ORC is an applied AI lab building an autonomous trading program for Robinhood Chain. It reads the market, the chain, and the crowd, then executes with discipline no human trader can hold for 24 hours a day.
Most trading bots follow rules. ORC learns. Each engine is a model trained on its own domain, sharing one world state so a rumour on X becomes a position on-chain within seconds.
A reinforcement-learned execution policy trades coins on Robinhood Chain. It sizes, enters, and exits positions from a live model of liquidity, momentum, and risk.
Describe a token and ORC writes, audits, deploys, and bundles the launch. Contract, liquidity, and initial distribution are handled as one atomic operation.
Language models read X, Telegram, Discord, and Farcaster in real time, separating narrative from noise and scoring attention before it becomes price.
ORC models are trained on dedicated H100 clusters against years of chain and market data, then continuously fine-tuned on live outcomes.
Every trade passes the same pipeline. Perception, reasoning, risk, execution, and review, with a hard risk layer no model can override.
Chain state, order books, mempool, and social streams merged into one tensor of the world.
ORC-1 estimates short-horizon return distributions and the probability the crowd is early or late.
Position limits, drawdown stops, and contract safety checks enforced outside the model.
Routes through Robinhood Chain with private submission to avoid front-running and slippage.
Every fill is scored against the prediction and folded back into training.
General models know a lot about everything. ORC models know one thing deeply: how price, liquidity, and attention move together on-chain.
The core reasoning model. A transformer trained on tokenised order flow, chain events, and social text, aligned to a single objective: risk-adjusted return over a rolling window.
A small, fast execution policy distilled from ORC-1. Runs at the edge next to the sequencer and decides how, not whether, to trade.
Multilingual social encoder that scores posts for intent, credibility, and expected reach.
Code model for contract synthesis and audit. Generates, tests, and deploys ERC-20 launches end to end.
Next-generation foundation model. Multi-chain, longer horizon, native portfolio reasoning.
Replayable backtests on real chain history so every model change is measured before it trades.
Robinhood Chain is an EVM network designed to bring traditional retail traders on-chain. ORC is native to it: same wallets, same assets, same rails, with a model doing the work.
Autonomy without limits is just a faster way to lose money. ORC keeps a deterministic risk layer between every model output and the chain.
Per-asset, per-day, and per-portfolio limits you set. The model cannot raise them.
ORC never holds your seed. Session keys are scoped to approved contracts and expire on schedule.
Each trade ships with the signals, the prediction, and the risk check that let it through.
ORC is onboarding a limited cohort of traders on Robinhood Chain. Join the list and we will reach out when your seat is ready.
No spam. Cohort invites only. Trading involves risk of loss.