LedgerSight
Finance operations workflows where AI recommendations remain separate from approved business action.
TrustOps: the operating discipline for accountable AI.
TrustOps is how CloudSeals makes AI-assisted work accountable: a policy check before consequential action, a person with authority to approve it and a retained record of the decision.
The seven-stage TrustOps operating loop
Where TrustOps appears
CompliSight
Industrial safety workflows that support supervision, incident review and evidence retention.
CarbonSight
Carbon MRV workflows that connect source data, calculations, review and reporting evidence.
Where TrustOps is heading
Research is extending the loop into governed digital twins, adding a simulation stage and an explicit governance stage: Observe → Simulate → Decide → Govern → Act → Prove. Simulation and physical actuation are R&D, not current capabilities.
Why an operating discipline, not a tool
An AI recommendation needs an operating boundary, a person who reviews it and a record that can be examined afterwards. TrustOps names that missing part and makes it repeatable.
Policy comes before output
The boundary is set before the model runs, not argued about after.
A person stays accountable
Recommendations are reviewed and approved by someone who holds the authority to approve them.
Evidence outlives the decision
What was proposed, on what basis, who approved it and what followed are all retained.
What TrustOps is not
The category is easier to use when its edges are clear.
Not a product
TrustOps is the operating discipline. LedgerSight, CompliSight and CarbonSight are the products that implement it.
Not a certification
It is how work is done, not a badge awarded by anyone.
Not a replacement for governance
It is how governance decisions show up in day-to-day operations.
Questions we get asked
Is TrustOps a product I can buy?
No. TrustOps is the operating discipline. The products that implement it are LedgerSight for finance operations, CompliSight for industrial safety and CarbonSight for carbon MRV.
How is TrustOps different from AI governance?
Governance decides what is allowed. TrustOps is how that decision reaches the workflow: the policy boundary applied at the moment of the decision, the human approval, and the evidence kept afterwards.
What are the stages of the TrustOps loop?
TrustOps organises accountable AI work into repeatable stages: observe, reason, apply policy, assess risk, approve, execute and retain evidence.
Where does Evidence Fabric come in?
Evidence Fabric is the shared evidence layer across CloudSeals applications. TrustOps says a record must exist; Evidence Fabric is where that record lives.
Does TrustOps mean AI makes the decisions?
The opposite. AI recommends; people and policy decide. The discipline exists to keep the approval and the accountability with a person.
Article 4 AI literacy
Use your organisation’s identified AI uses and roles to plan guidance and keep records of literacy measures. This is an operational use case, not a fourth CloudSeals product.