What adapterOS records—and what that means.
adapterOS is an evidence-bound intelligence workspace and engine. It keeps the source scope, supporting evidence, execution state, policy, and review path inspectable without pretending those records make every conclusion correct.
Proof is specific.
adapterOS becomes more credible when each control says exactly what it records, checks, measures, or leaves to a reviewer. These concepts reinforce one another, but they are not interchangeable.
| Concept | What the system can retain or check | What it does not establish |
|---|---|---|
| Source scoping | Which approved collection or source set governed the run. | That every fact the model knows came from that source set. |
| Evidence provenance | Which admitted passages or locators support a claim. | That the source itself is correct, current, or complete. |
| Source integrity | Content identity and change signals when the source path supplies them. | That the author or upstream system was trustworthy. |
| Answer-support checks | Whether required evidence is present, missing, partial, or degraded. | That the conclusion is semantically correct. |
| Execution record | Inputs, configuration, output, evidence, policy, and run state at the supported disclosure level. | That the recorded output should be approved. |
| Reproducibility | Whether the execution record contains enough state to revisit or compare a run. | That rerunning later will produce the same output under changed conditions. |
| Evaluation | Results against a declared question set, source scope, refusal cases, and acceptance criteria. | Universal accuracy outside the evaluated conditions. |
| Policy enforcement | Which configured rules applied and whether the run was allowed, denied, or routed for review. | Certification or legal compliance by itself. |
| Reviewer approval | The human decision, state, and rationale when the workflow captures them. | A substitute for accountable human judgment. |
One product, two surfaces.
The workspace is where people select sources, ask, inspect evidence, and review. The engine carries the same rules into another application or operational workflow.
Workspace
- SourcesSelect approved records.
- AskRun source-scoped work.
- EvidenceOpen support and limits.
- ReviewRecord the human decision.
Engine
- Source scopeDefine what the run may use.
- PolicyApply configured rules.
- Governed runAnalyze within the boundary.
- Proof recordRetain evidence and state.
The unit of work is a governed run.
Search, question answering, drafting, comparison, and analysis follow the same operational shape. That shared shape is what lets a result be inspected, reviewed, and returned to another workflow.
- 01Choose scope
Select the records and collection boundary for the job.
- 02Apply policy
Load the rules, permissions, evidence requirements, and review path.
- 03Run the operation
Ask, compare, draft, or analyze within the configured environment.
- 04Inspect evidence
Open citations, support strength, gaps, and execution state.
- 05Review or export
Approve, reject, revise, or return structured work to the operating system.
Built around the systems you already operate.
Workspace and engine are two delivery surfaces for the same governed run. MLNavigator scopes each integration around the customer's access model, source authority, and review path.
Workspace
Employees select sources, ask, inspect evidence, and record review in adapterOS.
Engine
The same source, evidence, policy, and review flow runs behind existing software.
Approved sources
Local files and folders · approved document exports · internal applications · REST interfaces
- ScopeSelect source and access boundaries.
- AnalyzeRun the configured task and policy.
- EvidenceAttach support, limits, and run state.
- ReviewRoute the result for human decision.
Return useful work
Answer · record · decision · review note · structured output
Current concrete interfaces are local files and folders plus REST. Other systems are evaluated as customer-specific integration work during the pilot; no packaged or certified connector is implied.
Start with a question that is expensive to verify.
Bring the approved documents. Establish the baseline. Define what an acceptable answer and review record look like. Then run a bounded pilot.