AI Makler — Intelligent Financial Agent With Memory and Multi-Workflow Orchestration
Markets move fast, and making sense of them requires not just data but context — what happened yesterday, what decisions you made, how conditions have changed. The AI Makler worker brings that context to life: an intelligent financial agent that remembers past sessions, makes decisions, manages positions, and can even trigger other workflows.
Think of it as a tireless trading assistant that keeps notes on every session and gets smarter the more you use it.
What Is AI Makler?
AI Makler (Polish for "broker") is an AI-powered financial agent that lives in the AI category of the left sidebar. Unlike stateless AI workers that process one request at a time, AI Makler remembers its past analyses, decisions, and market observations across multiple runs within the same workflow.
This makes it ideal for:
- Continuous market monitoring — the agent knows what it saw yesterday
- Trading signal generation — it tracks its own accuracy over time
- Portfolio management — it remembers open positions and reviews them
- Multi-step workflows — it can trigger other workflows based on analysis
Key Features
🧠 Persistent Memory
- One MongoDB document per workflow — all runs share the same memory
- Remembers: market state, analysis, orders, triggered workflows
- Configurable history (1–100 iterations, default 20)
- No raw prompts saved — just the meaningful context and decisions
📊 Two Processing Modes
| Mode | Purpose |
|---|---|
| Analysis | Examine market data and news, identify trends, assess risk |
| Decision | Make concrete trading calls: buy, sell, close, or hold |
📈 Structured Orders
When the agent decides to trade, it returns proper order objects:
{
"action": "buy",
"symbol": "BTCUSD",
"entry_price": 86500.00,
"target_price": 92000.00,
"stop_loss": 84000.00,
"position_size": 0.5,
"order_type": "market",
"reason": "Bullish flag breakout on above-average volume",
"certainty_pct": 82
}
The agent only generates orders when certainty > 60%. If it's not confident, it just returns analysis — no false signals.
🔗 Workflow Orchestration
AI Makler can trigger other workflows to perform complex tasks. List the allowed workflow IDs in the configuration, and the agent will decide when to run them, passing data along. Triggered runs are fire-and-forget via the same Redis queue as manual runs.
💼 Position Management
Pass your current open positions as a JSON array, and the agent will review each one — deciding whether to close, hold, or modify based on current market conditions.
How to Use It
Adding the Worker
- Drag AI Makler from the AI category onto your canvas
- Connect it after your data sources (or trigger it on a schedule)
- Configure the parameters
Configuration
| Parameter | Type | Description |
|---|---|---|
mode | select | analysis (default) or decision |
data | markdown | Market data — prices, indicators, volumes |
news | markdown | News and events |
allowedWorkflows | text | Workflow IDs the agent may trigger (one per line) |
investorType | select | aggressive, moderate (default), conservative |
instrumentTypes | select | all, crypto, forex, stocks, commodities |
orderTypes | select | market, limit, stop-loss, take-profit |
currentPositions | hidden | JSON array of open positions |
maxHistoryIterations | number | 1–100, default 20 |
Output Fields
| Field | Type | What it contains |
|---|---|---|
results | string | Full analysis or decision reasoning |
marketState | string | Brief market summary |
orders | array | Trading orders (empty if no decisions) |
ordersCount | number | Number of orders |
triggeredWorkflows | array | Workflows that were triggered |
triggeredCount | number | Number of workflows triggered |
memorySize | number | Current history depth |
latestAction | string | Last order's action (buy/sell/close/hold) |
latestSymbol | string | Last order's symbol |
latestCertainty | number | Last order's confidence |
Use Cases
1. Market Monitor With Memory
[Schedule Trigger] → [Fetch Market Data] → [AI Makler: analysis] → [Condition: alert?] → [Telegram Notify]
AI Makler runs every hour, sees how conditions evolved, and sends alerts when patterns change.
2. Signal Generator With Position Tracking
[Schedule] → [Fetch Data + News] → [AI Makler: decision] → [Save Orders to User List]
Agent analyses market data and news, returns buy/sell signals with targets and stop-losses.
3. Portfolio Manager
[Trigger] → [Fetch Positions + Market Data] → [AI Makler: decision] → [Run Workflow "Execute Orders"]
Agent receives current open positions, reviews each one, and decides what to do. The execution workflow handles the actual order placement.
4. Multi-Strategy Coordinator
[Trigger] → [AI Makler: analysis]
→ [Trigger: Run Backtest Workflow]
→ [Trigger: Run Risk Analysis Workflow]
Agent decides which analysis workflows to run based on market conditions, passing relevant data to each.
Memory in Action
When AI Makler runs for the first time, it has clean memory. After each session, it saves:
- What the market looked like
- What analysis it produced
- What orders it generated
- What workflows it triggered
On the next run, it gets a summary of previous sessions:
PREVIOUS SESSIONS (most recent first):
[1] 2026-06-21T08:00:00 | BTCUSD: Bullish, ETHUSD: Neutral | Orders: 2
[2] 2026-06-20T20:00:00 | BTCUSD: Ranging, high volume | Orders: 1 | Triggered: 1
[3] 2026-06-20T12:00:00 | BTCUSD: Bearish rejection at 88k
This context lets the agent spot trends in its own decision-making and adapt.
Legal Disclaimer
This is not financial advice. Trading involves substantial risk of financial loss. The AI Makler worker is a tool for analysis and automation — all trading decisions should be reviewed by a qualified professional. Past performance in memory does not guarantee future results.