Capital Management with Machine Learning.
Grow with Confidence.

Synertree SaaS

Make Better Decisions when It Counts

At Synertree, not only we build automation and optimization processes, but we also build trust. By focusing on rule-based approaches, professional users built stronger principles with higher levels of capability and consistency. As a result, stronger advisory relationships were formed. A great decision tree is built by many good decisions, start making yours today.

Build Scientific Process with Machine Learning

Streamline Your Investment Management Practice

Collect Data

Modeling on Cloud

Analyze & Test

Manage & Execute


Integrate sciences into your management process. Focus on the BIG picture.

Optimize asset allocation

Set up asset allocation rules and keep the portfolio running as you intended. Reblance investment portfolios according to the total risk metrics or individual asset risk levels. Optimize asset allocations for the portfolio based on risk or risk adjusted return metrics.

Minimize fixed costs

Lower your infrastructure cost to — Zero. Portfolio managers can simply initiate and quickly scale immediately. All while keeping their overhead costs low. Updates and maintenance are automatic. Run your portfolio management practice with less headaches and more powers.

Manage risks with data

Risks can happen without a warning. A systematic risk management approach is required to keep your portfolios in check. The risk engine automatically provides updates on the dollar amount that is at risk. Instead of approximating risks, portfolio managers can monitor portfolio volatility and asset price risks on the dashboard.

Engage with visual results

Our capital management software are built with your clients in mind.  We combine data and behavioural science to generate quality inputs and meaningful insights for your clients’ financial goals. Focus on client engagement and let the automated system guides the discovery process.

Integrate familiar technologies

Use your data to enrich your portfolio management practice. Works with Factset, Microsoft Excel and CSV, Interactive Brokers. Analyze your past performances and draw down risks. Build, test, and optimize trading strategies based on different technical rules.

Generate signals and act

Visualize how a trade could affect the portfolio risk quantum — before you make the trade. With data science, you can preview risks using historical data, allowing you to better manage your compulsions and respond to risks orderly and systematically. Market is always unpredictable; your actions don’t have to be.

Technical Features

Data Analytics & Visualization

  • Data plotting with Java scripts, Python lib, and Excel
  • Multi-level vectorization for super fast simulations
  • Task and schedule automation
  • Python Scikit-learn and Numpy for data analytics and machine learning

Quantitative Finance

  • Functional and non functional programming
  • Structured arrays for asset allocation
  • Financial time series modeling and regression analysis
  • Parallel computing and the Monte Carlo Algorithm
  • Constrained optimizations

Security Data Management

  • Historical EOD data for North American ETFs and Stocks
  • Fundamental data for stocks
  • Cloud-based interface built by Django
  • Security data management with Postgres database
  • Generate and export stock data in CSV

Helping Professionals helping others

Fund Manager

Risk Management

Price Simulations


Equity Analysis

Momentum tests

Portfolio Manager

Asset optimizations

Financial profiling

Equity Research

ETF management

Chief Investment Officer

Data-driven Modeling

Event-driven Modeling

Hedging Strategies

Risk Analytics

Model Management

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