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Unified Intelligence,
where strategy meets execution

Understand More. React Faster. Invest with Precision.

Architecture

  • Deep Learning Framework
    Multi-Modal Input
    Pre-Training
    Fine-Tuning
    Model Retraining
    Feedback Loops

Portfolio Intelligence

A large pre-trained AI model with real-time financial data retrieval, deep learning techniques for market predictions and multi-agent system for auto executing of financial tasks.

Purpose-built for professional investors, it offers real-time market insights, risk assessments, and hyper-personalized financial planning.

Portfolio Intelligence
A modular AI engine that creates hyper-personalized investment strategies by aligning each client’s risk profile, goals, and constraints with optimized portfolio decisions. It delivers real-time, explainable insights for portfolio monitoring and strategy refinement. Combining machine learning with rules-based automation, it integrates seamlessly into institutional workflows for scalable, client-centric investment management.
  • LSTM Time-Series Models forecast asset trends and volatility to match client risk profiles.
  • Hyper-Personalized Strategies tailor portfolios to individual goals and constraints.
  • RAG Reasoning delivers strategy insights grounded in client context and market data.
  • Neural Classifiers detect patterns and rebalance portfolios based on client profiles.
  • Free-Text to Strategy lets users generate tailored strategies using natural language.
  • Virtual Testing Lab simulates real-time outcomes for client-specific strategies.
  • Real-Time Risk Detection to instantly detect changes in risk exposure, enabling fast responses.
  • Predictive Analytics of risk events by analyzing trends, macro-economics and historical data.
  • Automated Risk Mitigation by recommending adjustments to minimize risk exposure proactively.
  • Customized Alerts delivers tailored alerts directly highlighting portfolio shifts requiring attention
  • Real Time Compliance Monitoring and oversights on portfolio alignment and internal policies.
Risk Management
Advanced AI-driven quantitative models identify, assess, and mitigate investment risks by continuously detecting shifts in risk exposure. This provides proactive decision-making by triggering real-time alerts and automating portfolio rebalancing to maintain optimal risk levels.
Trade Execution
Robo Trading uses AI to generate quantitative trading rules that define exact trade conditions. These rules power automated strategies by monitoring market data and triggering alerts or executing orders via secure APIs when criteria are met.
  • AI-Generated Rules generate quantitative trading rules, ensuring precision and adaptability.
  • Condition Monitoring constantly evaluates market conditions to detect opportunities.
  • Just-in Time Alerts & Auto-Orders,triggered by AI generated events and conditions
  • API-Based Execution routes srders through APIs to connected brokers for rapid execution.
  • Seamless Automation for fully autonomous robo-trading, reducing bias and increasing efficiency.
  • Real-Time Data Analysiscontinuously processes market data to inform investment decisions.
  • Trend Recognition detects short- and long-term market patterns for timely action.
  • Technical Indicator Monitoring like VIX, Puts/Calls, News and MACD to guide trading strategies.
  • Sentiment Analysis measures investor sentiment from news, social media, and analyst reports.
  • Workflow Optimization automates information flows across investment processes.
Investment Operations
AI models streamline investment operations by analyzing real-time data, tracking market trends, and monitoring technical indicators and sentiment. This enables faster, more accurate decisions, efficient portfolio adjustments, and reduced operational friction.

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