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a-Gnostics

a-Gnostics

Information Technology & Services

Kyiv, Kyiv 164 followers

a-Gnostics | AI-Powered Predictions for Energy & Industry — Pro-gnostics & Di-agnostics

About us

a-Gnostics delivers AI-powered predictive analytics for the energy sector and industry. 📈 Pro-gnostics: SaaS platform delivering electricity consumption forecasts with 98%+ accuracy. Used by energy traders, utilities, and demand response providers to optimize trading, anticipate demand, and improve reliability across North America and beyond. 🏭 Di-agnostics: The “Shazam for industrial equipment.” A mobile app that detects potential machinery failures from sound, helping reduce downtime and maintenance costs. Founded as an Industry 4.0 subsidiary of SoftElegance (est. 1993), a-Gnostics blends decades of software engineering with cutting-edge AI. Since presenting at Databricks Spark Summit Brussels 2016, we’ve focused on turning data into actionable intelligence. 🏆 Throughout our journey, we’ve joined top energy accelerators, earned prizes and honors, gained media recognition — and in 2024 won First Prize & Best Solution from Kyiv City Government. Several paid enterprise customers.

Website
http://www.a-gnostics.com
Industry
Information Technology & Services
Company size
11-50 employees
Headquarters
Kyiv, Kyiv
Type
Privately Held
Founded
2016
Specialties
Data Science, Artificial Intelligence, Predictive Analytics, Machine Learning, Forecasts, and Failure Prediction

Locations

Employees at a-Gnostics

Updates

  • Great work of entire team. Our forecasts at 🇺🇸 PJM: 65M+ people across 13 states, 160+ GW peak demand. Special thanks to our CTO, Yaroslav Nedashkovskyi

    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. #Energy #PJM #AI #Infrastructure #GridReliability #Utilities #Forecasting

    • USA, PJM, a-Gnostics
  • One of our co-founders, Andrii Starzhynskyi 👷♀️👂🏿🏭, 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. #AI #PanelDiscussion #Ukraine

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  • No connectivity — but no downtime: offline diagnostics for industrial equipment. Industrial environments are not built around perfect connectivity. Basements, remote sites, high-interference zones, exactly where critical equipment operates and are often the least connected. This creates a real operational gap: diagnostics delayed or skipped due to lack of signal. Di-agnostics removes that dependency. With Di-agnostics, engineers can: — record equipment sound directly on-site, without connectivity; — register new equipment during inspection; — continue diagnostics workflows without network availability. Once connectivity is restored, all recorded data is automatically synchronized and enriched with detailed analytics and Health Score calculation. This matters for equipment health monitoring engineers: — no missed inspection cycles: workflows are independent of network conditions; — higher data fidelity: data is captured at the source, in real conditions; — operational continuity: diagnostics reflects how industrial sites actually operate. Reduced latency to insight, issues are captured on site, not deferred. In practice, it means fewer blind spots, earlier anomaly detection, and more reliable asset management. We are already moving toward edge analytics and bringing intelligence directly onto the device, so even analysis won’t depend on connectivity. Because in industrial environments, reliability isn’t a feature — it’s a requirement. Download Di-agnostics app at: iOS: https://lnkd.in/dzcuqaDj Android: https://lnkd.in/dAx84GbC

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  • a-Gnostics welcome's Uliana Мelnychuk, based in Stockholm, Sweden, as a Data Scientist. She works on time-series models for electricity consumption, contributing to our 400+ daily forecasts. Her focus includes expansion and coverage of PJM market zones, in the U.S.

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  • What do energy traders and industrial operators actually gain from a-Gnostics version 4? Introducing a-Gnostics Chapter IV: not another generic AI model — but two specialized systems designed to operate under real-world constraints: - decisions must be made before 9 AM; - forecasts must be reliable across hundreds of zones; - models must adapt to local, non-stationary behavior; - equipment issues must be detected before failure, without complex hardware. This is exactly where most “AI platforms” fail. With a-Gnostics, customers get: 1. Operational certainty at scale — powered by Pro-gnostics 400+ electricity consumption forecasts generated daily and delivered on time, across markets like IESO, MISO, PJM, and Ukraine ready for use in trading and planning workflows. Pro-gnostics is not a single model, but a distributed forecasting system operating under strict time constraints. It delivers higher forecast accuracy through specialization. Instead of one global model, Pro-gnostics builds a dedicated model for each forecast, tuned daily using: - feature selection for each zone of forecast if needed; - localized consumption patterns; - weather dependencies and custom features. This transforms Pro-gnostics into a large-scale daily optimization engine, not a static ML pipeline. 2. Industrial sounds analytics recorded in offline mode — powered by Di-agnostics Di-agnostics operates on sound as a primary signal, enabling:  - non-invasive diagnostics;  - applicability in environments where traditional sensors are limited, unavailable, extremely costly, or NO internet connection. We continue working on Equipment Health Score:  - a normalized indicator of current condition;  - designed for intuitive interpretation in operational contexts and equipment;  - suitable for integration into maintenance workflows. In Di-agnostics we are focused on extracting actionable intelligence from unconventional data sources, where the main is sound. It introduces a new diagnostic modality, enabling non-invasive, scalable condition monitoring. Industrial AI systems should not generalize prematurely — they should specialize, adapt, and evolve continuously. Feel free to connect to if you are ready to revolutionize your energy and equipment management. #ElectricityConsumptionForecasts #IndustrialSound #FailurePrediction

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  • Our co-founder with the presentation "Industrial Equipment Failure Prediction Using Its Sound", for utility providers: Electricity, Water, and Gas, this approach delivers the following value: — Early detection of transformer faults; — Monitoring of electric motors in critical systems; — Failure prediction for pumps and rotating equipment.

    Ukraine Smart Cities & Technology Forum. My presentation "Industrial Equipment Failure Prediction Using Its Sound". The Smart Building Forum 2026, a key event for Ukraine's smart city technology and reconstruction, focusing on innovative, energy-efficient, and sustainable urban infrastructure. It acts as a major platform for technology integration and restoration efforts, connecting government representatives, municipalities, developers, and tech innovators. My presentation, “Industrial Equipment Failure Prediction Using Its Sound,” focused on a practical challenge faced by modern cities: how to move from reactive maintenance to predictive, data-driven operations. With the huge support from all our team, Andriy Stolbov, Yaroslav Nedashkovskyi. During my session, I introduced the core capabilities of Di-agnostics — our acoustic-based solution for early detection of equipment degradation. By analyzing sound patterns, the system identifies anomalies before they evolve into failures, enabling timely intervention without intrusive sensors or complex installations. For city-level operators and utility providers: Electricity, Water, and Gas, this approach delivers the following value: — Early detection of transformer faults; — Monitoring of electric motors in critical systems; — Failure prediction for pumps and rotating equipment. The result is reduced downtime, lower maintenance costs, and improved reliability of essential services. As cities continue to modernize and rebuild, integrating predictive technologies like this will be a key enabler of smarter, more resilient infrastructure. Happy to connect with anyone interested in applying predictive maintenance in urban systems.

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  • Our CEO and co-founder participated at Ukraine-Denmark Business Relationship and Investment Forum, 🇺🇦 🇩🇰. About 100 people come to Kyiv to discuss energy, recovery, military technologies and more

    Ukraine–Denmark Business & Investment Forum. 🇩🇰 🇺🇦 held in Kyiv, the forum gathered around 400 participants, including around 100 representatives of Danish businesses. The key focus areas were energy, recovery, and military technologies — sectors that are critically important for Ukraine’s resilience and long-term reconstruction. I would like to express my sincere gratitude to Denmark — its businesses and its people — for the consistent support provided to Ukraine. For the Danish model of military support. For Maersk-scale global logistics and for LEGO-level precision in engineering. For Danish croissants, Danish girl, for leadership in wind energy and energy efficiency. For Danish design — where simplicity meets functionality, and that distinctive Scandinavian sense of calm determination. Strong partnerships create strong futures.

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  • a-Gnostics at REСТАРТ conference with the booth; we've presented two our products: Di-agnostics — 'Shazam for industrial equipment', utilizing the sounds emitted by machinery and mobile application to predict potential failures. Pro-gnostics, SaaS platform delivering electricity consumption forecasts with over 98% accuracy

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  • a-Gnostics reposted this

    9 Years of a-Gnostics 🎉 We chose October 28, 2016 — the day after our presentation at the Databricks Spark Summit Brussels, as the official founding date. We could have picked other milestones instead: 2019 — when we first started getting paid for our product; 2018 — when we graduated from the excellent Radar Tech Energy Accelerator program; 2017 — when we reached the finals of the Industry 4.0 competition in San Sebastián; or even 2011 — when we first began working together at a software export company. I’d like to recall the story of how we managed to get a slot to speak at that conference in Brussels, what happened afterward — and what lies ahead. At that time, we were working on projects for U.S. clients related to industrial and business process automation, but we dreamed of creating our own product that would leverage mathematics and big data. We built several MVPs, but they didn’t yet solve a specific problem that customers were willing to pay for. We were developing a framework for processing large volumes of industrial data that was supposed to deliver practical insights. In 2016, we prepared a talk titled “Spark — Universal Computation Engine for Processing Oil Industry Data.” Looking back at that presentation now, I can see we were already touching on our core topic — predicting industrial equipment failures through data analysis. It’s a global problem, large enough to be a startup, yet each type of equipment requires its own specific data and models. Today, we can confidently call ourselves a Deep Tech Startup. For the conference, we focused on rod pumps on drilling platforms and data from dynamometers. We built our own synthetic data generator and applied a model from a scientific paper. The physical problem we studied was corrosion. At the time, it seemed that a solution capable of detecting anomalies in equipment operation was already ready for industrial use. Now we understand that was only the first step toward a deeper understanding of processes and real value creation. Years passed. We built a SaaS solution for forecasting electricity consumption with 98% accuracy, which genuinely saves money. It’s now used in Ukraine and Canada, and we are scaling to the United States. As for equipment diagnostics, by 2025 customers expect to see not just potential deviations, but also the actual operational condition in specific numbers, the probability of failure, a clear explanation of the cause, and ways to fix it. Our journey has already lasted more than nine years. It’s just a formal date, but a good reason to reflect on the exploration and technical work that shaped us — the pilot projects that helped us improve and still await further implementation. We keep going — with more ideas to bring to production and many enterprise customers

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  • Awarded first place in the Kyiv City Government competition, almost a year ago. Our product Di-agnostics, “Shazam for industrial equipment”, was recognized as the best solution. Last week, our Co-founder Andrii Starzhynskyi 👷♀️👂🏿🏭 had the chance to return to the Kyiv City Council as a guest speaker at the Industrial & Innovation Hackathon, participating in a panel discussion on the implementation of AI solutions in industry and their impact on real business operations

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