a-Gnostics, 44 Palladina Avenue, Kyiv (2026)

10/08/2026

PV integrations are now live ☀️ 📈 solar generation data now flows automatically into Pro-gnostics forecasts. Product update from a-Gnostics'.

We've delivered integrations with three major solar monitoring platforms: Huawei FusionSolar, SOLARMAN Smart, and PV.SCADA by KNESS.

Why is this important?

Pro-gnostics provides solar generation forecasts as part of our Electricity Consumption Forecasting service.

Many of our customers have installed PV plants at their facilities and integrated them into their energy management systems. Alongside electricity consumption, they need to monitor and forecast solar generation.

Our new integrations allow Pro-gnostics to automatically collect actual solar generation data from these platforms and include it in our forecasting datasets.

The result: less manual data handling and more accurate solar generation forecasts for enterprises.

Want to see what Pro-gnostics can do for your energy management? Contact us for demo access and explore how you can:
📊 Forecast electricity consumption;
☀️ Monitor and forecast solar generation;
🔋 Manage battery storage;
💰 Work with electricity market prices.

29/07/2026

Thank you Radar Tech, for the article. It was extremely useful to participate at the ENERGY Accelerator Program with DTEK for our business. It was a great start, a lot of knowledge and contacts. And you team is highly professional, and amazing people

17/07/2026

Industry 4.0–5.0 in Ukraine 🇺🇦 and our co-founders Yaroslav Nedashkovskyi and Andy Starzhynskiy

It was a pleasure to speak at the conference and present "AI for Energy Portfolio Management."

Artificial intelligence is becoming an essential tool for modern energy management. During the presentation, we shared how AI helps businesses improve forecasting accuracy, automate routine processes, and make better energy portfolio decisions.

Pro-gnostics. An AI-powered platform for forecasting electricity consumption, renewable generation, and electricity prices.

With Pro-gnostics, organizations can:
⚡ Forecast electricity consumption with high accuracy;
🌱 Forecast renewable energy generation;
🤖 Automate energy forecasting and planning processes;
📊 Optimize energy portfolio management;
💰 Support better decision-making and maximize profitability.

Who benefits from Pro-gnostics?
⚡ Energy traders;
🐔 Poultry farms and grain storage operators;
🏭 Industrial energy consumers.

Thanks to the and for the invitation and to everyone who attended the presentation and contributed to the discussion. I truly enjoyed sharing our experience and discussing how AI is transforming energy management and accelerating the adoption of Industry 4.0–5.0 technologies in Ukraine

25/06/2026

🇺🇦 🇨🇿 Report from the Ukraine–Czech Smart Industry Mission, June 2026

a-Gnostics founder @‌andriistolbov joined the delegation of the Ukrainian Cluster Alliance during the 4th Smart Industry Mission to the Czech Republic. The program included visits to four leading European Digital Innovation Hubs (EDIHs) in Prague and Brno.

The mission aimed to introduce Ukrainian industrial SMEs to the opportunities offered by the Czech innovation ecosystem and to establish new channels for cooperation between Ukrainian and Czech organizations.

One of the strongest impressions from the trip was the rapid adoption of industrial robotics. As shown in the second photo, autonomous machines are increasingly becoming a standard part of modern manufacturing. In the coming years, many routine industrial operations will be performed by robots and autonomous systems.

However, robotics is only part of the transformation. As factories become more automated, the importance of equipment monitoring, predictive maintenance, and AI-driven diagnostics grows significantly. Industrial organizations will need solutions that can continuously monitor machinery, detect anomalies, predict failures, and optimize operations before disruptions occur.

A key stop on the mission was Brain4Industry (B4I), located in Dolní Břežany near Prague. Brain4Industry is a consortium of research institutions, universities, and technology companies specializing in manufacturing digitalization, artificial intelligence, and additive manufacturing.

Their service model is particularly relevant for Ukraine and focuses on three major areas:

🤖 Digitalization and Artificial Intelligence:
Digital audits and digital transformation strategies;
Digital twins and AI-powered production solutions;
AI assistants for industrial applications;
Data integration across the entire product lifecycle.

🦾 Additive Manufacturing and Engineering:
Mathematical modeling and simulation;
Testing and validation;
Metal 3D printing and rapid prototyping;
Design for additive manufacturing.

Another highlight of the mission was the Cybersecurity Innovation Hub and CyberRangeCZ in Brno.

While cybersecurity is often viewed as a support function, the Czech approach treats it as an essential component of digital transformation. This perspective becomes increasingly important as industrial equipment, robots, sensors, and AI systems become interconnected.

CyberRangeCZ provides a realistic environment for simulating cyberattacks, training teams, testing the resilience of critical systems, validating digital solutions before deployment, and practicing incident response scenarios.

For us, the key takeaway is clear: the future of industry will be built on the combination of robotics, artificial intelligence, predictive monitoring, and cybersecurity. These technologies are no longer separate initiatives, they are becoming parts of a single industrial ecosystem.

Many thanks to @‌APPAU, the Ukrainian Cluster Alliance, the Czech EDIHs, and all partners who made this mission possible. We look forward to future collaboration and joint innovation projects between Ukraine and the Czech Republic

15/06/2026

⚡ a-Gnostics Challenge:

Take a look at the chart below.

On this day, electricity consumption in one zone suddenly dropped by almost 50%.

The most interesting part: the day started normally. The deviation appeared around midday and continued for the rest of the day.

❓ Question #1

What do you think happened?

What could cause such a sharp and sustained reduction in electricity consumption within a few hours?

❓ Question #2

How would you predict such an event before it happens?

Which data would you use?

• Weather forecasts?
• Market data?
• Grid topology?
• Industrial activity indicators?
• Equipment health metrics?
• Something else?

💡 Bonus question

Could predictive maintenance data help forecasting?

Imagine that a transformer, feeder, or another critical asset showed signs of degradation several days before the event.

Could industrial diagnostics become an additional input for electricity consumption forecasting?

We're interested in hearing from:

• Students
• Data scientists
• Energy professionals
• Researchers

Share your hypothesis in the comments.

In a follow-up post, we'll reveal what actually happened and discuss whether the event could have been anticipated.

29/05/2026

🌡️🌦️⚡ Weather data engineering: parts of electricity consumption forecasting, one of the less visible, but very important.

At a-Gnostics, our forecasting platform Pro-gnostics does much more than simply “get a weather forecast”.

Behind every electricity consumption forecast, we operate a custom weather service designed specifically for energy forecasting tasks.

What makes it different:

we generate additional weather features from raw datasets before they are used in machine learning models;

for different regions, we predefine the most accurate provider. A forecast that performs well in one location may perform much worse in another;

we purchase weather forecasts from multiple providers instead of relying on a single source;

if data from a provider is delayed, corrupted, or temporarily unavailable, our system automatically performs data replacement and recovery to keep forecasting pipelines stable;

we store historical weather forecasts, not only actual weather observations. This is critical for understanding how forecast errors affected previous electricity demand predictions.

In practice, electricity consumption does not depend on “temperature” alone.

It depends on combinations, transitions, deviations, persistence effects, humidity interactions, wind impact, rapid weather changes, and many other hidden patterns inside the data.

For modern energy forecasting, weather infrastructure itself becomes part of the forecasting model.

If you would like to evaluate your current electricity consumption forecasts against a-Gnostics’ Pro-gnostics service and explore potential financial improvements, please contact our co-founders for a free trial

22/05/2026

🚢🌊⚙️ Case Study: Di-agnostics at an Offshore Vessel Near Singapore

The problem:
Monitor industrial equipment when there is no stable internet connection for months.
Offshore vessels operate in demanding conditions, where early detection of equipment issues is critical to avoid failures. Internet connectivity is often unavailable in mechanical compartments and limited during long voyages.

The solution:
Di-agnostics monitors equipment health and detects early signs of:
• Bearing defects;
• Rotor imbalance;
• Shaft misalignment;
• Mechanical looseness;
• Gear or coupling damage.

The case:
We are currently piloting Di-agnostics with an offshore company operating oil transfer vessels near Singapore and across regional Southeast Asian waters.

Depending on the equipment type, inspections are required every 1–7 days. During these operations:
📶 Internet access in engine and mechanical compartments is unavailable;
🚫 Connectivity during voyages is often unstable or highly limited.

Di-agnostics is designed to work fully offline, allowing engineers to:
✅ Calculate equipment Health Scores offline;
✅ Record equipment sounds offline;
✅ Create and manage equipment records offline.

When connectivity becomes available again, recorded data can be synchronized with cloud models, and Health Scores can be updated accordingly. If required, synchronization can be minimized, and Health Scores can remain calculated entirely in offline mode.

Result:
Di-agnostics enables continuous equipment health monitoring even in environments with limited or no internet access — supporting predictive maintenance far beyond onshore operations.

📱 The latest version is now available on the App Store (https://apps.apple.com/us/app/di-agnostics/id6466275467) and Google Play (https://play.google.com/store/apps/details?id=com.a_Gnostics_app), including offline Health Score functionality

11/05/2026

🌡️💨☀️: our sprint planning and technical discussion last week focused on the latest update to a-Gnostics' Weather Service, which we launched to production in late April.

The problem behind time-series forecasting seems simple:

“What forecast model is better?”

In practice, it becomes much more complicated.

We purchase 3–4 weather forecasts from different providers and need to decide which forecast should be used.

The obvious approach is straightforward: compare forecasts vs. actuals and select the most accurate one.

But then the real questions begin.

1️⃣ Is average error actually the best metric for electricity consumption forecasting?

What if Forecast 1 is more accurate during high-temperature events or peak daytime hours, while Forecast 2 has a lower average error overall?

2️⃣ What if forecast quality actually changes across the historical dataset?

Yesterday, Forecast 1 may have been the best. Two days ago, Forecast 3 performed better. One metric may work well in March, but not in February. Performance can also vary by season or weather regime.

3️⃣ What if different providers perform better in different regions?

Forecast 4 may work better for one PJM load zone, while Forecast 2 performs better somewhere in IESO.

The obvious answer is: use the best forecast for each location.

But when you manage hundreds of locations, automated forecast selection, monitoring, and maintenance become a serious engineering task.

🧠 Question we probably enjoy the most:

Can we automatically select the best weather forecast for electricity consumption forecasting using only forecasted features and feature-selection techniques?

Short conclusion:

a-Gnostics' Weather Service is far more complex than it may initially appear — and every production update requires careful planning, development, validation, and monitoring.

30/04/2026

⚡ a-Gnostics continues to expand market for electricity consumption forecasts in the U.S. 🇺🇸

Our product, Pro-gnostics, is now live across the PJM Interconnection, with paying customers in production.

Why PJM matters:

— 160+ GW peak demand;
— 65M+ people served across 13 states;
— ~800 TWh annual consumption;
— ~180 GW installed capacity.

This is one of the most complex electricity systems globally, where even small forecast deviations have real consequences:

— 1% forecast error ≈ 1.6 GW imbalance;
— Capacity prices recently reached $329/MW-day, highlighting volatility.

What we delivered:

— High-resolution forecasts across multiple PJM zones;
— ~98% average accuracy in production;
— Access via API and SaaS.

Instead of treating zones as uniform, we model localized demand behavior inside each zone, where weather and load patterns actually diverge.

👉 That’s where accuracy becomes impact.

If you're working with U.S. power markets — happy to provide a 1-month trial.

23/04/2026

One of our co-founders took part at the discussion “Ukraine’s Place in the New World,” an event was held in Kyiv focusing on Defense Tech and AI.

Panel discussion: the opportunities and obstacles for Ukraine’s entry into global markets for military technologies, artificial intelligence, and GovTech.

The event was initiated by the Kyiv Institute of National Interest together with the Pylyp Orlyk Foundation. The discussion aimed to outline Ukraine’s role in the emerging architecture of global security, where technology, the defense industry, and digital sovereignty are becoming key factors of influence.

Event program: one of two panel discussions covered the following topics:
— the role of artificial intelligence and issues of digital sovereignty;
— prospects for the development of Ukraine’s defense tech sector;
— Ukraine’s integration into global defense supply chains;
— opportunities and risks of arms exports.

The discussion served as a platform for a professional exchange on the strategic directions of Ukraine’s development amid the transformation of the global order, where the combination of defense technologies, innovation, and public policy defines new opportunities for the country. The topic of artificial intelligence is particularly relevant.

a-Gnostics

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