Since we understand the recipe – ingredients, diets, allergies, nutrition, taste, techniques & more. We can connect your users with the best recipes available for their unique food preferences. Search over 2 million recipes - Search our large recipe database. We add new sites and recipes continuously. - You will also get access to over 5000 top web recipe sources - Our search algorithm returns the most relevant recipes from the most popular and best recipes sources on the web. We order recipes by their cookability and quality so your customer can always count on getting the best recipes! Semantically organized database - The recipes in our database are normalized and can be filtered in the search by calorie and diet preferences. Full nutrition for each recipe - We have the most accurate automated nutrition analysis on the web powered by our proprietary Natural Language Processing (NLP) engine. Customers get detailed nutrition breakdown of each recipe with 25+ nutrients and appropriateness for all major diets. - Filter by calories, diet or allergy restrictions - Edamam has developed over 35 diet and health filters for your customers to use. Now you can develop applications for virtually any popular diet or major health condition. Recipe caching - Edamam may allow caching for those customer on custom plans.
Cenacle Research offers Condition-based Predictive Maintenance solutions that reduce maintenance costs and improve asset life-time by optimizing the maintenance schedules. This requires calculating the asset's remaining-useful-life (RUL) based on the current and historic usage patterns and building a mathematical model that is capable of extrapolating failures from the past to the future. The Predictive Maintenance API offers: - failure rate estimation based on real-time operating conditions - failure rate estimation based on historic failure patterns The *Real-time Failure Rate API* allows you to calculate the failure rate of various components, such as Accumulators, Actuators, Belts, Clutches, Brakes etc. in real-time based on the prevailing operating conditions of the assets. This helps you in estimating the RUL for various assets such as: - vehicles in motion, based on the sensors attached to the vehicles to various key parts - stationary machinery in manufacturing plants - individual components inside machines etc. When you do not have the previous failure records or maintenance records available, or if your machinery is brand new with provisions to capture the required data using sensors, this API is the best option for high accuracy predictions. The *Historic Failure Rate API* allows you estimate the asset failure risks for a population of assets based on the maintenance records and previous failure patterns. This helps when you do not have provision to attach sensors and have adequate history of maintenance records for a population of machinery. [Get in touch](http://Cenacle.website/#contact) with us if you are interested in utilizing our Predictive Maintenance API in your applications.