We build machine-learning models, predictive systems, and AI agents, with the data, orchestration, and software needed to put them to work.
Develop custom predictive models for demand, inventory, resource planning, and other operating decisions. Evaluate models against agreed baselines, including specialized models where the use case calls for them.
Custom machine-learning models, forecasts, and model evaluation.Build agents that use models, business information, and connected tools to carry out defined work. Orchestrate multi-step workflows and include human review where the task requires it.
Custom agents, tool integrations, and coordinated workflows.Put data pipelines and access to models in place, including specialized models selected for the task. Connect them to the agents, orchestration, and applications that use them.
Data pipelines, model access, document processing, and system integrations.Build applications that handle recurring tasks, route exceptions, and connect work across business systems. Give teams the tools and operating information they need to act.
Workflow applications, connected business tools, and dashboards.Our client operating system brings the tools we build into one managed environment. It connects models, agents, and applications, with dashboards for your team to see the work and manage operations.
Manage the tools, models, and agents built for your business.
Coordinate how agents and connected business systems work together.
Bring system outputs and operating information into a view your team can use.
We evaluate the system for its intended use, deploy with your team, and can continue to operate and improve it. Ongoing responsibilities and support are defined for the engagement.
Deployment in a cloud environment selected for the engagement.
Deployment within the customer’s cloud environment.
Deployment on customer-managed infrastructure where the configuration calls for it.
Access, licensing, support, and handover depend on the agreed scope and configuration.
Our technical partnership with Matchmatch brings research expertise into model development, explanation, and evaluation.
Matchmatch is a separate firm. Dr. Nicholay Topin and Dr. Gregory Plumb contribute through that partnership.
Visit MatchmatchResearch & Engineering · Matchmatch
PhD in Machine Learning, Carnegie Mellon University. Research in interpretable machine learning and explainable reinforcement learning.
ProfileMachine Learning Researcher · Matchmatch
PhD in Machine Learning, Carnegie Mellon University. Research in model explanations, diagnostics, blind spots, and human evaluation.
ProfileGregory Plumb, Denali Molitor, Ameet S. Talwalkar
Nicholay Topin and coauthors
Valerie Chen, Nari Johnson, Nicholay Topin, Gregory Plumb, Ameet Talwalkar
We consider selective partnerships with industry and software teams to assess, build, and commercialize repeatable capabilities.
Development scope, customer configuration, and commercial rights are agreed for each partnership.
Discuss a partnership