1. Company Presentation
September 2012

2. The Company
Established in 2011, 12 employees, Located in Ramot –Hashavim Israel
– Igal Zivoni: Founder and CEO
More than 20 years of Significant international experience holding senior executive and leader position in the high-
tech industry. Prior to founding, Meteo-Logic, Igal was founder of several Internet ventures
– Olivier Attali: VP sales and business development
More than 15 years of international experience in sales & marketing, business development, strategy & management
positions with excellent track records in several leading high-tech companies
– Nir Kalkstein : Algorithm Expert
world renowned expert in the field of algorithmic prediction and data mining. Founder of “Medial Research” a
research institute that has pioneered the field of algorithmic analysis of medical data
– Dr. Baruch Ziv: Senior Advisor
A veteran synoptic meteorologist with over 20 years of experience in research & teaching. He has been a senior
lecturer in the Tel Aviv University, the Hebrew University of Jerusalem and the Open University for more than two
decades, teaching applied meteorology, air pollution & agro-meteorology
– Danny Deutsch: Professional Advisor
Danny Deutsch is a veteran meteorologist with over 14 years of experience in the field of weather forecasting. He has
been the TV weatherman of Israel’s most viewed news program on Channel 2 for seven years. Danny served in the
past as a meteorology officer in the Israeli Air force
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3. Strategy in a Nutshell
Mission Statement
Meteo-Logic is revolutionizing the weather forecast market with a
unique solution providing accurate weather forecast to the point
UVPs:
– Accurate weather forecast
• Precise location with any type of topology - Forecasting To the Point
• Precise time resolution: per hour
– Full Availability supplied by online service
• 4 updates during 24 hours
– The most cost effective solution
Market
– Focus on Professionals and Semi-professionals
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4. Target Market
• Energy
– Renewable Energy
– Electricity companies
• Agriculture
• Government
– Defense, Security, Risk management
– Municipalities & Smart City
– Environmental & Green
– Water Authority
• Transportation
– Aviation
– Airport, Seaport, Marine
• Media
• Others:
– Leisure , Insurance, Construction, Outdoor events, Production…
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5. Concept & Technology
• Meteo-Logic’s innovative technology offers an automated
solution to the problem of connecting the synoptic
forecasts at high altitudes with forecasting measured
values on the ground.
• The flow stems from two primary reasons:
– The physics that links the situation at high altitudes with the
measured values on the ground are extremely complex, and are
dependent on a large number of parameters.
– The topography and climate of a specific point are very
significant influences on getting accurate values.
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6. Concept & Technology
• Meteo-Logics service works in two stages:
– The system gets historic data for several years for a specific
point. Using this data, the system develops a complex, specific
model to link the synoptic situation to the measured values in
that specific area over time. This new statistical model is based
on specially developed Knn algorithms.
– To give a real-time prediction, the system uses the current or
forecast synoptic situation, and compares it to the historic
synoptic situations previously fed for that area. The algorithm
examines similar past synoptic situations and chooses the
correct metamorphosis for that particular synoptic situation.
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7. Solution
Meteo-Logic is SAAS platform, built to enable weather
forecasting derived from any weather station around the
globe directly to end users with no human intervention
• Accurate forecasting
Meteo-Logic brings the most accurate weather forecasting to a specific point, Our
algorithm analyze weather data history and generate 5 days hourly forecasting
accordingly
• High availability
As a SAAS service, Meteo-Logic’s forecasting is available to its user on any media, in any
place with internet connection (dedicated mobile app is under development)
• Competitive pricing
Meteo-Logic’s pricing plans are highly attractive, mainly due to the fact that the the
human factor is eliminated, we are build for scale and can serve high volume of
concurrent users
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8. High level feature set
• Access from anywhere
• Over 100 active Forecasting Points over Israel, generating
ongoing forecasting 24/7
• Predict Temperature, Rain, Humidity and Wind
• Proprietary ranking system allows to track prediction
quality
• History analysis per Forecasting Point
• Download prediction file for offline use
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9. Product Efficiency
SS-factor evaluates the prediction skill with respect to
reference forecast (global model) and perfect forecast
RMSE RMSE ( ref )
SS
RMSE ( perf ) RMSE ( ref )
ML prediction perfect prediction Ref. prediction (Global model)
SS>0 means that our prediction is better than
the reference one and SS=100 means that we
have reached the perfect (optimal) accuracy
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10. Product Efficiency
Validation of ML against global model (GFS)
Region SS-factor
S-factor is the ratio between the Coastal Plain
natural STD and the standard error of Mountains
the pertinent prediction model Negev Desert
temperature prediction
The S-factor for ML is twice
large as that of the global
model
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11. Product Efficiency
Example: Tel-Mond station
Meteo-Logic Prediction vs. Measured
Temperature
Meteo-Logic Prediction vs. Measured
Humidity
The prediction reflects realistically
the daily course of temperature &
rel. humidity
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12. Product Efficiency
Comparative ranking of the predictions of the global model
(GFS) and ML
Ranges for successful prediction
Temperature - 1 C
Relative Humidity – 10%
Wind speed – 4 m/s
Validation for 4 stations
The rank is the percentage of successful predictions
ML rank is higher by 20-30%
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13. Service view
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14. Thank You
Meteo-Logic team
info@meteo-logic.com