OpenAI alone
General reasoning. Useful for one-off judgments, but not a full decision system for costly repeated actions.
Consequence API
Turn model reasoning into a decision system your workflow can trust.
Conseq is the decision API for AI workers. Call `POST /api/v2/predict` before a costly action, get back `ALLOW`, `WARN`, or `ESCALATE`, and keep traceability, outcomes, and learning behind the same public contract.
What changes
Reasoning → decisions
The API is not trying to replace the base model. It makes repeated model-driven actions traceable, measurable, and operationally safe.
Current scope
Pricing first
The first live contract focuses on price changes because outcome feedback can be gathered quickly and verified against real data.
Example pricing consequence
Proposed action
Drop bundle price from $100 to $85 in a volatile electronics category
Immediate outcome
Short-term unit lift if demand responds to the markdown
Second order
Competitors match the lower price and reset the category margin floor.
Third order
Customers anchor on the discount and future full-price conversion weakens.
Expected value
-$18.4K over 14 days
Why this matters
A raw model answer is not enough when a bad heuristic can repeat across an entire catalog. Conseq is the branch point between "this sounds smart" and "this is safe to operationalize."
Why not just call a model?
The model gives reasoning. Conseq gives workflow accountability.
Conseq
A machine-readable decision layer with `ALLOW`, `WARN`, or `ESCALATE`, traceability, fallback rules, and later outcome verification.
Why companies care
The value is not one better answer. It is stopping a bad policy from repeating across thousands of actions inside a real workflow.
Public surface
One public call. The rest is support infrastructure.
predict
Call the decision API before an action ships. `PRICING` is the first live capability.
traceability
Every prediction gets an ID, a decision, and a history entry so operators can see what the system knew before execution.
verified outcomes
Record what actually happened later so the product can measure whether the prediction aligned, mixed, or missed.
Design principles
Credibility beats breadth.
Operational, not conversational
A frontier model can give a smart answer. Conseq turns that answer into a stable branch point your workflow can actually trust.
Second-order first
The API is built to surface the consequences that look fine on the first hop but quietly create downstream losses later.
Predict, then verify
Every prediction is meant to be revisited after execution. The feedback loop matters more than a clever one-off answer.
Narrow before generic
Pricing is the first supported action family. The goal is a credible contract with real outcome data, not fake breadth.
Roadmap
What ships next from here.
- Pricing consequence checks for single-SKU price changes
- Prediction history and outcome verification across companies
- Support and marketing action families once the feedback loop is real
- Middleware integration for agents to call before execution
API-first product motion
The public site, the AppSync schema, and the frontend sandbox are now aligned around the API itself. Manual audits are no longer the primary product story here.