Model and optimise multi-energy systems in hours, not weeks.
For energy systems that don't fit a template: one optimisation engine across every energy carrier and every building, comparing thousands of technology and supply options on cost and CO₂.
Swiss-built · EU-hosted by default
A real Sympheny model of Gare-Lac, a new neighbourhood in Yverdon-les-Bains: heat, cooling and electricity optimised together for cost and CO₂.
Trusted by 70+ energy planners, utilities and engineering firms across Europe, the USA and beyond.
Proven from a single site to an entire city.
See all case studiesAt 20% lower lifecycle cost than the conventional reference design.
16 PV and energy-sharing scenarios compared in one project.
Pareto analysis showed a CO₂-free 2035 supply at the same life-cycle cost as 2018.
From building-level site data to a complete multi-energy concept.
Sympheny covers the whole planning job in one place: build a digital twin of the site, run the optimisation, compare scenarios, and hand decision-makers a result they can act on.
One model for all energy carriers
Model electricity, heat, cooling, gas, hydrogen, storage and mobility together, instead of as separate studies that never quite line up. Sector-coupling options and infrastructure constraints sit side by side, so you compare them on the same footing.
Plan at district scale.
Pull asset catalogues, hourly demand profiles, tariffs, GIS layers and meter data into a single model you can reuse. Go from one building to a 78-district city without rebuilding from scratch.
Outputs your stakeholders can actually read
Hourly demand profiles, load-duration curves, Sankey energy flows and Pareto cost/CO₂ comparisons, all generated from the same model and viewable directly in the app. Print to share, no rebuilding charts in slide decks.
It pays off quickly.
For most teams, the time Sympheny saves on data preparation and scenario modelling covers the annual licence cost within the first two projects.
Where the savings come from
Compare far more options
Engineers who used to compare two or three scenarios now evaluate dozens on cost, CO₂ and technical criteria.
Amstein+Walthert · Ronquoz21, Sion →Set up with AI, solved in minutes
Your AI assistant sets the scenarios up in minutes. Sympheny then solves them fast: WSP had six Pareto-optimal designs back in under ten minutes.
How AI setup works →Stress-test before you commit
A 90,000 MWh district network in Bern was tested against more than 30 future price and demand scenarios.
EWB · Insel-Holligen, Bern →The 60%+ and 1–2 project figures are Sympheny estimates based on typical project workflows. Actual savings vary with project complexity, input data quality and team experience.
“With Sympheny we've delivered client projects we otherwise wouldn't have taken on at all. From simple analyses to demanding calculations, everything runs in one tool. That simplifies our workflows and saves valuable time.”
Built for the organisations shaping local energy systems
Engineering & Consulting Teams
Engineers and project teams lose weeks wrangling scattered inputs into shape before they can build scenarios solid enough to put in front of a client.
Explore engineering workflowsUtilities & Energy Providers
Plan heat networks together with power, cooling, storage and tariffs, over investment horizons that run decades out, with scenarios solid enough to back a real infrastructure call.
Explore utility workflowsCities & Public-Sector Planners
Build energy strategies, district plans and the reporting that goes with them, on a process that survives public-sector timelines and the people you have to bring along.
Explore public-sector planningDevelopers & Industrial Sites
Weigh site energy concepts on CAPEX, OPEX, CO₂, grid constraints and phasing before you commit to the big infrastructure spend.
Explore site planning workflowsRigour, usability, and proof in the same platform.
A concept only holds up if three things are true at once: the maths is sound, engineers will actually use the tool, and the output survives the meeting where a client picks it apart. That's the bar we built Sympheny to clear.
Calculations run on a deterministic MILP engine. It's pure maths, there is no AI used for optimisation. Clustering groups your data without learning from it, and no model is ever trained.
Every scenario is compared on the same cost and CO₂ basis, with sensitivity runs as scenario variants, batch-built from Excel or the API. When a client picks the concept apart, the assumptions hold up.
Commercially deployed since 2020, with 70+ customers and real-world references across districts, campuses, utilities, industrial sites, and policy scenarios. Includes the Nanoverbund thermal micro-grid in Basel, recipient of the Watt d'Or Prize 2025 from the Swiss Federal Office of Energy.
Nothing is pre-selected. Sympheny weighs every candidate you include on its merits and hands you the mix that hits your cost and carbon targets. No supplier is favoured.
“In the Uster city centre I compared three networking options: no network, an anergy network, and one with additional electricity trading. The result was clear — maximum thermal and electrical networking is the best solution, economically and ecologically. I couldn't have run a variant comparison at this depth without Sympheny.”
Ready to deliver energy concepts faster, with more scenarios and clearer trade-offs?
See how much faster your team can build and compare scenarios.
From a first feasibility concept to a full client portfolio: three tiers built around how energy planning teams actually work. See pricing