KERNELBAY LIMITED

HUMAN BEHAVIOR AUGMENTED ANALYTICS

5.0 2 Reviews
Visit website
Write a Review
Verified Profile

Kernelbay’s foremost mission is to provide every company in the Business-to-Customer segment with relevant insights that can be directly transformed into working strategies. Our goals are based on professional experience within such AI fields as Machine Learning, Data Engineering, Deep Learning, and Augmented Analytics.

Our main areas of expertise are machine learning, data engineering, deep learning, augmented analytics, and every new technology within the AI sector.

NA
2 - 9
2021
Locations
Cyprus
Stasinou 1, MITSI BUILDING 1, 1st Floor, Office 4, Plateia Eleftherias, Nicosia, Nicosia District 1060
+380674268888

Focus Areas

Service Focus

70%
30%
  • Artificial Intelligence
  • Big Data & BI

Client Focus

90%
10%
  • Small Business
  • Medium Business

Industry Focus

30%
10%
10%
10%
10%
10%
20%
  • E-commerce
  • Healthcare & Medical
  • Hospitality

KERNELBAY LIMITED Reviews

5.0 2 Reviews
  • All Services
  • Artificial Intelligence
  • Big Data & BI
  • Relevance
  • Most Recent
  • Rating: high to low
  • Rating: low to high
Write a Review
Victor Yermak

Yield Losses Estimation & Monitoring for agriculture insurance (application of data enrichment approach)

Rating Breakdown

  • Quality
  • Schedule & Timing
  • Communication
  • Overall Rating

Project Detail

$10001 to $50000
Completed

Share it on

Review Summary

Our standard approach to the task was using vegetation indexes for loss yield estimation. Kernelbay bring confident that these results can be improved by enriching the data. For example, collecting such as temperature at data analysis points, wind strength, soil moisture, atmospheric pressure, and many other parameters that are available for analysis. By enriching source data, we can find insights, patterns, anomalies, and correlations between initial and enriched parts and thus significantly improve the results in a single field.

What was the project name that you have worked with KERNELBAY LIMITED?

Yield Losses Estimation & Monitoring for agriculture insurance

What service was provided as part of the project?

Artificial Intelligence

Describe your project in brief

The project aim is to develop a model of yield losses estimation and monitoring based on a series of vegetation maps of the field, precise weather data, and tracking climatic events such as drought, floods, hail, hurricanes, etc.

What is it about the company that you appreciate the most?

{"1":"unique approach, value for money, time to delivery, smooth cooperation"}

What was it about the company that you didn't like which they should do better?

{"1":"project documentation would be more detailed and supplement by diagrams and pictures"}

Ilya Gandzeychuk

Augmented Analytics solution to create the ML model for sales prescriptions.

Rating Breakdown

  • Quality
  • Schedule & Timing
  • Communication
  • Overall Rating

Project Detail

$10001 to $50000
Completed

Share it on

Review Summary

We had a large dataset with sales data of big toy shops network. We needed to build ML model for weekly rollout sales prescriptionsn based on consumer behavior predictions.

Kernelbay enriched the dataset with broad range of parameters which define the envronment at location and time each sales transaction proceeded. Then they provide us with correlations, insights, patterns and anomalies and build the ML model for sales prescriptions using forecast of that enviromental parameters.

What was the project name that you have worked with KERNELBAY LIMITED?

Augmented Analytics for consumer behaviour predictions

What service was provided as part of the project?

Big Data & BI, Artificial Intelligence

Describe your project in brief

We had a large dataset with sales data of big toy shops network. We needed to build ML model for weekly rollout sales prescriptionsn based on consumer behavior predictions.

Kernelbay enriched the dataset with broad range of parameters which define the envronment at location and time each sales transaction proceeded. Then they provide us with correlations, insights, patterns and anomalies and build the ML model for sales prescriptions using forecast of that enviromental parameters.

What is it about the company that you appreciate the most?

Their approach to work with data is to enrich the intial data with external data.

They have experience to deal with a lot of sources of available open data.

What was it about the company that you didn't like which they should do better?

In this project, we were quite satisfied with the service