Narrative based Ai (Ai-narration) uses natural language processing (NLP) and machine learning (ML) to augment storyline understanding with real-world event context using computed high-value internally generated event data.
Prechelon uses internal and external data wranglers to acquire unstructured data. We use an agile architecture to scale alongside the anticipated growth in unstructured signal data.
2.5 exabytes of data are produced daily and the pace is accelerating. We use proprietary natural language processing (NLP) to extract, disambiguate, classify, and connect entities (i.e. people, places, things, other).
Prechelon uses a proprietary event representation to move through abstraction in ways that improve event relations, dependency inferencing, and learning capability.
A virtuous real-world event data cycle powers proprietary language and leaning capabilities that extend standard machine learning algorithms to better isolate changing contexts so the most relevant entities and intentions related to real-world events are identified and inferred.
Machines can understand and infer connections in more dimensions at a greater horizon than humans. Our pipeline utilizes internally generated high-value data to generate future event likelihoods.
Myths, archetypes and stories are how we organize the world. Everyone wants to know where the narrative is heading and how it ends. We transform computed context and prediction into future human-readable formats.