Our mission is to democratize access to artificial intelligence by bringing down the cost of development and propel cost conscious organizations, small and medium enterprises and individuals to participate in the Artificial Intelligence market. We focus on key cost contributors of AI development 1. Labeled Data, 2. Computational Power 3. Qualified Labor.

1. Distributed Synthetic Data Platform for
Deep Learning Applications
Where androids dream of electric sheep
December, 2017

2. Neuromation Platform - Revenue Model
Neuromation partners with an established software or hardware vendor and will work as partnership entity to enhance vendors product.
1. Partnership with established software/hardware provider.
2. Development a product that would enhance (give brains) to the product that’s been already sold by the vendor
3. Incremental revenue from the enhanced product will be allocated to the partnership (neuromation labs)
4. Allocations of incremental revenue is distributed based on the partnership agreement with individual vendors/providers
Neuromation Labs - Revenue Model
Neuromation Platform brings together synthetic data generation for training AI models using vast computational resources of cryptocurrency mining community. The platform provides easy access to
AI practitioners and commercial entities. Requests for AI solutions will be published on the platform in predetermined format. AI practitioners will bid for the contract and will execute delivery through a
smart-contract project management and settlement mechanism.
Neuromation Platform will collect transaction fee based on the nature and volume of the contract participants. Neuromation fees will vary between type of domains, components, and participant and is
expected to be under 9.6% of the total transaction cost.
Our platform will channel computing
capacity of cryptocurrency miners into
more lucrative “knowledge” mining:
distributed computation processing for AI
tasks. This will bring down the cost of the
AI practitioners and will benefit providers
of the computational powers by
increasing their revenue
Mission Statement: Our mission is to democratize access to artificial intelligence by bringing down the cost of development and propel cost conscious organizations, small and medium enterprises and individuals to
participate in the Artificial Intelligence market. We focus on key cost contributors of AI development 1. Labeled Data, 2. Computational Power 3. Qualified Labor.
We built the first commercial framework
adaptation of the synthetic dataset. The
results indicate a higher level of
accuracy than manually labelled
datasets. Our adaptation proved that
the use of synthetic datasets is cost
effective and flexible in implementation.
The Neuromation Platform provides an
exchange and ecosystem where participants
can either contribute or purchase the
components of an AI models. AI practitioners
will have direct access to the commercial
entities and platform will eliminate the need
middle-brokers (consulting companies,
vendors, brokers)
Labelled Data
Synthetic Data
Computational Power
Cryptocurrency Miners
Labor - Direct Access

3. Units of Input
of USD per
Input
Number of
Transact.
(000)
Revenue
(USD)
Data Generator USD/ Units 25 200 $ 5,000,000
Data Generation mages 0.05 1,000,000 $ 50,000,000
Model Training Hours 100 20 $ 2,000,000
Units of Input Input
Number of
Transact.
(000)
Fee
Transaction
Volume (000)
Revenue
(USD)
Data Generator USD/ Units 260 10 10% $ 2,600 $ 260,000
Data Generation Images
1,000
15 2% $ 15,000 $ 300,000
Model Training Hours
60
1,000 15% $ 60,000 $ 9,000,000
Model Deployment
USD/#of
models 15,000
1 2% $ 15,000 $ 300,000
Neuromation
Platform
Neuromation
Lab
REVENUE
Data Generator
Data Generator - is a software designed to generate a specific synthetic dataset with
the design and objectives set by the requesting party. This is a software development
product.
Data Generation
Data Generation - is a process in which a specifically designed Data Generator is used
to produce synthetic images (3D models of a target object).
Model Training
Model Training - is the process of feeding the output synthetic dataset instances (e.g.
images) produced during Data Generation to feed the deep learning models
Data Labeling White-labeling of the harvested images by outsourcing companies
Data Set Sales sales and re-sales of the datasets produced in Data Labeling process
SaaS
(API + Computing power)
Creating deep learning models in accordance with the technical design
specifications of the requestors.
Model Deployment Deployment of the deep learning models for end-solutions
TOTAL COST
● Payroll
● Total PR and Marketing
● Hosting Computing/Power
● Miscellaneous
● Total
$2,958,000
$ 600,000
$ 1,440,000
$ 456,000
$ 4,454,000
PLATFORMNEUROMATIONLABS
PRODUCTS

4. Valuation
Investments
● Presale
● First Week
● Second Week
● Third Week
TIMING BONUS:
+ 25% in Neurotokens (NTK)
+ 15% in Neurotokens (NTK)
+ 10% in Neurotokens (NTK)
+ 5% in Neurotokens (NTK)
TOKEN Purchase
● 2018 year revenue with LOI $
3,750,000
● Total estimated Revenue (2018 - 2019) $
67,000,000
Neuromation Estimated Revenue
2018 - 2019
January 1st January 7th, February 15th,