ecosystem.Ai is a low code environment which uses a combination of AI and behavioral science to select the best campaigns, products, messages, and offers for your customers - in real time. Set up effective recommendations in minutes using our default Dynamic Recommenders and use Generative AI to enhance your interactions. Or configure your own AI algorithms, with control over all of the settings that impact how the recommendations are made.

The complexity and variability of humans means that change is inevitable; the ecosystem.Ai model serving platform assists you in delivering on those tight AI project deadlines with a robust platform that can be used to integrate your models into websites, apps, inbound call centers, outbound dialers, etc and access to a full set of API's.

The ecosystem.Ai platform:
Creates revolutionary engagements by understanding the human in your system, using social science and behavioral algorithms.
Seizes opportunities as they happen using truly real-time capabilities; model serving, features, dynamic experimentation and business integrators.
Radically reduces the cost and time to market, for every deployment, by providing an effortless no-code/low-code deployment environment.
What you get with this install:
Prediction Server - allows you to manage many data engineering, data science, machine learning and other functions available through Python, the Workbench, or API's.
Workbench - is a no-code front-end to perform end-to-end prediction project life cycle activities including the deployment of real-time behavioral predictions into production.
Notebooks - comes with a number of default Python libraries and Jupyter Notebooks to guide you through any customizations you might need for predictions, experiments, simulations, etc.
Client Pulse Responder - provides full runtime inference and scoring capabilities for dynamic or static real-time activities including logging, and is permanently in production.
Grafana - make your real-time data come to life. It's a dashboard to track the performance of the use-cases implemented in the Client Pulse Responder Runtime.