Professional platform for everyone

Build. Test. Automate. Without Coding.

Build trading strategies with visual blocks and AI assistance. Backtest your rules, then automate through your connected broker.

Get StartedSee Alphavator in action

The saved Quality Value Momentum 20 trading strategy assembles automatically: market screening, weighted quality, value and momentum factors, Top 20 selection, 5% allocations, and monthly rebalancing. Tickers shown are a saved snapshot. Then Technical Donchian Breakout GLD assembles: Current Price above Donchian Upper buys 100% GLD; below Donchian Lower sells 100% GLD. Both channels use lower length 20, upper length 40, and offset 1. Technical Bollinger Breakout QQQ follows: Current Price above both the 200-period SMA and Bollinger Upper buys 100% QQQ. Price below Bollinger Mid or below the SMA triggers separate 100% sell orders. Bollinger uses length 50, standard deviation 2.1, DDOF 0, and SMA mode. Both indicators use closing prices and offset 0.

Traders want algorithmic trading, but the path to automation is still fragmented and complex.

Intuition is common, systematic trading is the goal, and the middle layer is where most products still break down.

Current reality

Intuition Driven Trading

Many retail trading decisions still follow headlines, social chatter, rumors, or gut feel.

Result

  • Inconsistent outcomes
  • Emotional decision-making
  • No way to improve or scale performance

Core gap

No Path to Systematic Trading

Retail traders still lack one straightforward path from rules to live trades: define a strategy, validate it on data, connect a broker, and automate execution without writing code.

Major Barriers

  • Complex coding requirements
  • Manual and time-consuming backtesting
  • Delayed or missed trade execution
  • Limited strategy logic
  • Data pipelines
  • Broker integrations

Desired state

Systematic Trading

A growing segment of retail investors wants to trade more like professionals.

Desire

  • Defined entry/exit rules
  • Backtested strategies
  • Data-driven decision making
  • Automated execution

How Alphavator works end-to-end.

Set your strategy in the visual builder, validate logic with backtests, run risk checks, then route orders through your connected broker.

Alphavator workflow architectureFundamental data powers Quant Trading, and indicators power Technical Trading. Both connect to the AI Strategy Agent, alongside historical market data through Backtesting and real-time market data through Simulation. The agent connects to Auto Trading, which distributes strategies to four TBOT units.ROEP/ERevenue…1000+SMAMACDRSI…1000+Quant TradingTechnical TradingAlphavatorAI Strategy AgentHistorical market data20 yearsReal-time market data< 20 ms latencyBacktestingSimulationAuto TradingTBOTUnit01TBOTUnit02TBOTUnit03TBOTUnit04

  1. Quant Trading

    Design quantitative stock-selection strategies visually using fundamentals like ROE, P/E, growth, and profitability. Alphavator updates selections dynamically as market conditions change.

  2. Technical Trading

    Create technical strategies with visual blocks for indicators, patterns, and rule logic. Extend them with advanced signals from machine learning, news, and social sentiment.

  3. AI Strategy Agent

    Turn plain text or a YouTube link into a strategy with Alphavator’s agentic AI, then optimize, backtest, simulate, and deploy as TBOT with built-in risk controls and rebalancing.

  4. Backtesting

    Run fast, vectorized backtests across multiple timeframes using up to 20 years of historical data. Evaluate performance with professional-grade metrics and tune with confidence.

  5. Simulation

    Test strategies in live market with paper money and real-time data. Alphavator delivers institutional-grade feeds with sub-20 millisecond latency for responsive simulation and execution.

  6. Auto Trading with TBOT®

    Launch an AI-powered TBOT® built from visual blocks and connected to your broker. Once funded, it runs automatically during market hours based on your strategy rules.

Trust, control, and access to what professional traders build in code.

Alphavator is non-custodial software for user-defined strategies; funds stay at your broker. It does not provide investment advice, discretionary trading, or custody.

Custody

Funds stay in your brokerage account

Alphavator is non-custodial and does not take possession of client funds.

Ownership

Strategies are user-defined

Users create, review, and control the rules that drive execution.

AI Role

AI is assistive only

AI can help draft or refine rule logic, but it does not autonomously trade.

Execution

No discretionary trading

Alphavator does not decide when, what, or how much to trade.

Guidance

No investment advice

The platform provides tooling and workflow support, not recommendations or signals.

Integration

Broker-connected execution

Execution runs through the connected brokerage account using the user configuration.

See how user-defined logic moves from builder to broker-connected execution.

Screen recordings from the real product: you will see how entry, exit, and risk rules are assembled in the visual builder, how those rules are checked against historical data before deployment, and how execution is turned on only for strategies you approve, using your linked brokerage account.

01

Define Strategy Rules

Create user-defined entry, exit, and risk rules in a visual builder.

02

Test Before Deployment

Run backtests and review rule behavior before enabling broker-connected execution.

03

Broker-Connected Execution

Execute the strategy you approved through a connected brokerage account while funds remain at the broker.

04

Build from YouTube

Use content as a starting point, then convert ideas into user-defined strategy rules.

05

Manage Your TBOTs

Monitor deployed strategies, review status, and manage execution from one overview.