Trust and Verification
Why Every AI Application Needs a Knowledge Graph
A knowledge graph gives an AI application stable entities, relationships, and identifiers. This structure helps the application connect evidence and avoid ambiguous names.
Scope and decision boundary
Trust requires evidence, a validation rule, a visible state, and a method for disagreement. Agreement alone is not sufficient.
A trustworthy application states what it measured and what it inferred. It also states when evidence is incomplete or unavailable.
This guide defines the technical controls for this subject. It does not treat a model response as proof.
Start with the decision boundary. Identify the permitted inputs, the required output, and the state change that can follow validation.
This subject also connects to Why Intelligent Contracts Need Machine Trust, Not Only Consensus and Why Explainability Is Important for AI-Native Blockchains. Read those guides together when the decision crosses trust, retrieval, or execution boundaries.
What changes in practice
Entity identifiers separate names from identity.
Treat this point as a design requirement. Record the input and the expected result before implementation.
Typed relationships state how two entities are connected.
Connect this point to a visible contract state. A reviewer must be able to inspect the resulting behavior.
Source references support verification and updates.
Test this point with normal, invalid, unavailable, and disputed inputs. Do not test only the successful path.
Implementation in practice
Define the main entity types before you collect data.
Document the owner, input, output, failure response, and test evidence for this control.
Attach a source and update time to important facts.
Document the owner, input, output, failure response, and test evidence for this control.
Resolve conflicting claims instead of silently replacing them.
Document the owner, input, output, failure response, and test evidence for this control.
Verification procedure
Use this procedure before deployment. Keep the test evidence with the contract version and network configuration.
- 01State the decision in one sentence. Identify the person or system that uses the result.
- 02List each deterministic input, non-deterministic input, external source, and model dependency.
- 03Define the accepted output type, required fields, value limits, and failure states.
- 04Test correct input, malformed input, unavailable evidence, stale evidence, and conflicting evidence.
- 05Test validator agreement, validator disagreement, leader rotation, appeal, and finality where applicable.
- 06Confirm that no state change occurs before the contract obtains an acceptable result.
- 07Record the source, network, transaction state, and validation outcome for operational review.
Design review questions
A reviewer must answer these questions before the contract handles a high-impact decision.
- Can fixed code complete this task without AI or web access?
- What evidence is necessary, and which source is authoritative for that evidence?
- What result must a validator reject?
- What does the application do when the result is partial or unavailable?
- Can a user distinguish an accepted result from a finalized result?
- What data must remain private?
- Which dependency can cause several validators to fail at the same time?
Evidence record
Keep enough evidence to reproduce the application decision. Do not store private input in a public contract record.
- Field 1
- Contract version and network identifier
- Field 2
- Transaction identifier and current transaction state
- Field 3
- Source identifier, retrieval time, and content version when available
- Field 4
- Model task, required output structure, and validation criteria
- Field 5
- Validator outcome, disagreement state, and appeal state
- Field 6
- Final application action and the authority that approved it
Operational monitoring
Deployment is not the end of verification. Monitor the complete decision path and investigate changes in behavior.
- Measure source, model, and network availability as separate signals.
- Measure response time for retrieval, model execution, validation, acceptance, and finality.
- Record rejected proposals, validator disagreement, leader rotation, and failed retries.
- Track source format changes and model configuration changes that can alter output.
- Review appeals and overturned results for weak criteria or missing evidence.
- Repeat the validation suite after a contract, prompt, source, model, or network change.
Release criteria
Release the contract only when the team can explain each input, validation rule, state change, failure response, and authority boundary.
The test suite must include evidence failure and validator disagreement. A successful example does not prove safe behavior.
The interface must show the correct transaction state. It must not describe an accepted result as final before the finality process ends.
The operating team must have a response procedure for provider failure, source change, disputed results, and contract defects.
Limits
- A graph structure does not guarantee correct facts.
- Uncontrolled graph growth can make validation difficult.
Primary GenLayer sources
- Use the official Web Access page as the primary protocol reference for this subject.
- Compare the implementation with Non-determinism before you select the final validation and failure rules.
Check the source pages again before production deployment. Protocol, network, and software requirements can change.
