General presentation of Probayes

Copyright © 2010 Probayes All Rights Reserved 1 1

Behaviour Analytics& Prediction

December 2010

ProbayesMastering Uncertainty


Company

Founded in 2003 – Based in France (Grenoble)

Spin-off of a well-known lab (INRIA/CNRS)

Office: France, Mexico

22Employees80%PhD

Privatelyheldbyfounders&employees

Profitablesinceincep:on$


Missionstatement

Developbestofbreed

computed‐aideddecisionmakingsolu;onbasedupon

predic;vebehavioranaly;cs

PREDICTBEHAVIOR

Behaviorof:

 Objects

 Process

 People(Consumers)


Ourmethodology

ClassifyBehaviorsRight/wronggesture,turnleL/right

LearnBehaviors Buildmodelsorlearnfromdata

RecognizeBehaviors Computeprobabilitytobeinagivenbehavior

THEN,PREDICTNEXTBEHAVIORS


Auniqueapproach

Mixing  DealingwithUncertaintyandIncompleteness  Modelingknowledge(formaloruncertain)  Miningdata

Usinguniqueandpowerfulmathema:caltools(Bayesiannetwork,mul:‐model,Markovchain,..)

KNOWLEDGE&DATA=>RELEVANCE


Ourteam

Strongprojectmanagementexper;se:  WorkwithF500companies(Areva,Toyota,…)

  Knowhowtodealwithconfiden:alityandIntellectualProperty

Mathema:cs

Astrophysics

Robo:cs

…

+

Ateamof15doubleskilledengineers

SoLwareengineers

DOUBLESKILLEDENGINEERS


Ouroffer

Product(ProBT,BofSDK,RecoSDK)

+

ProfessionalServices

(Modeling,DataMining,MachineLearning)

=

Solvingefficientlycomplexproblems(behaviordetec;on,sensorfusion,predic;on,…)


Targetmarkets

Finance  Opera:onalRisk  Fraud&Moneylaunderingdetec:on

ProcessManagement(BPM)  Industrialprocess(produc:on,maintenance)  Automo:ve,Health,Energy,Security

BusinessIntelligence  Helpdesk,Call‐center  Consumerbehavior(web,energy,wholesale)

Defense&Automo;ve  Data&sensorfusion  Classifica:on&BehaviorRecogni:on  Trajectorypredic:on


References

Finance

ProcessManagement(BPM)

BusinessIntelligence

Defense


Ourproducts

ProBT  Probabilis:c&Predic:veanaly:cssoLwaretool  10yearsofR&D

‐Score15millionsbanktransac;onsaday‐

RecoSDK  Processing,Analysis,Classifica:onof:meseriesinreal;me  SupervisedLearning,HiddenMarkovModels

‐GestureRecogni;onusinganysensor‐

BOFSDK  Probabilis:cgridtomergesensorsdata  1patent

‐ReliableMul;sensorsfusion‐


Examplesofapplica;ons

FraudDetec;on Probabilis:cmodelingoffraudbehaviorscoupledwithselflearningcapabili:esso the system adapts and adjusts automa:cally to new fraud pacerns, it canassignaprobabilityoffraudforalltransac:ons.

Reducefraud$$$

Energyconsump;onpredic;on Predictenergyconsump:onofcomplexsystemssuchasdistricthea:ng,waterboilers,engines,andhelpop:mizeenergybyanalyzinguserbehavior.

Saveenergy,improvecomfort

Predic;vemaintenance Modeling complex compoundequipments suchasmechatronics solu:ons, andpredictthefuturetrendofequipmentcondi:on.

An;cipatebreakdown


Examplesofapplica;ons(2)

Gesturerecogni;on Recognizethetypeofgestureapersonismakingassoonaspossible,andofcoursebeforethegestureisfullycompleted.Useanysensors.

Usegesturesascommands

ChurnPredic;on Findoutcustomerswhoarelikelytoleaveamobileoperatorwithinthenextcomingweeks.

ImproveROI&ARPU

Self‐adjus;ngse^ng Basedonbehavioranaly:cs,an:cipatethefutureneedsandthenmakethepropersedngmostlikelytobeused.

Improve&adjustuserexperiencetotheUser

h_p://www.my‐smart‐phone.com/move‐n‐play/videos/


Onlinedemos

Keystrokedynamic Recognizeapersonusingthewaysheusesakeyboard Soyouneeduser/password,andthewaytokeyintheinforma:on Improveiden:fica:ononwebsites,systems&applica:ons.

h_p://www.keystroke‐dynamics.com(user:web,password:web4you)

Sensorfusion:GestureRecogni;on Capabilityofusingdifferentsensors(video,accelerometer,…) Learnandrecognizegestures Behaviordetec:on(panic,faint,…)

h_p://www.youtube.com/watch?v=Z50IrzkUY08

Collisiondetec;onsystem Fusioninforma:onfromdifferentsensors(video,laser) Trackobjects,quicklypredictcollisionriskforthenext10seconds Keepintoaccountbothobjects&drivers/usersbehavior

h_p://www.probayes.com/IMG/mov/BOF.mov


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?

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BigDataExtractpredic:vemodelsfromdata

Classify&Segmentdata

Classify&Organize

UncertaintyMissingdata,hiddenvariablesinvolvedinaprocessbutimpossibletoread

Sensorwithpoorprecision,orsensordegradingover:me

Incompletemodelswithnodata,feworalot

Whenarewerelevant?

InverseproblemManyprac:calproblemsarecalled”inverse"inthesensethatitiseasyto

knowtheresultofanac:on,butverydifficulttoknowtheac:onsleadingto

desiredresult.

PREDICTTOBETTERDECIDE


Contacts

THANKYOU

[email protected]

+33476426413

Probayes345rueLavoisier38330MontbonnotFrance

www.probayes.com

General presentation of Probayes

Technology

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