Whether it’s booking a flight, cancelling a lost credit card or providing tech support, our backend models are the same. The platform is sector-agnostic, continuously improving as we scale across different application domains.
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Our AI agents are polyglots, with latest advances in cross-lingual deep learning allowing us to scale across languages at almost no extra cost.
The unique coupling of machine learning models with our proprietary data collection means we get high-quality data at a fraction of the cost paid by our competitors. Experts familiar with the use case are asked to guide our intuitive data collection procedure, instead of having to operate the full machine learning pipeline themselves.
No more domain-specific dialogue hand-crafting! We believe content should be curated by service providers and users - not by system developers. Our hybrid engine is based on re-ranking. Slot-filling offers a high precision solution for well-defined tasks, while our relevance engine improves recall for the long-tail of possible user queries.
How do our AI agents make decisions? The PolyAI Policy Engine uses a proprietary dataflow formalism, allowing us to make use of reusable components which can be composed to craft domain-specific behavior. This makes our agents much easier to maintain and allows them to scale to complex use cases in real world application domains.