App Orchid

Companies are trying to develop and deploy AI and IoT applications at scale but usually never progress beyond experiments and prototypes because of the complexity in bringing together the myriad of technologies and making them work together to deliver on the use case(s).
This requires years of building an enterprise platform which supports data aggregation and integration, multi-cloud computing, collaborative platform development, enterprise microservices, and a host of other technical components to work together in one common framework.
The common framework must then be implemented by highly skilled (and expensive) technical personnel. It must also be designed to be easily usable by end users and provide significant business value.
The cost and time needed to develop and deliver this common framework, or "model-driven architecture" as more recently advertised, is prohibitive for most organizations and very risky and expensive if not done properly. Most organizations have failed.

Out of the 25+ AI-based enterprise applications we have built on the App Orchid platform, three (3) have been successfully sold and delivered across a variety of industries.
Our flagship product is ContractAI which has proven to reduce time to contract for large Enterprise companies like BP, Fidelity, and LNG (Shell company). For BP, contracting time has been reduced by 87% across 200+ suppliers. We've used NLP and linguistics to allow BP and others to better understand the risk and performance of their existing contracts to improve their ability to negotiate more favorable terms.