Grydnova
Grydnova is an AI-assisted target grid planning tool for electricity distribution network operators and municipal utilities. It builds a computable digital twin from GIS data, runs load-flow simulations and forecasts local demand growth to prioritise cost-efficient network reinforcement.
What is Grydnova?
Grydnova is an AI-assisted planning tool for electricity distribution grids, published by OmegaLambdaTec GmbH of Garching near Munich; the site carries the line by OmegaLambdaTec throughout. It addresses one audience precisely: distribution network operators and municipal utilities facing rising electrification, decentralised generation, volatile photovoltaic feed-in, bidirectional flows and, above all, a lack of visibility in the low-voltage grid.
The product is organised in two modules. The base module, Digital Twinning, turns GIS, operational and consumption data into a georeferenced, topologically correct and computable network model. It checks that data automatically, plausibility-tests it, corrects inconsistencies and structures the grid into calculable sub-networks with all relevant components. The planning module, AI-supported grid planning, then identifies present and future bottlenecks on realistic load flows, produces locally resolved demand and feed-in forecasts for solar PV, electric mobility and heat pumps, and turns them into a scenario-based footing for prioritised, cost-optimised measures.
The published technical envelope is unusually specific. Forecasts are resolved down to the individual house connection and run out to 2050. Scenarios simulate load and feed-in in 15-minute resolution for up to a full year, with risk and impact analysis. Coverage is stated for low and medium voltage, with a claim of visibility across all voltage levels. Outputs include capacity and risk maps, calibrated load-flow status reports listing limit violations with prioritised measures, and network models exportable in Shape and CSV for reuse in SCADA or MDM projects. The regulatory frame the vendor targets is German target grid planning under §14d EnWG — that is the subject matter of the software, not a certification held by the publisher.
How it is delivered matters as much as what it does. The vendor explicitly contrasts Grydnova with an isolated software tool and sells it as an expert-guided project, running from a quality check of the customer's data foundation through to a simulation-based decision basis. The application is developed continuously with network operators, and the product was launched in 2025. Nowhere, however, does the site describe how users technically access it.
What it does
- Build a computable, georeferenced digital twin of a low- and medium-voltage distribution grid
- Run physically accurate load-flow calculations and expose capacity bottlenecks and limit violations
- Forecast local demand and feed-in growth for solar PV, electric mobility and heat pumps
- Simulate load and generation scenarios in 15-minute resolution for up to a full year, out to 2050
- Check, plausibility-test and correct inconsistencies in heterogeneous input data automatically
- Prioritise and cost network reinforcement measures on a scenario-based footing
- Export the network model in Shape and CSV for reuse in SCADA or MDM projects
When to use Grydnova / When not to
A quick filter to help you decide if Grydnova is the right fit.
When to use Grydnova
- Distribution network operators planning low- and medium-voltage reinforcement under regulatory and budget pressure
- Municipal utilities that hold GIS, operational and consumption data but have no in-house data science team
- Grid planning engineers who need a computable, exportable network model rather than one-off external studies
- Teams preparing target grid planning documentation in line with Germany's §14d EnWG requirements
- Investment planners who must justify and prioritise capital expenditure on the distribution grid
When not to use Grydnova
- Buyers who need a published price list, as nothing is quoted publicly and every engagement starts with a sales conversation
- Organisations wanting self-service software, since the vendor explicitly positions Grydnova as an expert-guided project rather than a standalone tool
- Teams looking to replace their existing operational load-flow tools, a question the vendor's own FAQ raises without publishing an answer
- Non-German-speaking teams, as the entire site and all product material are in German only
- Developers expecting an API, a mobile app or a browser extension, none of which the vendor offers
How to use Grydnova
A typical end-to-end flow, from setup to results.
- Request a demo through the demo form to obtain access to a video tutorial, or book an individual appointment through the contact page
- Discuss scope with the vendor, which offers to show the network model, typical bottleneck maps and a sample scenario simulation
- Provide the GIS, operational and consumption data that describe your distribution grid
- Let the vendor run a quality check on that data foundation before any modelling begins
- Have the data checked, plausibility-tested and corrected automatically, then structured into calculable sub-networks
- Obtain the georeferenced digital twin of the network as the computational basis
- Run load-flow analysis on the current state to reveal limit violations and capacity bottlenecks
- Apply the AI development models for solar PV, electric mobility and heat pump ramp-up out to 2050
- Simulate load and feed-in scenarios with risk and impact analysis, then prioritise measures
- Export the resulting network model in Shape or CSV for reuse in SCADA or MDM projects
Pros & Cons
Pros
- Fully verifiable legal identity: the Impressum gives the commercial register entry HRB 216948 at the Munich register court, VAT number DE299376629 and a named managing director
- Precise, quantified technical scope rather than adjectives: 15-minute resolution, a 2050 horizon, house-connection granularity, low and medium voltage
- The network model is exportable in Shape and CSV, which limits proprietary lock-in
- Explicit regulatory anchoring to §14d EnWG target grid planning
- A named customer reference with an attributed quote, from Netzgesellschaft Niederrhein
- Expert guidance is part of the offer, which suits utilities without in-house data scientists
- A no-commitment demo is available through a simple form
Cons
- No public pricing of any kind: not a figure, not a range, not a rate card anywhere on the site
- No terms and conditions are published, so contractual terms cannot be reviewed before contact
- The privacy notice covers website visitors only and says nothing about how customer grid data is processed
- Nothing is published on hosting location, retention periods, subprocessors, a data processing agreement or model training
- The site displays four FAQ questions but never serves their answers
- Several pages are unedited templates or empty, and the online booking page states there is nothing to book
- German only, with no API, no mobile app and no description of how the product is technically accessed
Pricing & Plans
No pricing is published. An exhaustive search across every page of the site, in both the rendered text and the underlying HTML, returned no amount, no currency and no billing period. Grydnova is sold on a quotation basis, the commercial entry points being a demo request or an individual appointment. The vendor advertises neither a permanent free plan nor a free trial, and does not state that either is unavailable, so both remain undetermined. The online booking page states that there is currently nothing to book. Prospective buyers should expect a scoped quotation rather than a rate card.
Data, GDPR & hosting
A consolidated view of how Grydnova handles your data.
GDPR overview
Implementation is visible but partial. The publisher is a German company and its privacy notice follows the expected pattern: OmegaLambdaTec GmbH is named as the controller with its Garching address and telephone number, and the notice sets out the rights of access, rectification, blocking, erasure, restriction of processing and data portability, the right to withdraw consent at any time, the Article 21(1) and 21(2) objection rights including direct marketing, and the right to lodge a complaint with a supervisory authority. Technical cookies rely on Article 6(1)(f). No data protection officer is named and no Article 27 representative is designated, which is expected for a controller established in Germany. The critical gap: the notice covers website visitors only. Nothing describes how the software processes customer grid data, and the notice carries no effective date or version.
Who owns the data?
No terms and conditions are published anywhere on the site, so contractual data ownership is simply not knowable before contact. The privacy notice names OmegaLambdaTec GmbH as the controller, but it addresses website visitors only: form entries and technical browsing data. It says nothing about the GIS, operational and consumption data a customer would hand over to build the digital twin, nor about who may use that data or for what purpose. The single reversibility signal the vendor publishes is that the resulting network model is exportable in Shape and CSV formats. Everything else about ownership has to be settled contractually.
Reuse rights
For website data the stated purposes are narrow: delivering the site without errors and analysing visitor behaviour, with technical cookies resting on the legitimate-interest basis of Article 6(1)(f) GDPR. The vendor states that server log data is not merged with other sources. For customer data there is no published position at all — no clause describes secondary use, resale, benchmarking or model training. Customers can reuse their own outputs in a practical sense, since network models are exportable in Shape and CSV for reuse in SCADA or MDM projects, but no licence terms govern that reuse because the site publishes no terms of service.
Data retention & training
Hosting summary
No hosting jurisdiction is disclosed, for the website or for the product. The privacy notice and the cookie page describe what data is collected from site visitors but never say where it is processed or stored, and there is no mention of transfers outside the European Union, standard contractual clauses or named subprocessors. What can be observed technically concerns the marketing site alone: it is built and served on Wix infrastructure, and the domain resolves to an address geolocated in the United States that the collection tooling flags as anycast — a content delivery node, not a processing location. Neither fact should be read as a statement about where a customer's grid data would be held. Since the publisher is a German company acting as controller under the GDPR, an EU processing location is a reasonable expectation, but it is an expectation and not a published commitment. Any utility handing over GIS, operational and consumption records describing critical infrastructure should establish hosting location, subprocessors and transfer safeguards contractually, because the site provides none of them.
Things to keep in mind
Risks and trade-offs to weigh before adopting Grydnova.
- The publisher's own pages give two incompatible savings figures for the same claim: over 30% on the product page and up to 90% on the investor page. Neither is independently verified
- Efficiency claims of this kind are vendor statements, not audited results, and grid reinforcement decisions built on them carry real capital consequences
- With no terms and conditions published, the contractual position on data ownership, liability and exit cannot be assessed before committing to a conversation
- The absence of any published statement on hosting, retention, subprocessors or model training means a utility must obtain all of it contractually, for data that describes critical infrastructure
- Forecasts to 2050 invite false precision: a 15-minute scenario is only as good as the assumptions behind photovoltaic, electric mobility and heat pump ramp-up, and those assumptions belong to the planner, not to the tool
- Delegating the modelling to an expert-guided project can hollow out in-house grid planning judgement over time, which is precisely the capacity a network operator needs to retain
- The regulatory framing is German and tied to §14d EnWG; the product's value outside Germany is not documented
Setup & Integrations
Technical difficulty
Low effort for the customer's own team, by design. Implementation is guided by the vendor's experts from the initial quality check of the data foundation through to the simulation-based decision basis, and the publisher explicitly targets utilities that lack the internal resources for this kind of analysis. Input data inconsistency is handled by the tool itself, through automated checking, plausibility testing and correction. The real prerequisite is data availability: GIS, operational and consumption records for the grid. One caveat — the site never describes how the product is technically accessed.
Behind Grydnova
Fundraising
Social
Resources
All the official URLs gathered for verification and reference.
Frequently asked questions
What exactly is Grydnova — software, consulting or a project?
Which voltage levels does Grydnova cover?
How much does Grydnova cost?
Does Grydnova offer an API?
Can I get my network model out of the tool?
In which languages is Grydnova available?
What does the vendor say about how my grid data is handled?
Who is behind Grydnova?
How do I get started?
Should you pick Grydnova?
Grydnova is a narrow, well-defined vertical product: AI-supported target grid planning for electricity distribution operators and municipal utilities. Within that scope it is credible. The technical envelope is stated in numbers rather than adjectives — 15-minute resolution, a 2050 horizon, forecasts down to the individual house connection, low and medium voltage — and the network model it produces is exportable in Shape and CSV, a meaningful concession against lock-in. The publisher's legal identity is fully verifiable, with a commercial register entry, a VAT number and a named managing director in the Impressum, and the product is backed by a named customer reference with an attributed quote.
The reservations concern documentation rather than substance. No price is published in any form. No terms and conditions exist on the site at all, so the contractual frame cannot be examined before contact. The privacy notice, though properly built for a German controller, covers website visitors only: how the software handles a utility's grid data — where it is hosted, how long it is kept, who else touches it, whether it feeds any model — is simply not addressed. Several pages of the site are unedited templates or empty, four FAQ questions are displayed without answers, and nowhere does the vendor say how users technically reach the product. The publisher's own pages also give two incompatible savings figures for the same claim.
The practical consequence is clear. This is a tool to evaluate through direct contact, not one to judge from its published material. A distribution network operator sitting on heterogeneous GIS and consumption data with no in-house analytics capacity has good reason to request the demo; anyone who needs to compare terms, prices or data-protection commitments on paper will have to obtain them privately first.
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