Infrastructure, not signals
Infrastructure for AI-native trading systems.
Crateria combines live market data, AI agent reasoning, and deterministic trading logic into one platform — built for teams who write the strategy, not buy someone else's.
What is Crateria?
Crateria is infrastructure for building, testing, and running AI-native trading systems — not a signal service, and not a guaranteed-returns product.
A traditional trading bot runs a fixed set of rules against market data. Crateria is built for a different kind of system: one where an AI agent reasons over context — market conditions, strategy intent, prior outcomes — and a deterministic execution layer carries out the resulting decision safely, consistently, and auditable end to end.
You bring the strategy. Crateria brings the plumbing: market data ingestion, deterministic signal logic, and agent orchestration — so building an AI-native trading system doesn't mean building all of that from scratch first.
Crateria does not sell signals, does not publish trading recommendations, and makes no claims about win rate or returns. It's infrastructure a technical team uses to build and run their own system.
Trusted Architecture
A strategy moves through six stages, from raw market data to a notified, executed decision — each stage independently testable and replayable.
- 01
Market Data
Live and historical price/candle data is ingested and normalized before anything downstream sees it.
- 02
Signal Generation
Deterministic logic evaluates market conditions against your strategy's rules and produces candidate signals.
- 03
AI Agent
An LLM-driven agent reasons over the signal, market context, and strategy intent to decide what — if anything — happens next.
- 04
Validation
The agent's decision is checked against risk and consistency rules before anything is allowed to proceed.
- 05
Automation
Validated decisions are automated through to your broker — order placement, position management, execution.
- 06
Notifications
Every decision and execution is reported back — nothing happens silently.
Example Workflow
A strategy goes from written intent to a monitored, automated decision — deterministic logic and AI reasoning working together, not competing.
1. Define the strategy
You write the strategy's rules and intent — what conditions matter, what the agent should weigh, what the risk boundaries are.
2. Deterministic logic generates signals
As live market data arrives, deterministic rules evaluate it against your strategy and produce candidate signals — fast, consistent, no LLM call needed for this part.
3. The AI agent reasons over the signal
The agent takes the signal plus broader context — market conditions, strategy intent, prior outcomes — and decides what action, if any, follows. This is where judgment enters the pipeline, not raw rule-matching.
4. Validation and execution
The agent's decision is checked against risk rules before it's automated through to your broker — deterministic logic has the final say on whether a decision is allowed to execute.
5. Notification
Every decision and execution is reported back to you, whether or not it results in a trade.
Get in touch
Pricing is use-case-dependent, not a fixed table — book a demo or contact sales to talk through your specific needs.
There's no self-serve signup — every engagement starts with a conversation. Reach out and we'll walk you through what Crateria can do for your use case.