Realtime Decision-Making Engine
Where Your Business Data Lives

We help companies improve realtime decision-making in place to grow sales and to enhance customer experience and lifetime loyalty by monetizing transactional data across all business interactions without the hassles of hiring armies of cloud and data science PhDs.

Bind Disconnected Data Lakes
Into Causal, Auditable Outcomes

We focus on business AI applications leveraging modern advances in machine learning and cloud economics by solving complex technical problems to (i) bind the disconnected enterprise lakes of structured and unstructured data into numerical vectors connected by common backplane enabling (ii) realtime decision-making driven by causal inferencing and continuous learning.

Easy, Fast, Secure to Deploy
Using a Spreadsheet to Start

A business analyst knowing how to use a spreadsheet can use our service to make auditable decisions connected to data: Which 3 of the 10,000 knobs counted by Hadoop could critically move the needle today, this week, this month? How to distill service interactions from 20 to 2? Which customers to discount, by how much, and when? Where to place new retail stores?

How We're Different

Our solutions feature enterprise-class auditability, performance and security, can be deployed in weeks and deliver business value beyond traditional correlational (“what-is”) statistics; rather, we quantify and enable causal analytics (“what-if”) to drive real-time, continuous, in-place decision-making, featuring:

1. Modern machine learning and business AI technologies (e.g., Causal Inferencing, Vector-space Embeddings) for transactional or time-series data not offered in place by Google, IBM Watson, or the traditional Hadoop jujitsu.

2. Differentiated Auditable Insights yielding principled, repeatable, transparent and scalable results, unlike most other AI offerings featuring opaque or complete black-box models (e.g., deep neural-networks).

3. Strategic Reinforcement Learning engine, which learns from history of past decisions and payoffs to support future decision-making for optimal business outcomes in complex, multi-agent, stochastic business environments.

4. Blockchain audit trail of the Inferred Quantitative Efficacy of the proposed decisions, with results consumable using standard BI tools, deployed via containers (e.g., K8s) where business data lives, e.g., mainframe, midrange, x86, private or public cloud.

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