Carnegie Mellon AI Startup Zensors Profile

By Sean Patton, Published Jun 11, 2019, 11:40am EDT (Info+)

Zensors is a startup formed by Carnegie Mellon graduates from a Carnegie Mellon research project, offering customized models per camera that they claim delivers significantly higher accuracy.

We spoke with Zensors to better understand their approach, how they plan to scale their system and their go-to-market.

In this note examine:

  • Who is Zensors
  • What Customers is Zensors Targeting
  • How Much Does It Cost
  • What is Zensors' Go-To-Market
  • What Type of Analytics
  • How Do They Generate Custom Datasets
  • What VMS Integrations

Zensors ********

******* ** ****, ******* *** ********** a ******** ******* ** **-************* ****************** ****. ******* ******* ** ********* ** Pittsburgh *** *** *********, ********* ******* development ******, *** * ** ****** contracting **** ** ***** *** ******* labeling. ******** ** ** ********* ********* of *****-******** *********** ** ******** ****** University, ********* ***** ****** ********** *****, while **** ****** * ******* ****** in *****-******** *********** ** ******** ******, as **** ** ********** ******* *********** and ** ** ******** ** ********.

******* ******* $*.* ******* ** *******. They *** *** ******** *********, *** they *** ******* *************, *** *** * *********** **** DHS, *** * ****** *********** ****, ******* ** ***** **** ********** investments.

***** ********* **** ******* **** *******

******* ** ******** ***** **-***** ***** analytics **** **** ******-********* ****** ******** that *** ********* ******* ** ****** people *** ********, *** ***** **** 500 ****** ** ******* ********* *** available.

******* **** **** ***** ***** ****** to *** ********'* ******** ******* ** generate ************ ****** ***** ** ****-***** video (*.*. ****-**** **** ********, ******* tracking, **** *********). ****, **** ***** they *** ********** ****** ******** ** analytics, ***** ** ****** ***** ****** verticals (*.*. ***** **** *******, ************** Terminals).

**** *-****** ********* ***** ***** ******* people-counting *** ***** ********** ** ****:

One ***** *** ******

******* **** ******** ****** *** ******* and ********* *** ******. **** ** atypical **** **** ***** *********, **** AI-based ******, ***** *** ******* ** public ** ****** ******* **** ** images ** ****** *** ******** ******* (for **** ******** *******, **** ******** ******** ******** *** ***** ************). ******* ****** **** *********** ** models **** *** **-**% **** ******** and ******** ******** **** **** ********, night ****, *** ****** *********. **** noted ***** ** * ******** "********" neural ******* ***** *** ***** ******** per ****** ** *** * "**********", and ******* ** **** *** ******* as **** ********* ** ******** *** entire ****** *******.

******* **** ******** *** ******** *** created ***** ******** ********* ***** *******, customer ****** ***** *** ****** ****** from ******* ******** ** ***** ******** sites.

****** ********* ** ****** *********

******* ****** * *** ********* *** event *******, ********* *** ****** ************. Their ****** ** ****** ** ***, and ***** ** *** ** ********* on-premise, ******* **** **** **** **** deployed ******.

******* **** ***** ********* ** ******** to ***** **** *****, **** ** digest ****** ** ***********, ** ******** the ***** ******** ****** ** ****. To ****** *** ******, * **** asks * ******** (*.*. "*** **** cars *** ** ****?", "*** **** people *** ****?"), *** *** ********* specific ***** ** *** ***** ** search:

**** ** ******* ** ************* ******* by*****'* ******* ******** ********** (**** ****). *** ******** *** ** ******** into **** ******* ***** "********* *****" Reports, ***** ******* ********** ********* ** the ****** ** ******* ******* *******:

** **** *********** ** ******* ********

******* **** **** ***** *** ** develop **** *********** ****** ** ****** classifications, *** ******* *** ***** ********. They **** **** ***** ********* *** not ******* ** ******* ******* ********* (e.g. ******* ********, ******* ** * library) ** *******, *** ******* *** customized ****** ******** ** ******** ******* behaviors.

Targeting ***** ******, *********, ***** **********

******* **** **** *** ********* ***** city ********, ************** **** (*.*. ********, train *********), *** ***** ********** **** large ******* ** ****** *** ******** (e.g. **** ******** *******, ***** ******* garages). * ************** ****** ****** ** the ******* ** ******* ******* ******** modeling, ***** **** **** ****** **** to ********** ****** ********, *** ******** the ***** ** ********. **** **** they **** ********* **** ***** ********* for ***** ******* ************, *** ****** and ******* ********.

******* ****** ** ******* **** **** mounted * ** ****** ****** **** an ********** ******** *** **********, ********* used ** **** *******, ***** ***** $1,500 - $*,***. **** **** **** are ***** ** * ***** ******** in **********, **** ***-***-***** **********.

Per ****** *** ***** *******

******* **** **** ******* ******* *** standard ******** ****** (*.*. ****** *** vehicle ********) ** $** *** ****** per *****. ************* *** *** *****, so * ****** ****** ******** ****** and ******** ***** ** $** *** month. ******* **** *** ******, ********** behavior-based ****** **** $** *** ***** per ****** *** *****. **** **** said ***** *** ******* ***** *********, which ****** ** *** ****** ** processing ********, ***** ** ***** ******** and ******** ***** **********.

3rd ***** ****** *******, ********* ***** *******

******* **** **** ******* *** ***** cameras ***** ******** ********* (*****, ****, FTP ********), *** ********** ** *******. Atypical *** **** ***** *********, ******* said **** ** *** ******* **** fps, *** ***** *** ********** (*.*. people ***** ********), * ***** ***** 10 ******* ** ******. ******* ******** and ******** ***** ********* ******* ****** frame *****.

** ******* ******* ** ******* *******, they ******* ** **-******* ******* **** 6 ****** ** ****** *********.

Direct ***** *********, **** ** *** ****

******* ***** ****** ** *** ***** but ***** **** *** ******** ** build ** ********** *******. **** **** that ************ ** *** ***** *** integrators ** ***** ******* ***** ****, but **** *** ********* ****** * sales ***********/******** *******,** ******** ** **** *********** ********* and ***********.

Only *** *********** - **********

******* ***** ***** **** *** *********** is ************** ************ **** **** ***** ** ********** more ************ ** **** ** ***** development *******. ************, **** **** ****** integrations **** ***** ********** ** ******** connect *** **** ********* ****** **** the ****** ** ****** *******.

Potential **********, ** ** ****** ***** ****

***** **** ******** ****** ** * leader ** ** ********, ** ******* that *** ********** ** ******* ****. The ********* ** *** ** **** it ** *** ***** **** ******** market **** *** ** (** **** a ****** ********? ***********? **************?). **** advanced ***** *** **** ***** ** a **** **** **** *** **** do ****** **** *** **** (******* example****** ***** **** ****** ********* ****). *******, *********** ********, **** *** benefit **** * **** ****-*** *********** specific ******** **** ** ****** ** understand *** ** ****.

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