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Executive SummaryAI TechnologyInteractive ExamplesUser ScenariosRoadmapTeam

Lead the AI Revolution in Finance with Us

Harness AI-driven forecasts to transform personal finance and accelerate your growth.

Executive Summary:

  • Company Purpose:
    • Provides AI-powered investment analysis accessible to everyone.
    • Converts complex data into straightforward insights for both beginners and experts.
  • Market Opportunity:
    • Capitalizes on a trillion-dollar fintech boom.
    • Addresses soaring demand for personalized, real-time financial guidance.
  • Innovative Solution:
    • Delivers real-time AI forecasts for stocks, crypto, and more.
    • Simplifies advanced data with easy-to-use dashboards.
    • Offers tiered subscriptions that fit any budget or skill level.
  • Technological Edge:
    • Utilizes machine learning and NLP for live, accurate forecasts.
    • Automates risk-balanced strategies tailored to each user’s goals.
    • Runs on scalable infrastructure designed for high-volume performance.
  • Growth Strategy:
    • Forms strategic alliances with brokerages and fintech leaders.
    • Expands into key markets in Europe, North America, and Asia.
    • Continuously evolves features with user feedback and market shifts.
  • Investment Appeal:
    • Serves a rapidly growing market for AI-driven finance tools.
    • Generates revenue via subscriptions, withdrawal fees, and B2B integrations.
    • Emphasizes financial education, building trust and long-term user loyalty.
  • Invitation to Join:
    • Seeking investors and co-founders passionate about democratizing finance.
    • Together, revolutionizing personal finance with AI for global impact and sustainable growth.

AI Technology:

Sources Types

  • Robust Data Integration:
    • Comprehensive Data Collection: Our AI systems gather vast amounts of data from diverse financial markets, including real-time data streams from stock markets, bond markets, cryptocurrency exchanges, and economic indicators.
    • Multi-source Aggregation: By integrating data from financial news, social media sentiment, and macroeconomic indicators, our AI provides a holistic view of the investment landscape.
  • Advanced Analytical Engine:
    • Deep Learning Models: Utilizing state-of-the-art deep learning techniques, our AI analyzes complex patterns and trends that affect market movements and asset valuations.
    • Predictive Analytics: Our models predict future market behaviors by learning from historical data, helping to forecast price movements and market trends with high accuracy.
  • Real-Time Probability Calculations:
    • Dynamic Risk Assessment: AI algorithms calculate the probabilities of various market outcomes, allowing for dynamic risk assessment and management tailored to individual risk profiles.
    • Precision in Predictions: By processing vast datasets, our AI delivers predictions with high numerical precision, enabling users to make decisions based on reliable probabilities rather than mere speculation.
  • Diverse Investment Analysis:
    • Equities and Bonds: AI-driven insights into stock and bond markets, providing users with advanced portfolio management tools and investment strategies.
    • Cryptocurrency Specialization: Special algorithms tailored to the volatile nature of cryptocurrencies, offering users insights into potential gains and risk mitigation strategies.
  • Personalized Investment Analysis:
    • Customized Portfolio Suggestions: Based on individual user profiles, which include risk tolerance, financial goals, and investment preferences, our AI suggests optimized investment strategies.
    • Adaptive Learning: Our system adapts to changes in user preferences and market conditions, continuously refining recommendations to suit evolving needs.
  • Transparency and Explainability:
    • Insightful Reporting: We provide users with clear explanations of how decisions are made, what data was considered, and why specific investments could be good for him.
    • User Empowerment: By demystifying the complexities of AI, we empower users to understand and trust the insights provided, fostering confidence in their investment choices.
  • Regulatory Compliance and Security:
    • Data Security: Adherence to the highest standards of data protection and privacy, ensuring all user information and transaction data is securely managed.
    • Compliance First: Our technology is built to comply with all relevant financial regulations and ethical standards, ensuring peace of mind for our users.

Interactive Examples:

Asset: Insight Questor

Price exceeded price 100 $

User Scenarios:

  • Regular Users (Individual Investors):
    • Personalized Analytics: Leveraging AI to analyze financial goals and market conditions, providing users with detailed insights into potential market movements and trends.
    • Market Forecasts: AI-powered forecasts that help users understand future market scenarios, aiding in their financial planning without direct recommendations.
    • Automated Alerts: Notifications about significant predicted market changes relevant to their financial interests, facilitating informed decision-making.
  • Professional Traders:
    • Real-Time Market Analysis: Access to sophisticated analysis tools that deliver comprehensive insights and forecasts about market trends.
    • Trading Signals: AI-generated signals based on predictive market behaviors, supporting traders in strategizing their trades more effectively.
    • Risk Management Tools: Advanced tools for assessing and managing potential risks identified through AI-driven market forecasts.
  • Casual Savers:
    • Savings Insights: Automated insights based on AI forecasts, suggesting optimal times for saving based on predicted financial trends and personal spending patterns.
    • Investment Insights for Beginners: Data-driven insights into potential market movements, helping users understand when might be a better time to invest or save.
    • Progress Monitoring: Tools that visualize financial growth, influenced by AI predictions on market conditions and personal finance trends.
  • Business Clients (SMEs):
    • Tailored Financial Analysis: Custom analytics that incorporate AI forecasts of market conditions, tailored to specific business needs and industry trends.
    • Cash Flow Predictions: Predictive analytics for cash flow, providing businesses with foresight into financial planning and management.
    • Investment Strategy Support: Support tools that use AI-generated market forecasts to help align business investment actions with expected market developments.
  • Hedge Funds:
    • Advanced Portfolio Analysis: Comprehensive analytics including detailed forecasts of market trends that impact various investment strategies.
    • Algorithmic Trading Support: Algorithms that utilize AI-generated forecasts to automate trading decisions based on predicted market shifts.
    • Compliance Monitoring: Ensuring adherence to financial regulations with tools that incorporate future regulatory changes predicted by AI.
  • Financial Startups:
    • Scenario: Emerging fintech companies leverage our AI technology to enhance and expand their financial service offerings.
    • AI Application: By integrating our AI, startups gain access to comprehensive analytics, powering their services with advanced insights and improved decision-making capabilities.
    • Usability Highlight: Our platform’s API-first design ensures seamless integration, allowing startups to efficiently implement sophisticated features and scale their operations with minimal technical overhead.

Roadmap:

Year 1: Initial Development & Alpha Version (Months 1-12)

Budget: ≈ €3,500,000

Phase 1: Organizing the structure of the future project and Hiring a team (Months 1-3)
  • Hiring technical and financial specialists
  • Development of the concept of the first version
  • Design and project and construction of the AI learning model
  • Office rental and relocation of all specialists requiring relocation
Phase 3: Alpha Version Prototype & Internal System Testing (Months 6-9)
  • Creating a basic 'Alpha prototype' of the platform, focusing on backend and data flow (not user-ready yet).
  • No real AI predictions yet; this step focuses on data accuracy, system stability, and backend workflows.
  • Internal testing on basic financial calculations and system reliability, ensuring that AI has the correct data inputs.
Phase 5: Application Development (Months 9-12) - parallel
  • Design UI/UX first version for beta-app functional is ready
  • Data Base organisation, prepared first version of backend
  • Application interface is developing (not user-ready yet).
Phase 2: Initial AI Algorithm Development (Months 3-6)
  • Collecting, clean, and process large financial datasets with the help of finance experts.
  • Developing the framework for AI models (without actual prediction generation)
  • Finance experts guide the data features and market variables the AI will eventually predict
Phase 4: AI Model Prototyping & Alpha Refinement (Months 9-12) - parallel
  • AI engineers build 'early models' for stock prediction, but the outputs are still in testing and refinement stages.
  • Finance experts validate that the initial model predictions align with real-world financial scenarios.
  • Build initial design prototypes for the 'news list' and 'personalized analytics', though they will be non-functional at this stage.
Year 2: Feature Expansion & Full Launch (Months 12-24)

Budget: ≈ €4,500,000

Phase 7: External Beta Testing Preparation (Months 15-18)
  • Refining AI models based on feedback from finance experts and initial data.
  • Preparation Beta version for external testing but (do not launch externally yet)
  • Finalizing the Beta platform's structure: stock forecasts, personalized analytics, news integration, and trading instruments.
Phase 9: AI Scaling & Feature Expansion (Months 21-23)
  • Fine-tune personalized analytics based on external testing results.
  • Expand trading instruments and refine the news feed integration.
  • Continue to refine user interface and experience based on user feedback.
Phase 6: Beta Version Development (Months 12-15)
  • Alpha testing with focus groups of first functions
  • Fixing issues and beginning building the 'Beta version' with basic stock forecasting features and personalized analytics.
  • Expand AI capabilities based on Alpha results, but predictions are still early-stage.
Phase 8: Limited External Beta Testing (Months 18-21)
  • Launch the Beta version for a 'select group' of external users (early testers).
  • Collect feedback on platform performance, AI accuracy, and user engagement.
  • Collaborate with finance experts to validate the accuracy of stock forecasts and ensure the platform is functioning correctly.
Phase 10: Beta Version Market Launch (Months 23-24)
  • Officially launch the 'Beta version' to a larger audience with: - Stock forecasts for the most famous stocks. - Personalized analytics and insights based on user preferences. - A news feed with relevant financial updates. - Trading instruments for executing trades directly on the platform.
  • Beginning marketing push to acquire more users and promote the Beta version.
Year 3: Early Growth Stage (≈ Months 24-36)

Budget: ≈ €4,500,000

Phase 11: Open Beta & Community Growth (Months 25–27)
  • Open access to the Beta version for the general public.
  • Implement referral programs and community-building campaigns.
  • Monitor early metrics like retention, engagement, and feature usage.
Phase 13: B2B Onboarding & Financial Partnerships (Months 29–31)
  • Initiate pilot partnerships with financial firms, banks, and fintechs.
  • Provide B2B clients with dashboard access and advanced features.
  • Set up legal and compliance infrastructure for larger deals.
Phase 15: Break-Even Readiness & Market Expansion Prep (Months 33–36)
  • Align unit economics to approach break-even point.
  • Prepare localization, legal documents, and marketing for US and Gulf region expansion.
  • Develop investor reports and pitch decks for Series A funding.
Phase 12: Monetization Launch & Feedback Loop (Months 27–29)
  • Introduce paid plans for B2C users (monthly/yearly tiers).
  • Collect data on pricing sensitivity and user conversion.
  • Launch feedback loop systems to continuously improve AI insights.
Phase 14: Product Refinement & Infrastructure Scaling (Months 31–33)
  • Optimize backend systems for scalability and cost-efficiency.
  • Refactor AI models for speed and accuracy under real-world loads.
  • Add missing features based on user behavior analytics.
Report 1: Platform Foundation & Data Architecture (Months 6)

Core platform infrastructure and data architecture are in place. Financial datasets have been collected, and the AI framework has been established. The system is ready for Alpha development.

Report 2: Alpha Version Prototype & AI Model Development (Months 12)

The Alpha prototype is operational, focusing on system stability and financial data accuracy. Early AI models for stock forecasts are under development, with input from finance experts guiding model training.

Report 3: Beta Development & External Testing Preparation (Month 18)

The Beta version is under development, featuring stock forecasts and personalized analytics. External Beta testing is being prepared, and the AI models are being refined based on initial internal feedback.

Report 4: External Beta Testing & AI Scaling (Month 22)

Limited external Beta testing is underway, and AI models have been scaled for improved prediction accuracy. User feedback is being collected, and preparations for full market launch are progressing.

Report 5: Market-Ready Beta Version (Month 24)

The Beta version is ready for market release.

Report 6: Monetization Launch & B2B Pilot Programs (Month 30)

The platform has initiated monetization through paid subscription tiers. First B2B pilot integrations have begun with select financial partners. Initial revenue metrics and user conversion rates are under evaluation.

Report 7: Product Optimization & Scaling Infrastructure (Month 33)

Ongoing refinement of AI models, user interface, and backend architecture is underway. Technical infrastructure has been scaled to support increased user load and data processing demands in preparation for market expansion.

Report 8: Break-Even Readiness & Expansion Strategy (Month 36)

The platform is approaching break-even. Preparations for entering new markets (US, Gulf region) are finalized, including legal, compliance, and localization efforts. A Series A investment round is being prepared to fund expansion.

Team:
Nikita Pletnev
Founder & CEO
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  • Phone(EU):
  • LinkedIn:
Christina A. Saks
Co-Founder & COO
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Dmitry Sergeev
CTO
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Jukka Hemmi
CFA
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