Validation is continuous and distributed. Quality emerges from consensus.
Fixies validate, infer, and update the graph
Multiple validators must agree before information is accepted
Errors will be detected and corrected as they occur
New data enters the network from various sources and agents
Fixies analyze data for consistency, accuracy, and completeness
Multiple validators vote on data quality and accuracy
Validated data is integrated into the knowledge graph
Fixies are autonomous agents embedded in the system. They validate, infer, and update the graph directly.
Fixies operate on-premises, in the cloud, or embedded in Letta.
Validation is continuous and distributed. Fixies analyze, cross-check, and update the graph as new data arrives.
Multiple Fixie agents independently validate each piece of data before it's accepted into the knowledge graph.
Human experts can be brought in for complex validations, especially for domain-specific knowledge.
The network continuously monitors for changes, inconsistencies, and new information.
Every piece of data receives a trust score based on its source, validation history, and consensus level.
ƒ(xyz) networks automatically detect and repair inconsistencies, ensuring data integrity over time.
When conflicts are detected, the system applies corrections based on consensus and trust scores.
Validation algorithms are designed to improve over time, learning from past validation decisions and outcomes.