How it works
You design the strategy.
AI agents execute it.
A team of autonomous AI agents researches markets, debates trades, manages risk, and executes on HyperLiquid - 24/7, fully transparent, adapting in real-time.
The flow
Three steps.
That's it.
No coding. Define what you want, deposit funds, and your agents start working.
Design your strategy
Pick pairs, set risk level, choose indicators, and tell the agents how aggressive to be. Or grab a pre-built strategy from the marketplace.
Deposit & activate
Bridge funds from Ethereum or Base, deposit into your strategy vault, and hit activate. Your AI agents spin up and start analyzing markets.
Watch them trade
Agents research, debate, and execute 24/7. Every decision streams live to your dashboard - you see what they're thinking and why.
The cycle
What happens every cycle
Your agents run a full analysis cycle autonomously. They decide when to run next - rechecking in minutes during volatile conditions, or waiting hours when the market is quiet. No fixed schedules. The agents adapt.
Gather intelligence
Live prices, technical indicators, social sentiment, and on-chain data - everything the agents need to understand the market right now.
Form a thesis
The Strategist analyzes the data and decides: buy, sell, or hold? It builds a trade plan with entry, stop-loss, and profit target.
Check the risk
The Risk Manager independently reviews every trade. Too risky? Too big? It can approve, adjust, or reject - no rubber stamps.
Execute the trade
Approved trades go to HyperLiquid with stop-losses, take-profit levels, and slippage guards - all placed automatically.
Monitor & protect
The Monitor watches positions 24/7 and can close early if the thesis breaks. It autonomously decides when the next cycle runs - rechecking in minutes during high volatility, or waiting longer when the market is calm.
Report everything
Every cycle produces a transparent summary. You see what was analyzed, what was decided, and why - in real time.
Under the hood
The nitty-gritty
Beyond the main cycle: timers, self-healing, and guardrails that keep your desk running 24/7.
Agent-controlled timers
In "agent" frequency mode, the Monitor decides when the next cycle runs. Volatile market? Recheck in 1–5 min. Quiet? Stretch to 1–2 hours. Minimum interval is configurable (e.g. 1 min). Open positions or big moves trigger a shorter fallback so the desk doesn't sit idle.
Watchdog
Every minute the scheduler checks all active strategies. If a strategy lost its timer (e.g. after a restart), it gets restarted using the configured cycle interval. No manual intervention - the system self-heals.
Evolution & auto-health
Every N cycles (e.g. 25), if the strategy has had no trades for a long streak, an LLM diagnoses why and can propose adjustments: cycle interval, prompt tweaks, signal exclusions. Applied changes create a new strategy version with a changelog.
Execution guards
Trade cooldown between trades; loss-streak cooldown (e.g. 3× normal cooldown after consecutive losses); max trades per day; drawdown limits. The Monitor is fed the current guard status so it doesn't infer from stale thread history.
LEVELS & MEMORY
The Monitor can output consensus levels (LEVELS: SUPPORT=… RESISTANCE=…) and a structured MEMORY block (thesis, key levels, patterns, warnings, lessons) so the next cycle has cross-cycle context - no amnesia between runs.
Your AI team
Three agents. One goal.
Specialized AI agents that challenge each other - so bad trades get caught before they happen.
The Strategist
Finds trading opportunities by analyzing charts, news, social media, and on-chain data. When it spots a good setup, it creates a detailed trade plan.
The Risk Manager
Reviews every trade the Strategist proposes. Is it too risky? Too big? It can approve, shrink the size, or reject entirely.
The Monitor
Watches open positions 24/7. If the reason for a trade stops being true, it can close the position early. It also decides when the next cycle runs - recheck soon when volatile, or later when quiet.
How they work together
The Strategist wants to trade. The Risk Manager wants to protect. This tension means only high-quality trades get through.
Your choice
You pick the model
Every strategy runs on the LLM you choose. We pull from 200+ models via OpenRouter - one API, every major provider. Pick budget, standard, or premium; the catalog is filtered for models that support tools and structured outputs so your agents can actually run.
One model per desk
When you configure a strategy or fund, you select the model that powers the Strategist, Risk Manager, and Monitor for that desk. Same brain for the whole team.
Tiers by cost
Budget for high-frequency cycles, standard for balance, premium when you want the strongest reasoning. Per-cycle cost is shown so you can tune for speed vs. quality.
Production-ready only
The picker only lists models that support tool calling and structured outputs, with enough context for full cycles. No guesswork - if it's in the list, it works with CoreX.
Model selection is in your dashboard when you create or edit a strategy, or when you configure a fund. Default is Gemini 2.5 Flash; switch to Mistral, Claude, GPT, or dozens of others in one click.
Intelligence
Where the data comes from
Your agents pull from multiple real-time sources - no guessing.
Live prices & charts
Real-time price feeds, order books, funding rates, and volume from HyperLiquid.
Technical indicators
45+ indicators - RSI, MACD, Bollinger Bands, Supertrend, Ichimoku, and more across all timeframes.
Social intelligence
Real-time monitoring of 20+ crypto Twitter accounts. AI scores relevance and impact.
Market events
Funding rate spikes, liquidation cascades, volatility shifts, open interest surges.
Web research
Agents search for macro news, catalysts, on-chain metrics - with source citations.
Technical edge
Patterns & indicators
Agents get a real-time snapshot of 45+ indicators and structured pattern signals across any timeframe - no manual chart reading.
Indicators
Computed in real-time for every timeframe. Agents reference these by name in their analysis - all available out of the box.
Patterns & signals
Deterministic detectors and compiler tokens the Strategist can combine in natural language.
- Volume - confirmation, spike detection, OBV divergence, participation score
- Crosses - EMA/SMA crossovers, RSI threshold, MACD signal line
- Consolidation - squeeze detection, BB width compression, Keltner/Donchian range
- Trend - ADX strength, EMA ribbon, Supertrend, Ichimoku cloud position
- Momentum - RSI/MACD/StochRSI alignment, ROC acceleration, TSI divergence
- Reversion - VWAP stretch, BB band touch, RSI extremes, CMF divergence
- Volatility - ATR regime (cool/hot), Keltner expansion, historical vs implied
- Candlesticks - engulfing, hammer, doji, harami, kicker, shooting star, morning/evening star, three soldiers
- Multi-timeframe - HTF alignment, divergence detection, VWAP anchored, indicator confluence scoring
- On-chain - funding rate spikes, OI shifts, liquidation cascades, whale activity
Continuous improvement
How the agents learn
Cross-cycle memory, trade lessons, and auto-health evolution keep the desk from repeating the same mistakes.
MEMORY block
The Monitor outputs a structured MEMORY block every cycle: thesis, keyLevels, patterns, warnings, lessonsApplied. The next cycle receives this as context - no amnesia between runs.
thesis: "Long bias, watching 101k support"
keyLevels: "101200, 99800"
--- END MEMORY ---
Trade lessons
After each trade (or batch), the system can attach lessons: category, content, confidence. These are injected into the next Strategist prompt so the agent avoids repeating bad entries or ignores learned warnings.
Evolution & auto-health
Every N cycles (e.g. 25), if the strategy has had no trades for a long streak, the system runs a health check: an LLM diagnoses why (conditions too strict? wrong timeframes?) and can propose condition adjustments. Applied changes create a new strategy version with a changelog - the strategy literally evolves.
Strategies
Build it or buy it
Create a custom strategy or pick one from the marketplace. You control the risk level.
Transparency
No black boxes. Ever.
You see everything your agents do - every thought, every decision, every trade.
- Every agent conversation saved and viewable
- Traceable sources - click through to verify
- Live streaming of every cycle
- On-chain proof of every trade on HyperLiquid
- Clear cost breakdown per cycle
Under the hood
Built for production
CoreX isn't a wrapper around ChatGPT. It's a distributed system for real-time financial workloads.
Ready to try it?
Define your strategy, pick a risk level, and let AI agents trade HyperLiquid for you - around the clock.