Mathison was built to serve as an artifically intelligent complex event processing platform.

Artifical Intelligence is a platform, not a feature

Most systems can tell you what happened in the past. Mathison can tell you what is going to happen next. The world is complex and ever changing. Mathison helps your business understand how to navigate when all of the old formulas are out the window.
Services Use Cases

Human In The Loop AI

H.I.T.L. is a hybrid form of human intelligence and machine intelligence. It rapidly increases the velocity of model creation and implementation. The reality is, all productive business Artificial Intelligence is about looping the humans in. Humans can label data very effectively. Providing this kind of feedback in real time with our novel congnitive architecture enables new approaches to A.I. as well as augments the usage of tried and true approaches to machine learning. This super charges our implementations.
By using your people and augmenting them with our Data Service Reps, we achieve optimal operationalization of novel artificial intelligence models. At the same time we are re-optimizing, re-training and operationalizing new models.
Supply Chain Graph

Supply Chain Management Graph

Supply Chain security starts here. Predict disruptions and manage risk when the old formulas don't exist anymore.

Customer Experience Engineering

Customer Experience Engineering

Customers expect a new experience. Address privacy concerns and rebuild your customer demand chain.

Service Chain

The Emergent Service Chain

Take advantage of gig-economy and just in time services, resiliently, to manage spikes and drops in demand.

Manufacturing IoT

Manufacturing IoT

Reshoring initiaves and supply chain diversification require real time data flows to enable efficient automation.

Graph of Society

Society Graph

All politics, and data, are local. Make market place risk assessments that affect your overall enterprise in real time.

The MetaChain

The MetaChain

Tame the Franken-SaaS and make 360 degree sense of your data without replacing software.

Our Latest Thinking

Operationalizing Artificial Intelligence Putting AI into production is not called deployment, it's called operationalizing. We dont' have build/test/deploy/manage order of things. There is the now the training phase and the inference phase. Training Phase: select multiple algorithms select appropriate data clean data label data apply data to algorithm hyper parameters validate test over/under…

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