Solon / Governed AI workflows
Governed AI agents for your operation.
Counterfold designs AI workflows that work with your operational data, approved tools and explicit human responsibilities. A useful agent needs both the context to understand a task and boundaries that determine what it may see and do.
From a chatbot to an operational workflow
A general conversation can help draft an answer. An operational workflow must know which records are in scope, which calculations are approved, what evidence supports a conclusion and who can authorise the next step.
We define those boundaries before expanding autonomy. A first use case might assemble a sourced review brief, investigate a data exception or compare the output of an approved scenario tool.
Four controls to design together
- Context: retrieve only data permitted for the identity, task and purpose.
- Models: agree processing location, provider access and retention.
- Tools: validate inputs and restrict operations outside the model prompt.
- Actions: require the appropriate review, recheck permissions and record outcomes.
Evaluate what the system actually does
Evaluation uses representative tasks and failure cases. Check unsupported statements, missed evidence, incorrect tool arguments, data leakage and attempts to exceed authority. A fluent answer is not an acceptance test.
Keep deterministic calculations separate from generated interpretation. Compare candidate models on the actual workflow, preserve source references and define escalation when the available evidence is insufficient.
Custom deployment and operating ownership
The right model and hosting arrangement follow the sensitivity, latency and operational requirements. European hosting, on-premises or hybrid designs may be considered; no single arrangement is assumed to fit every client.
A pilot needs named owners, recovery procedures, logs with appropriate access and retention, and a way to stop or roll back a workflow. Wider deployment follows acceptance and an agreed support model.
Practical answers
Questions before the first conversation.
Can agents take action without human review?
That is a decision-specific design choice, not a default promise. Consequential actions require the authority and safeguards agreed for the workflow. Initial pilots can operate in observation or recommendation mode.
Can you use multiple models?
Where useful, models can be compared or assigned different roles. More models do not automatically improve reliability. The combination must be evaluated against the same task, data and permission requirements.
What is available to try now?
The public Icarus finance example demonstrates deterministic scenarios, source inspection and a fixed decision brief. It does not call an AI model. A live agent integration is scoped and evaluated as part of a client engagement.