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Organizing the tsunami of videos and making them searchable and useful

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Organizing the tsunami of videos and making them searchable and

useful

About Us

• Empowering brick & mortar retailers with actionable insights using existing in-store video

• $20B total addressable market

• Machine Vision + AI + Deep Learning from MIT CSAIL• Auto-detect similar objects based on appearance and

activity• 1 PCT and 3 provisional patent applications filed

• Signed LOI to one of the largest camera manufacturers• 5 pilots with multi-national companies in retail applications

• Mark Cuban (pre-seed funding 6/14)• Techstars Boston 2015 class• $500K convertible debt round (7/15)

Overview

Primary Focus

Technology

Customers

Investors

• Founded 2013, 8 employees, U.S. Delaware Corp.

Senior Team

Richard Lee, Co-Founder & CEOSales, Marketing, Finance, Retail Innovation

Shaser Bioscience (2010-2015)• VP Marketing • Majority acq by SPB for $50M in 2012P&G / Gillette (2003-2010)• Global Manager, RFID Strategy• Marketing Innovations / Brand ManagementMIT MBA (2001-2003)• Research, Auto-ID Center• Mastercard, New Payment TechnologiesPwC, Cambridge Incubator (1994-2001)

Shashi Kant, Co-Founder & CTOEmergent Semantics, Web Architecture, Machine Learning

Cognika (2006-2013) - Co-Founder and CTOMIT MS (2004-2006)• MIT CSAIL• Researcher, MIT Auto-ID Center• ASP Fellow, Systems EngineeringAbsolute Software (2000-2003)• Web ArchitectThinq.com, Trintech, Schlumberger

Why Video Analytics (now)?

Brick and Mortar Retailers are in a Period of Massive Re-Invention

Finally entering the “age of enlightenment”

Actionable Insights Using Existing Infrastructure

Technology / Innovation Finally Delivering on Promise

IRIS+ TechnologyBased on Appearance & Activity vs. “Trip-Wire”

Female, based

on flowing

hair

Large human walking

Female, based

on body feature

s

Brown hair Red

shirt Blue pants White shoes

C T S C

C T S CFemale,

based on

flowing hair

Small human walking

Female, based

on body feature

s

Brown hair Red

shirt Blue pants

“Quantified Store” with IRIS+

1. Shopper Foot TrafficNationally, By Region, By

Store

Focus on Traffic, Time in Store, Conversion

2. Time Spent in StoreTotal, By Department, Dwell,

Interactions

3. ConversionsNumber of Transactions,

Abandonments, Basket Size, Conversion Percentage

IRIS+ Demo for QSRMarketing interested in Shopper Traffic & Peel-Off

Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul 36,000

38,000

40,000

42,000

44,000

46,000

48,000

50,000

5.4%

5.6%

5.8%

6.0%

6.2%

6.4%

6.6%

6.8%

Monthly Traffic & Peel Off Rate

Passerby Traffic (in 000s) Peel Off%

Total Chain Datato understand drivers

Store- and Regional Datato understand winners / laggards

IRIS+ Demo for QSRMerch / Store Ops interested in Time Spent in

Store

Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul5.60

5.70

5.80

5.90

6.00

6.10

6.20

6.30

6.40

6.50

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

In-Store Activity

Time In-Store (min) Salesperson Interaction (%) Display Engagement (%)

Ability to deep-dive into Time by Activity

Understand which promotions work

Track Interactionsby Salesperson / Stores

Visualizations for QSRData Visualizations help understand what’s

working

Target Customers

Initially, Netra will Sell Through:• Camera Manufacturers• Solutions Providers• Integrators

Signed LOI with camera company & 5+ pilots currently

Eventually, Netra will Sell to End-Users:• QSR Chains• Department Stores• Cell Retailers• Mass Merchants• Grocery Stores• Convenience Marts• Gaming• Municipalities

CompetitionFocus on improving Usability / UX vs. Core Technology

Financial Projections$125MM+ revenues focused on Retail Intelligence only

$000s 2015 2016 2017 2018 2019

IRIS+ streams 339 4,115 28,331 137,379 422,514

Revenues $249 $3,956 $12,127 $41,574 $126,013

Operating Expenses $397 $4,210 $11,279 $29,989 $90,451

EBITDA ($157) ($358) ($171) $6,308 $31,274