A platform to democratize
AI-based interventions and experimentation
Track & label
Start by connecting mobile or web apps to the benshi.ai platform as your sources of user data. benshi.ai provides a predefined set of available tracking events and auto-generates meaningful user & content traits, individual behavioral time series metrics, and KPIs specific to your use case resulting in labeled, machine learning-ready data
Develop a benshi.ai tracking plan from our preset schemas for ML
Connect seamlessly through our SDKs
Track data in real time, driven by your business questions
Segment users & content
Segment your users and application contents into affinity cohorts based on users' past and predicted behavior, or build custom segments based on exploratory questions. Cohorts act as a single unit for training of machine learning models, analytic exploration and experimentation.
Our analytics space offers visual exploration of historical time series behavioral and health data, along with visualization of app content performance, user traits, and KPIs
Visualize historical user activity and engagement data in near-real-time
Integrate behavioral analytics into your personalization workflows
Compare time series data across user & content cohorts
Predict, recommend & validate
Time-varying behavioral predictions, personalized content recommendations, and app content demand forecasting are core outputs of the platform. In our Predictions space, partners can explore the predictions from of our machine learning models for individual users and app content to get a glimpse into the future.
Machine learning model governance and transparency are fundamental to benshi.ai's predictive power. In the Model Management space, partners are able to explore models — the origin of all of the platform's predictive outputs — through accuracy metrics and performance monitoring.
Experiment & personalize
The Intervention & Experimentation space is where partners can create and evaluate just-in-time adaptive interventions (e.g. incentives or recommendations that can be delivered when and where they are needed through push notifications, in-app content display, sms, whatsapp). Users are targeted based on predictions of behavior, demand or trajectories of health and disease. Our partners can take action to nudge groups of users towards goals, health outcomes or policy intervention objectives that they define
Microrandomized Trials (MRTs)
Causal impact analysis