Governing AI is a process question before it is a policy question.
Govern AI where it actually operates — inside business processes, with defined access, authority and evidence.
Why this is hard.
Most AI governance effort produces a policy document. Policies are necessary, but they do not answer the questions that determine whether an AI deployment is safe: in this specific process, what information can the model see, what actions can it take, where does a human have to approve, and what evidence is retained afterwards?
Those questions can only be answered where the AI is actually used — inside a workflow, against a defined set of records, with a defined scope of action. Governance applied at the level of the organization rather than the process tends to be unenforceable.
The signals this solution acts on.
Use-case inventory
Which processes use AI, for what, and who owns each one.
Data access
What each capability can read, bounded by the same permissions that bound the people using it.
Decision authority
What the system may do on its own, and what it may only recommend.
Human oversight
Where approval is required, by whom, and what they saw when they approved it.
Auditability
Inputs, sources, outputs and approvals retained against the record they concern.
Testing and monitoring
Known-answer testing and continuous monitoring, so accuracy is measured rather than assumed.
Risk classification
Use cases classified by consequence, with controls proportionate to it.
How the pieces combine.
Inventory the use cases
Including the ones already happening in tools nobody approved.
Classify by consequence
A drafted email and a posted journal entry are not the same risk and should not carry the same controls.
Bound access and authority
Permissions, scope of action and approval points defined per process, not per organization.
Design the human checkpoint
Decide where judgement is required and make it a step, not a hope.
Retain the evidence
What the model saw, what it produced, who approved it and when.
Test and monitor
Measure accuracy against known answers and watch it over time.
Products involved.
You do not need all of them. Each is useful on its own; this is the combination that addresses the problem completely.
Systems it reads from
Where it fits
What this looks like when it works.
Services that help you get there
Frequently asked questions.
Where do we start?
With an inventory of the AI use cases — including the ones already happening in tools nobody approved — each classified by its consequence.
What evidence is retained?
What the model saw, what it produced, who approved it and when.
Do we need every product listed on this page?
No. Each product is useful on its own. A solution describes how several of them work together on one outcome; you can start with one and add the others as they create value.
Does Farsight DS replace our existing systems?
No. It works on top of the systems you already run. Nothing is replaced.
Work through strengthen ai governance & control against your own systems.
Thirty minutes. We map what you already have and where this would start paying.