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PredictiveGrid™

Mary 18, 2016

Company Confidential

Successful approval of Seed C term sheet which is reset of cap table and control structure (full support of GE Ventures and Investors in the Seed C Round) positioning us well operationally and for next Series A Round

$250K DOE grant awarded to us to develop our products and commercialize for market (NOT a research award)

PG&E, contract signed for paid Proof of concepts - increase Paid-Proof of Concept Demonstrability (3 new use cases- total $125K)

Preferred Vendor Status Contract Signed with PG&E - Allowing PingThings to conduct business with all other business units

PG&E recommended us to their Distribution group for more paid product engagements -building our modules tailored to this new group (have immediate budget in place for immediate engagement)

Major Data Sharing Agreements signed – We are getting data from 20% of all utilities in North America and estimate we will be getting data from 40% in Q4.(Peak Reliability Contract signed, ISO New England Contract signed, more in discussion)

Starting Multi year commercial (beta) license deal discussions ($950K - $1.2M each) with Peak RC, PG&E and other major utilities/ISOs (Central Main Power, Idaho Power..etc).

Completed military grade colocation facility – data security audited and approved by Peak Reliability Coordinator and PG&E.

Continuing Thought Leadership in the industry- published O’Reilly technology book in March “Data and Electric Power- From Deterministic Machines to Probabilistic Systems in Traditional Engineering”

Business update- last 90 days

$800B Invested in Smart Grid infrastructure in the past decade

4

Existing technology is exploiting only a fraction of the data’s potential value

Intelligent, transmission sensors generate massive amounts of high fidelity, high volume data

Uses SmartGrid data to provide real time, pinpoint visibility into critical assets and environments, for multi-million dollar cost savings and transformational insights

Aging Physical Infrastructure

Break/Fix Approach

Electric Utility Challenges

3

Utility Industry is $1T in US alone with $3T in assets, Unplanned utility outages cost $180B per year

Explosion of New Data


4 Company confidential

Market Status

A PROACTIVE solution to one opportunity - Intelligent Asset Maintenance - will save $50B per year in the US

Intelligent Asset

Maintenance

Asset Protection

Solar Flare + GMD Impact

Security (EMP)

Intelligence

Distributed Generation Disruptions

Islanding

Dashboards BI & Reporting

Historical Analytics

Legacy solutions are REACTIVE

Opportunities

Leveraging IoT Investment

PingThings uses existing end-points and data streams to create new IoT Applications Uses Big Data Science to identify anomalies, create alerts and

recommend actions from existing data streams and external data

Creates an Anomaly Detection Engine that monitors the same data streams in real time to identify events, alerts and corrective actions

That is continuously refined through ongoing Machine Learning

Empowers operators with tools to mitigate disruptive events before they happen

Makes use of current under-utilized data instead of adding additional sensors, networks and data management

5

High demand for analytics

North American Smart Grid Market Growth 2013-2014

Source: GTM Research 2013-2014

Growth Rate (CAGR)

US transformer monitoring analytics alone will grow 8x in 5 years

6 Company Confidential

Traction


Investors

Proof of Concepts

Research Partners

Who We Are


Rich Sootkoos Chief Executive Officer

Jerry Schuman Chief Technology

Officer

Sean Patrick Murphy

Chief Data Scientist

3x Founder/Co-Founder with

Successful Exits Senior Executive

Activision, ZeroDegrees,

Idealab, Disney, PepsiCo

Senior Scientist Johns Hopkins

University Applied Physics

Advanced Machine Learning

3x Founder/Co-Founder

Sun Microsystems, Apple, Canon

Mehrdod Mohseni Chief Revenue Officer

Chief Marketing Officer GE Energy

President UISOL, an Alstom Grid Company

Registered Professional Engineer

and Senior IEEE member

5

Ingest Engine

Receives &

processes data

PhasorSense™

Specific Smart Grid data science

algorithms combined with machine learning

Saving utility companies tens of millions by reducing the need for additional hardware and/or expensive field based site activity

Initial Use Cases: Asset Maintenance, Asset Protection, Asset Performance, Sun Flares, Weather events, Hydro/wind/solar impacts

PredictiveGrid™

Assessments & alerts

for pinpoint visibility

Transforming Transmission Operations

9


SCADA

PMU

OTHERS

HISTORIAN & PDC’s

Stream

SPS

EMS

OMS

EMS- Energy Management System SPS- Special Protection Systems OMS- Outage Management Systems

Ingest Engine

Ingest Engine

Receives &

processes data

Receives streaming and historical data from multiple sources and makes it available for analytics


Our technology can identify and predict events using existing high fidelity synchrophasor data without the need for additional hardware sensors deployments (see appendix)

Classifiers

Anomaly Detection Machine Learning

PhasorSenseTM

Patent-pending technology combines data science, machine learning, and algorithms to analyze grid specific data

PingThings Predictive Analytics

Actual readings from costly atypical hardware deployed for this specific event


Identifies priorities for action, in advance, without field deployment. Delivers actionable reports & alerts.

PredictiveGrid™

PredictiveGrid:GIC PMU Stream Processing

Typical Hardware requirements to support PingThings Analytics

• Apache Spark Streaming (compute fabric)

• Kafka (message bus)

• Cassandra (time-series persistence)

• nVidia Tesla GPU enabled “deep learning”

• GE Predix™ Machine Enabled

• C37.118.2 Protocol support

• Space Weather Prediction Center Alert Engine

• TPL-007-1 Compliance Assistance

Simple Installation/Integration

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Faster sales cycle

Faster adoption/penetration

• Current collaboration with DOE and interconnect entities (RRO- Regional Reliability

Organizations) that monitor large groups of utilities

Very high value to cost ratio at current expectations from large utilities

• Does not require a system change

• Significantly lower price point than current utility platforms

• Hyper-growth of data can be leveraged with minimal additional costs

Low risk / high reward

• Pure software play requiring no new hardware and independent of existing systems

• Appliance loosely-coupled architecture for easy assimilated plug and play

FERC orders & mandates

• Compliance (geomagnetic disruption / solar flares)

Company Confidential 15

Sales cycle reduced from 3 years to 6 months

Rich Sootkoos, CEO [email protected]


Investor Relations

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