Elisci Solutions
Agentic AI Trading
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Autonomous agents • Risk-first execution • Human oversight

Agentic AI that plans, trades, and learns — with guardrails.

Deploy goal-driven trading agents that research signals, generate hypotheses, simulate strategies, and execute with strict risk controls. Designed for paper trading, research, and gradual production rollouts.

View architecture Risk controls
⚡ Fast backtests 🔒 Key isolation 🧾 Audit trails

Product

Agentic workflow from research → simulation → execution → monitoring.

v0.1 template

Strategy agents

Goal-driven agents propose trades, explain rationale, and adapt to market regimes with configurable rules.

Backtest & simulation

Fast experimentation loop: feature generation, walk-forward evaluation, and paper-trading rehearsal.

Execution engine

Order sizing, slippage-aware routing, and guardrails. Supports “human-in-the-loop” approvals.

Risk & limits

Daily loss stops, max drawdown controls, position caps, and portfolio constraints enforced at runtime.

Audit & explainability

Every decision logged: signals, prompts, confidence, and actions — ready for review and debugging.

Monitoring

Live dashboards for exposure, performance, anomalies, and drift detection with alerts & rollbacks.

How it works

Reference architecture for agentic trading systems.

Agent lifecycle
1
Observe Fetch market data, news, and indicators. Normalize & cache features.
2
Plan Generate candidate strategies and define constraints (risk, exposure, time).
3
Simulate Backtest, walk-forward, and stress test against slippage and regime shifts.
4
Act Place orders with size limits and guardrails. Optional approvals.
5
Learn Update beliefs, retrain models, and record outcomes for continuous improvement.
Example stack

Swap these with your actual stack. This is just a template.

  • Data: market feeds, fundamentals, optional sentiment.
  • Models: time-series, regime, pair signals, RL (optional).
  • Orchestration: agent planner + tool calls + memory/logging.
  • Execution: broker API, slippage model, position manager.
  • Governance: approvals, audit trails, alerting, rollbacks.

Risk controls

Risk-first design: limits enforced in code, not in hope.

Hard stops

Daily loss stop, max drawdown, max leverage, max position size. Trades blocked if violated.

Key isolation

Separate read vs trade keys. Rotate keys and restrict IPs. Keep secrets out of the repo.

Human approvals

Optional review gate for strategy changes, new symbols, or large orders before execution.

Pricing

Example pricing section — replace with your real offering.

Research & Paper
For prototyping agent strategies
$0 / month
PAPER
  • Agent strategy templates & configs
  • Backtests + walk-forward evaluation
  • Paper trading with logs & audits
  • Risk limits + alerts
Production
For live execution with governance
Custom pricing
LIVE
  • Broker integrations + routing
  • Human-in-the-loop approvals
  • Monitoring dashboards + incident playbooks
  • Compliance-ready audit trails

FAQ

Short answers your visitors expect.

Is this fully autonomous?

No. You can run autonomous loops, but the system is designed for guardrails and optional approvals.

Can I use it for paper trading only?

Yes — paper-first is recommended. Add live execution only after you validate performance and risk behavior.

What markets are supported?

Template supports any market with a data feed + broker API (stocks/crypto/fx). You decide integrations.