Protect your collection.
And the planet.
Without choosing.
Your collection environment is one of the most energy-intensive spaces in any building: expensive to maintain, carbon-heavy, and often running harder than preservation science requires. Now you can find the optimal balance, with the data to back every decision.
Stay in the loopClimate control is the largest single source of carbon emissions in cultural institutions.1
Institutions can reduce energy use by up to 50% by broadening environmental setpoints without compromising their collections.2
1 New Buildings Institute and Environment & Culture Partners, Culture Over Carbon (2023). 2 Getty Conservation Institute, Managing Collection Environments: Technical Notes and Guidance (2023).
The challenge
Maintaining these environments costs more than it needs to
Without models that show where the energy efficiencies actually are without compromising preservation, institutions default to being overcautious. This results in mechanical systems running hard to maintain temperature and humidity ranges that are narrower than preservation science requires, which is expensive, carbon-intensive, and sometimes counterproductive. Incorrect climate can be a major risk to collections and can cause irreversible chemical and physical damage over time. Built by a team that includes conservators, Conserv draws on risk models developed by conservation scientists — grounded in the same preservation science used by leading institutions worldwide.
Rising energy costs
Climate systems are one of the largest and fastest-growing line items in institutional budgets. The pressure to find savings is real, and it is intensifying every year.
Carbon-intensive operations
Funders, boards, and communities expect progress on sustainability. Collection environments are a significant source of emissions, and a meaningful place to start.
Systems working against themselves
Narrow setpoint bands create compounding mechanical strain. Systems overshoot corrections, heating and cooling run simultaneously, and wear accumulates. The result is higher energy use and less stable conditions than a more flexible strategy would produce.
Microclimates you cannot see
Sensors placed in ductwork measure what the HVAC system produces, not what your collections actually experience. Localized hot spots, humidity pockets, and airflow dead zones can create conditions for mold growth or accelerated corrosion that never appear in mechanical system data. Reducing energy use without eyes on the collection space is not a safe experiment.
How it works
A living model of your building, grounded in preservation science
Conserv ClimateSmart brings together three sources of data that have never been combined in one platform. The result is a digital twin of your building that shows you where efficiency gains are possible, and where they are not.
Your building data
Start with sensors placed directly in your collection spaces, not just in ductwork or mechanical rooms. What the HVAC system delivers and what your objects actually experience can be meaningfully different, and only collection-level data captures that gap.
Preservation science
Every recommendation is filtered through materials-based preservation risk research developed by conservation scientists, reflecting what your specific collection type can actually tolerate rather than generic guidelines. Temperature swings cause wood and panel paintings to crack; sustained high humidity promotes mold and corrosion; low humidity makes organic materials brittle. The model knows the difference.
Energy economics
The platform factors in real utility costs so you can see what each degree of setpoint flexibility is worth in dollars and carbon, giving every decision a clear, quantified case. This lets you pursue savings where the science says it is safe, and hold the line where it is not.
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What you can do
From data to decisions
A suite of tools designed around how collections professionals actually work: analyzing risk, running experiments, making the case for change, and preparing for what might go wrong.
Scenario planning
Model how your building performs under different conditions before committing to a change or facing an emergency. Run "what if" scenarios without real-world risk.
Experiment runner
Test setpoint changes in a controlled, data-backed way. Track how your environment responds in real time, with preservation risk monitored throughout.
Advocacy reports
Generate reports that make the case to leadership, facilities teams, funders, and boards. Data-backed and written in plain language, ready to share without additional work.
Enhanced energy monitoring
Add sensors for higher-resolution energy data across zones, wings, or mechanical systems. No new infrastructure or IT involvement required. Greater granularity lets the model pinpoint exactly where inefficiencies live.
Expert consultations
Connect with HVAC specialists and conservation professionals who have spent years helping institutions identify inefficiencies and improve collection environments. Get guidance grounded in decades of field experience, applied directly to your building and collection type.
Common questions
What people ask us
What energy data do you need to get started?
Utility billing data is enough to begin. Monthly invoices give the model what it needs for cost and carbon calculations. Sub-meter or interval data improves precision, but it is not required. If you want more granularity and do not have it yet, energy monitoring sensors can be added to capture data at the zone or system level.
Do we need new hardware or sensors?
Not if you already have real-time environmental sensors installed in your collection spaces. Your existing sensor data feeds directly into the model. If you use other hardware that automatically collects environmental data, we can work with that too.
Can we safely reduce energy use without sensors in our collection spaces?
Not reliably. Sensors in ductwork or mechanical rooms tell you what the HVAC system is doing, not what your collections are experiencing. Microclimates can develop in corners, display cases, or storage areas that never register at the mechanical level. Mold, corrosion, and dimensional changes in materials can begin in conditions that look fine on a building management system. ClimateSmart is built around collection-level sensor data precisely because the decisions being made carry real preservation risk. Broadening setpoints without that visibility trades one problem for another.
Is this using ChatGPT or generative AI?
No. ClimateSmart uses physics-based preservation models and traditional machine learning, not large language models. The models are built on decades of conservation science and improve over time as your building's real sensor data flows in. There is no AI generating text, summaries, or recommendations from a general-purpose language model.
How does the model improve over time?
As your sensors continue logging real conditions, the digital twin becomes more accurate to your specific building. Seasonal patterns, unusual events, and HVAC behavior all get incorporated, so scenario predictions get sharper the longer you use it.
Who owns the data?
You do. Your environmental data is yours. It is used only to build and refine the model for your institution, not shared with other organizations or used to train shared models.
Be part of building the future of collections stewardship
We are working with a small group of institutions to shape and refine the model. If your institution is actively collecting environmental data and interested in exploring energy efficiency, we would like to keep you in the loop.
- ✓ Early access to the ClimateSmart platform
- ✓ Input into the feature roadmap
- ✓ Updates as we release new capabilities
- ✓ No commitment required to stay in the loop
Keep me in the loop