OWAL Startup Profile - Ex-Googler Cloud AI Video Platform

By Sean Patton, Published May 29, 2019, 11:50am EDT (Info+)

OWAL, a NYC-based startup developing AI video analytics, is aiming to "improve the quality of life" within high-rise apartments, and commercial property management markets.

** ***** ** **** (********** **** the ****), ** ****** ********** ***** approach, ****** ***********, *** *** **** plan ** **** *** ***** ***** platform.

** **** **** ** **** **:

  • *** ** ****
  • **** ********* ** **** *********
  • **** ** ****'* **-**-******
  • **** **** ** *********
  • *** **** **** ** ****
  • **** *** ************ *** *******
  • *** ** **** ***** ****** ******** Models
  • **** ******** ** ********
  • ****** *****

OWAL ********

******* ** ****, *** **-***** ** video ********* ************** * ****-**** *********, ********* ********* *********** *******, **** experience ** ******* ******** *** *********** hardware/software ********* *********. ******* ******* *****, *** **** ** *** *** creator** '****** ******** *** ***********' *** 'Chromebox *** ********', ** ******** ** management ********** ** *********/*****. ******* ******** development ** **** ******* ********, ******* **-******* *** ****** ** computer ****** ********* *** ****** **** OCR ********** ************.

****'* ************ ** ** ********, **, at***'* **** ****** ***, ** **-******* *********. ***** ******* funding ** ***********, *** **** ***** several *********** **** **** ********, *** they *** ******** ** ***** ********** Seed/Series * *****.

****-**** **** *** ****** ********* / Urban ******** ********** *****

**** ****** ****-**** ********* ** ** "ever-expanding ****" ** *******, ********* ******, vehicles, ****, *****, ********, ********/*******, *** carts. **** **** **** *** ********* large *********** *** ********** ******** ********** companies ********* ** ***** ***** ***** in ***** *** ***** *******. ** issue *********** ****** ******** ******* * **** *** **** recognition ** ****** ********/********* ** ********* and ******.

**** **** **** **** *** ******* where **** *** ****** "*** ****** positive *****", ************ ********** ********** **** recognition ******** *** *********-**** ********** ** patients ** ********-****** *******.

**** *-****** ********* ***** ******* *** offering:

Privacy ******** / ** ****** ** *** **************

**** **** **** *** ********* **** making **** ********* ******* ***** ******* laws, **** *** *** ********** ** selling ** ***********/*******, *** *********** ** small ******** ********** ********* **** ***** not **** "*********" ******* ***** *********/******** and ******** **********.

**** **** ** *** ******* *************** for ****** ************** *** ***:

** ** *** ******* **** ******** data ****** **** ** **** *** marketing *** ********** *******. ***** ***** characteristics ** *** (** ** ***) serve * ******** ********* ****, ** have ****** *** ** ******* **** functionality.

Hybrid ***** / ***** ********* ********

**** **** **** ***** ******-******-**-***** *** appliance-based **-******* *********, ********* ** *** number ** ******* *** *********** ** the ******** **********. ****** **** ** video *********, **** **** ****** *** GPU/CPU ******** ********, ********* ***** ***** from******************, ***** *** ********* ** ****** GPU *** ***** *** *************.

**** ******* * ******* ** ~****** for **** *********** *** **** **** it ******** ******* ** ~******. **** said **** ******* *.***, *.***, *** MJPEG **** *******, ******** ** ***** to *** **********. **** **** **** also **** ************ ********* ******* ****** cameras **** ******* **********.

**** ****** * ************** ** **-******* gateways, ******** ***** ***** *********, *** 3 ** *** ****** ******* * or **** ****** **** *** ***** analytics **********. **** **** *** ********** will ******* ****-**** **** *********, ***********, and **************, ***** ***** ***** ********* use * ****** ********. **** ***** the ********* ******** ****** ********* ********* using ***-******* ******, ***** ******** ****** classification ** ********* ** *****-****** *******.

Custom ********* ****** / ***** ********

**** ****** *** ** ***** ******* strengths ** *********** *** ********** ** quickly ******** ****** ******** ******, *** compiling/labeling ****** ******** **** ***** ******** and ************ ** ****** **** *** - *,*** ****** ****** ********* ** the ********** ** *** ****** *********. This ** ************* ***** ******** ****** that ******* **** ****** ***** ****** would ** ******* **. **** **** said **** ***** ***** ****** **** datasets **** ******* ***** *** *****, and ************ ***** ******.

*** ******** ******* **** ******* ** a ***** **** ******* ** *** equipment ** ** *** ******* ****** detection, *** **** **** ** *** to ** *** **** ******* *** use ** *** **** ********* ** available, ***** *** ****** ******* ****** to *** *****, **** * ******* of ********* *** ******** *** *********.

Web ******, ******* ********* / ** ******** *** ************

**** ** ********* **** **** * web *********** *** ******* **** ***** with ******** *** ******** **** ********* through ******** *****. **** **** ***** MMS ******, ***** ********* ***********, *** an******* **** ******* ***. ***** ******* ******** ****** ***** is * ***** ********* **** ******* steps *** ******** *********** ** ****** events.

**** **** **** **** ****** **** video ******* **** ***-***** ***** *** perform *** ** ***** *********, *******, they ** *** ********* *** ****** or ******** ***** **** **** *** VMS. *** ******** ***** *** **** for ***** *** ***** *************. *** said **** ** *** **** ****** VMS *********** ** ***** *******.

*******

**** ****** * ******** ************ ******* for *** *********:

  • *** ********* ******/*******/****** ********* *************** *** **** ***********: $** *** camera *** ***** ($*** *** ***** minimum)
  • ******* ***** ***********: $** *** ****** per *****
  • *******/******* **** ***** *********: $** *** camera *** *****
  • **** *********** $** *** ****** *** month, **** * ******* *** *** person ** * ***** ********. **** pricing ******** * **** ** ***** storage *** ***** ******** ($*** *** month *******)

*** ******* ********** ***** ** ******* from $*** - $*,*** *** *** support ****** ********* ** ** **** as *** ******* ** *** **** expensive ******, ** **** *********** ** 40 - ** *******.

**** **** **** **** ****** ************ includes * **** ** ***** *******, and ********** ******* ** ********* *** an ******** ********. **** ***** **** customers *** *** ***** **** *********** subscriptions ********* ******** * **** ** storage.

Primarily ****** ***** / ******** ** ***** *******

**** ***** ****** *** *** * limited ********** *******, *** ***** **** want ** ******** ***** ********** **** to *********** ***** ***** ***** *** support ************ *** **** ************* ** **************** ** ******** **** ****. **** said **** **** ****** ****** ****** with **** ***** ********** ******** ******.

Comments (2)

Very niche unless LPR does not require a minimum.

Agree
Disagree
Informative
Unhelpful: 1
Funny

If I had a nickel for every Ex-Google, Ex-Amazon, Ex-Microsoft engineer that believes they could be successful in the surveillance/security market by the merits of the technology (i.e. using "AI analytics",) I would be rich.  What "they" fail to understand is that it is not a technology problem - it is a sales/marketing problem that deserves more attention.  Detecting objects is not solution, it is what you do with it.  100-1000 images for training will not yield an accurate model.  

NOTICE: This comment has been moved to its own discussion: AI Startups - What They Fail To Understand Is That It Is Not A Technology Problem - It Is A Sales/Marketing One

Agree: 2
Disagree
Informative: 1
Unhelpful
Funny
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