Fatbrain

Outcomes Engine

FatBrain’s Outcomes engine enables businesses to move beyond traditional correlational (“what-is”) statistics, with causal (“what-if”) analytics to drive real-time, continuous decision making – all in place.

Our engine leverages modern advances in machine learning and cloud economics to bind disconnected data lakes of structured and unstructured data into learned vector embeddings (LVE) representation, enabling real-time decision making that is driven by causal inferencing and automated lifelong learning.

 
fatbrain outcomes engine graphic

How it Works

data select

Select

Data

Uses 100% of the data, be it multi-lingual text, location, numerical, categorical, image, sound, or any combination of such data types.

vectorizeVectorize

Vectorize

Data + Context

Uses Learned Vector Embeddings (LVE) to encode hidden relationships in data and quantify a similarity metric for imputation, recommendation, classification, and regression.

learn

Learn

distance_metric, lens

Uses Deep Learning to automatically learn outcomes from few or no labeled examples as well as from past decisions and their consequences.

next row

next item

recommend

Recommend

API {…}

Delivers recommendations to assist decision making, enabling business analysts to learn, use, and explain decisions in a secure, in-place, auditable way.

comply

Comply

Decision + Audit Trail

Generates a blockchain audit trail of each proposed decision to ensure they are explainable, auditable, and fair.

 

Don’t guess outcomes. Know them.

Turbo-charge the speed and effectiveness of decision making with the FatBrain Outcomes Engine.

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