ecosystem.Ai
Behavioral Predictions
ecosystem.Ai is a low-code environment that combines AI and behavioral science to select campaigns, products, messages, and offers for customers in real time. Use default Dynamic Recommenders, Two-Tower retrieval, or your own models, then close the loop with POST /invocations and POST /response.
The runtime is a Java 25 scoring engine (Amazon Corretto 25; plugins, MCP, dashboard, campaign BDD). Workbench is the operator UI. Try a live stack at https://medemo.ecosystem.ai .
What is ecosystem.Ai?
We are a team of social, computational, data, and technical scientists. Dedicated to making products that always account for the human in the system. With our combination of skills and expertise, we have dedicated ourselves to designing technology that enables you to interact, intervene and engage with the humans in your system. Change is inevitable, and human complexity is difficult to keep up with. We have worked towards making it possible to identify and change with the humans in every system.
Why ecosystem.Ai?
Low-Code
The first low-code environment to combine behavioral social science with real-time machine learning.
Make data-driven decisions powered by continuous learning. Letting you innovate, excite, and create richer human experiences through automated predictive interactions.
Behavioral Science and Real-Time Predictive technology
Behavioral Predictions: Predictive interactions tailored to your customers’ personality and behavioral patterns. Real-Time Deployments: Build loyalty with push messages, notifications, and feedback in milliseconds. Low-Code Environment: Rapid implementation of automated processes with little-to-no coding knowledge.
We’ve enhanced the veracity of generative AI
A seamless collaboration of real-time machine learning and generative AI. Use runtime scoring, fact injection, and behavioral algorithms so generative steps stay grounded in offers and customer context.
Artificial Intelligence and Computational Social Science
Understand and predict ever-changing human habits. Build: Use the Workbench and Server to build models and tell the system what you want it to do. Track: Assess real-time human interactions and feedback on interactive Dashboards. Predict: Put models into production and start predicting in real-time with the Runtime (Client Pulse Responder). Automate: Manage processes, boost engagements, and schedule campaigns with Pipelines.
Harness the power of AI to give your company the competitive edge
Recommender Systems: Send compelling offers, nudges, and triggers at decisive moments. Interaction Science: Nurture lasting relationships with highly personalized interactions. Productivity: Boost productivity, streamline processes, and delight customers. Enterprise Solutions: Enhance your enterprise with sophisticated AI solutions. Experimentation: Test the power of your offers and interactions, in real-time. Build Your Own: Use our product to build your own machine learning solutions.
Design principles
- Closed loop first. Score with
/invocations, learn with/response.paramsis a JSON string. - Stable platform, product plugins. Pre-score, post-score, and reward classes customize behavior without forking the runtime.
- Named algorithms only. Dynamic Engagement uses documented
approach/sub_approachIDs — do not invent them. - Ontology for agents. MCP and REST concept catalogs ground tools before they call the runtime.
- Self-host and enterprise auth. Runtime, Workbench, and Server can run in your environment.