Agentic AI for Prediction Markets.
Poly-Alpha is an autonomous multi-agent framework designed to reason, plan, and deploy capital entirely independently, replacing legacy quantitative infrastructure with goal-oriented AI.
The Execution Layer for Quantitative AI.
Poly-Alpha is a B2B SaaS platform that gives institutional funds and proprietary trading desks a fully managed, autonomous trading stack for prediction markets — deployed entirely through our API. Think of it as your quant team in software form.
Instead of spending 12–18 months building internal infrastructure to parse news, calculate edge, and execute trades, your team simply calls our API with a high-level objective. Poly-Alpha's multi-agent swarm handles everything below: real-time data ingestion, LLM-driven probability estimation, dynamic position sizing via Kelly Criterion, and sub-10ms execution on Layer-2 orderbooks.
We currently operate on Polymarket, Kalshi, and Manifold Markets — the three largest prediction market venues globally — with real-money volume and measurable Sharpe ratios. Our clients retain full capital control with optional human-in-the-loop approval gates before any trade is submitted.
Reason
Agents continuously read news, analyst reports, and market microstructure to form their own probability estimates — updated in real-time.
Optimize
A dedicated risk agent applies Kelly Criterion sizing and Shin debiasing to determine optimal position sizes that protect against systemic ruin.
Execute
An execution agent submits limit orders directly to L2 orderbooks via our native connector — in under 10 milliseconds, ahead of REST-API competitors.
Multi-Agent Swarm Capabilities
Engineered for high-throughput autonomous reasoning and tool execution.
Agentic Reasoning & Reflection
Poly-Alpha agents don't just parse data; they understand market intent. Utilizing fine-tuned LLM models, agents conduct continuous chain-of-thought analysis on real-time news streams, reflecting on their own probabilities before finalizing a strategy. They dynamically update their Bayesian priors without human intervention.
Autonomous Tool Use
Our agents utilize direct API tool-calling to interact with continuous double auction orderbooks at sub-10ms latency.
Self-Correcting Risk
Dedicated risk agents continuously monitor portfolio health, employing self-correction heuristics to halt trades and prevent ruin.
Goal-Oriented Optimization
Initialize your swarm with high-level directives (e.g., "Maximize Sharpe ratio with 2% Max Drawdown"). The agents will dynamically calculate live metric exposures, ingest tick-level historical data from over 5,000 markets, and shift execution parameters to satisfy the ultimate goal state entirely autonomously.
The Agentic Architecture
Poly-Alpha offers a resilient network of specialized AI agents, securely managing high-frequency telemetry.
import polyalpha as pa
from loguru import logger
# Initialize autonomous swarm
swarm = pa.Swarm(api_key="sk_live_...", sandboxing=True)
# Define high-level objective
directive = "Capture premium on FED_RATES without exceeding 1.5% DD."
logger.info("Deploying Poly-Alpha Agents...")
plan = swarm.reason_and_plan(directive=directive)
swarm.execute_plan(plan, await_human_approval=False)Built by Researchers
Founded by a specialized team of machine learning and quantitative systems engineers.
Transparent SaaS Pricing
Scale your autonomous capital deployment with predictable infrastructure costs.
Developer
For independent researchers.
- 1 Autonomous Swarm
- 1M API Requests / month
- Standard REST Execution
- End-of-Day Data Sync
Professional
For prop desks and small funds.
- 5 Autonomous Swarms
- Real-time Layer-2 Execution
- Unlimited API Requests
- Live Event Webhooks
- Priority Slack Support
Enterprise
For institutional capital.
- Unlimited Swarms
- Petabyte Historical Data Lake
- Custom Debiasing Parameters
- On-Premise Deployment
- SOC-2 Audit Reports
Deploy Poly-Alpha Agents
Begin provisioning your own autonomous quantitative swarm today.