes, which slow down innovation and efficiency.
  • Why It Matters: Efficient data management is crucial for optimizing operations, accelerating decision-making, and maintaining competitiveness.

Solution

  • advanexus Solution: advanexus addresses data management complexity by utilizing advanced algorithms for generic database transfer, enabling seamless integration, fast analysis, and customizable solutions that simplify business processes.
  • Unique Advantages:
    • Delay Elimination: Continuous real-time data transmission.
    • Speed & Efficiency: Optimized data transfer speed for greater efficiency.
    • Process Simplification: Streamlined development and operations.

Advanexus Key Advantages

Functionality advanexus Databricks Databox Semantix ClicData IDexcel IBM DataStage Alteryx Cloudera Snowflake Talend Google BigQuery Informatica Qlik Tableau Looker Domo
Data Connection ✅ ✅ ✅ ✅ 🔄 🔄 ✅ ✅ ✅ ✅ ✅ ✅ 🔄 🔄 ✅ 🔄 ✅
Automation of Key Tasks ✅ ✅ 🔄 🔄 ✅ 🔄 ✅ ✅ 🔄 ✅ ✅ ✅ ✅ 🔄 ✅ 🔄 ✅
Automatic Process Generation ✅ 🚫 🚫 🚫 🚫 🚫 🚫 🚫 🚫 🚫 🚫 🚫 🚫 🚫 🚫 🚫 🚫
Data Processing Speed ✅ ✅ 🔄 🔄 ✅ 🔄 🔄 🔄 ✅ ✅ ✅ ✅ 🔄 🔄 🔄 🔄 🔄
Real-time Data Quality ✅ 🔄 🔄 🔄 ✅ 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄
Sandbox for Data Transformation ✅ 🔄 🔄 🔄 🔄 🔄 🚫 🚫 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄
Intuitive Analytics and Visualization ✅ 🔄 ✅ 🔄 ✅ ✅ 🚫 🔄 ✅ ✅ ✅ ✅ ✅ 🔄 🔄 ✅ ✅

Legend:

  • ✅ : This platform or functionality has excellent support or offerings for the given feature.
  • 🚫 : This platform or functionality is not specifically focused or provides limited support for the given feature.
  • 🔄 : This platform or functionality provides a moderate level of support or functionality for the given feature.

Advanexus: Technical Superiority

Parameter advanexus Databricks Databox Semantix ClicData IDexcel IBM DataStage Alteryx Cloudera Snowflake Talend Google BigQuery Informatica Qlik Tableau Looker Domo
Non-Technical User Friendly ✅ 🚫 🔄 🔄 🔄 🔄 🚫 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄
Data Engineer Friendly ✅ ✅ 🔄 🔄 🔄 🔄 ✅ ✅ ✅ ✅ ✅ ✅ 🔄 🔄 ✅ ✅ ✅
Data Scientist Friendly ✅ 🔄 🔄 🔄 🔄 🔄 🚫 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄 🔄

Legend:

Proficiency Level Non-Technical User Friendly Data Engineer Friendly Data Scientist Friendly
✅ Highly proficient (Advanced) The platform is designed to be highly user-friendly for non-technical users, requiring minimal technical knowledge. The platform is highly friendly for data engineers, offering advanced features and capabilities. The platform is highly friendly for data scientists, offering advanced tools and features.
🔄 Moderately proficient (Intermediate) The platform provides a moderate level of user-friendliness for non-technical users, with some technical knowledge required. The platform provides a moderate level of friendliness for data engineers, with some advanced features. The platform provides a moderate level of friendliness for data scientists, with some advanced tools.
🚫 Less proficient (Basic) The platform may have limited user-friendliness for non-technical users, requiring significant technical knowledge. The platform may have limited friendliness for data engineers, with fewer advanced features. The platform may have limited friendliness for data scientists, with fewer advanced tools.

Market Size

Market Size in 2020 (in billion dollars) Size in 2030 (in billion dollars) CAGR (%) Fastest Growing Market Largest Market Source
Customer Data Platforms 4.67 47.68 33.70% GLOBAL GLOBAL Data Bridge Market Research
Customer Data Platforms (Global) 1.16 6.94 25.4% GLOBAL GLOBAL Fortune Business Insights
Customer Data (Global) 1.56 4.8 27.41% Asia-Pacific North America Mordor Intelligence
Autonomous Data Platforms 1.1 4.7 23.0% GLOBAL GLOBAL Grand View Research
Data Science Platforms 96.3 378.7 16.43% GLOBAL GLOBAL Precedence Research
Autonomous Data Platforms (Global) 0.62 4.8 22.8% GLOBAL GLOBAL Allied Market Research

Market Growth: The demand for efficient data management is increasing across industries such as finance, healthcare, and manufacturing.

Traction

  • Current Status: advanexus is in the MVP phase, with technical testing completed and pilot implementations planned.
  • Team Achievements: We are actively working on assembling a team of experts in analytics, software development, and data management to advance the platform post-funding.

Business Model

  • Monetization Strategy: Subscription models tailored to different user needs, with additional services for implementation and support. The platform allows for multi-cloud or on-premises deployment.
  • Additional Revenue Streams: Consultancy services for customizing solutions according to user needs.

Team

  • Founder: Milovan Tomasevic, PhD (CEO/CTO), with experience in data management and software development.
  • Hiring Plan: Further team expansion with specialists in data science and business development.

Call to Action (Ask)

  • Our Need: We are seeking an investment of $300,000 to complete the development of cloud solutions, test scalable generic models for companies, and enable quick deployment within minutes. This funding will also support market entry with initial clients over the next 18 months.
  • What We Offer: An opportunity for investors to be part of a high-growth potential startup, with direct influence on market entry and success.

Logo

Logo Logo