2. Value proposition
Did you know that: The average cost of unplanned
downtime in lost revenue, financial penalties, idle staff time,
and restarting lines is $532K according to senseye.
Problem: Industrial equipment breaks.
• Di-agnostics is a service for industrial equipment
failure prediction and anomaly detection.
Industrial AI sound analytics SaaS for prediction of failures
in heat engines and electrical motors, to help enterprises
simplify their work and reduce maintenance costs.
• It uses Machine Learning and Artificial Intelligence
to predict failures before they happen.
• The current focus is on sound analytics of
heat engines and electrical motors.
3. How Di-agnostics works
Record the sound of how the equipment
works and transmit data via the special
Process it in the cloud infrastructure for data
computing and analytics.
Use a large dataset of the different sounds of
industrial equipment. It was built a comprehensive
data pipeline to easily train, schedule retrain, and
use specific models.
Receive motor status in seconds and
analyze spectrogram via UI for administrators and engineers.
No needs to buy additional vibro- or noise-
sensor for each electrical engine. Data is the
The user stays on the field and sends
data for analytics to the cloud. No needs to
move to fixed working place.
03 No needs to teach new engineer
how to hear if the equipment
works in normal or pre-failure
04 a-Gnostics already has production
implementation of Energy Consumption
Forecasts service for large Ukrainian
agroindustrial holding MHP, 30+ daily
Di-agnostics uses existing infrastructure,
machine learning models, AI and ML,
and data pipelines.
in the system.
5. Initial focus on global compound feed industry,
# of feed mills:– 28,414 in the world; – 6,232 in the USA;
– 6,948 in Europe.
3.6 million professional truck drivers in the U.S. and
37.9 million trucks.
There are 1,000 grain elevators in Ukraine; 8,800 in the
USA; 28,000 in the world.
Poultry: slaughter 68,000,000,000 heads a year vs
403,000,000 (0.6%) at MHP, largest in Ukraine.
The biogas market will grow from $3.1 to $6.52B in 2028.
In 2022 Di-agnostics is piloting in Ukraine at:
1. compound feed manufacturers and
2. poultry farms;
3. biogas stations.
Implementations and go2market
In the United States and Canada pre-piloting:
1. oil & gas industry, specifically for electrical
engines at rod pumps, and other equipment.
The next focus is on internal combustion
engines for trucking industry.
During the tests accuracy of the models – 93% and above in specific cases.
6. Market overview
Total market of electrical motors: $106.3 B in 2020, and reach $207.3 B by 2030; CAGR of 6.7%.
Industry: agritech, 4.3%; repair and maintenance budget, 5%.
• TAM (Total Addressable Market): 121 B x 0.043 = 5.2 B engines in agro.
• SAM (Serviceable Addressable Market): 5.2 B x 0.05 = 260 M spent for motors repair.
• SOM (Serviceable & Obtainable Market, Share of Market): 260 M, 10% of enterprises, 26 M / Year.
Trucking industry & heat engines:
$732.3 billion in gross freight
• Top 20 electric motor manufacturers
and 300 million industry globally;
Over 30 million engines sold each
• The farms equipment market is 99.4B
in 2021 and $126 in 2027.
• The predictive maintenance market is
$4B in 2020 and $18.6B in 2027.
• 50,000 employees work in repair and
maintenance services in the USA.
1 – Using AI ML, cloud portal, real-time.
2 – Special app vs hardware.
3 – Accuracy.
Di-agnostics Neuronsoundware Signally.ai Groundup.ai NLacoustics
1 ✔️ ✔️ ✔️ ✔️ ✔️
2 App Sensor +
Data Data + Hardware Camera
3 93%+ Depends on data
Depends on data
reduce by 25%
No public info
4 Automatically* 3 month No public info Enterprise specific 3-5 month
5 Scalable to all
6 B2E SaaS** and
B2E B2E B2E B2E
* – Companies and users do self-registration, and models are retrained automatically as new data comes.
** – Framework is ready for unlimited scaling in the cloud.
*** – There are many users’ apps on sound or noise diagnostics; no backend and enterprise-level security.
4 – Time to set-up new customer; new model.
5 – Is specialized in equipment industry?
6 – Enterprise vs B2C. Initial investment.
8. Roadmap and finances
$150,000 for 10% of current shares.
1. 0 – cloud. The current grant from Microsoft for $150,000 for 2 years on Azure.
2. 30% – business development. A salesperson in Houston, TX; UK or Germany.
3. 10 % – marketing. Customers’ success stories, upgrade existing materials and
create a video.
4. 10% – advertising. Launch an online campaign. Focus on feed mills in U.S.;
5. 50% – product development. According to the roadmap.
Technical and product roadmap for 2022, September – December:
1) prediction on the phone, offline; 2) models improvements; 3) iOS version;
4) Remaining Useful Life (RUL); 5) security certification.
In late 2021 it was released the Enterprise version of Di-agnostics
service, the cost is $2,500 per month per enterprise, to monitor up to
25 large engines (more than 200 kW).
9. Yaroslav Nedashkovskyi
System architect, technical team lead, and
senior software developer since 2003.
Joined SoftElegance in 2011.
Competences: Architecture, Technical
implementation, Machine Learning and AI.
a-Gnostics co-founders and team
Chairman of the board, Co-founder.
Founder of SoftElegance, a custom
software development outsourcing
Competences: Strategy, Finances.
In software development and
project management business since
2004. Joined SoftElegance in 2010.
Co-founders work together since 2011. The first
service of a-Gnostics launched in 2018, after
graduation from Energy Accelerator.
The current team that works on sound analytics
since December 2021, consists of 6 members.
Competences: Product, Marketing, Sales.
10. S E Project Management Ltd.
Company number 07602794
142 Cromwell Road,
London, United Kingdom, SW7 4EF
+44 207 048 7339
+380 50 312 4725