Put AI to work inside a complete workflow.
Calvoryn helps turn AI models and prototypes into defined operating workflows: receiving information, using the model, taking permitted actions and handing exceptions to a person.
Discuss an AI implementation
Where the gap appears
The model can answer a question, but the result still needs to reach a record, a queue or an operator. Inputs vary. A tool call fails. A response needs checking before anyone acts on it.
AI implementation is the work of making those relationships explicit and building the surrounding path. The right solution may combine AI with ordinary software and human decisions.
What the work can include
- Connecting existing models or AI tools to intake and business systems.
- Moving information from documents into a defined review or action workflow.
- Handling missing information, failed requests and uncertain outputs.
- Creating representative evaluation examples for the intended task.
- Defining who can approve, correct, retry or stop an action.
The scope depends on the starting system, its data and the consequences of an incorrect result.
Agentic operations with explicit limits
An agentic workflow lets software carry out defined steps using tools. Calvoryn approaches this through the job to be done, the tools permitted and the decisions that stay with a person.
Examples of possible scope include research and drafting with human review, or a queue-based workflow that acts only within agreed rules. Permissions, review points and stop conditions belong in the design from the beginning.
Input enters validation. Valid input proceeds to the model; invalid input goes to review. The model proposes an action. A policy check permits the action or sends it to review. An action failure also goes to review. Review ends with correction or a stop; it does not automatically grant execution permission.
What gets tested
Agree examples of valid inputs, missing or invalid information, tool failures and outputs that should not lead to an action. Check what is recorded, who is alerted and how a person can intervene.
Acceptance should cover the workflow as well as the model response. A useful answer that never reaches the right place is an incomplete result.
Boundaries are part of the scope
Model outputs can be wrong. Any allowed action needs a defined permission boundary and an appropriate review path. Model choice, evaluation depth, data access and operational support are agreed for the specific engagement.
If the main problem is exchanging data between tools, start with systems integration. If an implementation is already stalled, see production rescue.
Show the workflow you want to make useful.
Bring the current model or prototype, an example input and output, the systems involved and the decisions a person must retain.