Ask your buildings anything
Kaiterra AI turns your indoor environmental quality data into answers. Ask a question in your own words, and get a clear response from your own devices. No dashboards to learn. No spreadsheets to export.
You have the data. Getting answers shouldn’t be this hard.
You have the data. Getting answers shouldn’t be this hard.
Prefer to work inside your own AI tools? Bring Kaiterra data into Claude, ChatGPT, Gemini, Cursor, and more.
Closing the loop for building performance, simply by chatting
Understand, diagnose, report, and share, all in a single conversation. Issues get resolved faster, your team gets support, and occupant experience improves.
See Kaiterra AI in action
You don't have to toggle filters and tabs to know your air quality. Just ask, in your own words. Ask about one room or your whole portfolio at once, run deep analysis and diagnostics, check certification compliance, and more.
CO₂ peaked at 1,480 ppm around 7:40 PM in Conference Room B.
An after-hours all-hands ran ~90 min past the HVAC schedule; ventilation had already ramped down for the night.
Your air quality is genuinely strong and on track for WELL. Here's the realistic WELL projection:
Preconditions — all 4 should pass:
Optimization points — projected 7 of 7:
Here's the monthly IAQ summary built from your 30-day portfolio data:
Monthly IAQ Summary — July 2026 Portfolio
Headline: 3 buildings have persistent, multi-metric failures that need attention this month; 4 buildings are performing at or near excellent across all parameters.
30-Day Performance Stack Rank
| Building | Air Quality % | Thermal Comfort % | CO₂ % Excellent | PM2.5 % Excellent | TVOC % Excellent | Temp % Comfortable | Humidity % Comfortable | Priority |
|---|---|---|---|---|---|---|---|---|
| Courtyard 3 Connector | 53% | 0% | 80% | 25% | 0% | 0% | 0% | Investigate all metrics |
| Lejo House | 67% | 2% | 100% | 1% | 100% | 0%100% too warm | 4%96% too humid | Thermal + PM2.5 failure |
| Josh Test | 59% | 69% | 88% | 15% | 74% | 59% | 79% | PM2.5 & temp needs attention |
| Andu's US Test Building | 70% | 69% | 95% | 30% | 86% | 38%62% too warm | 100% | Overheating + PM2.5 |
| Kyle's Home | 67% | 100% | 0% | 100% | 100% | 100% | 100% | CO₂ sensor data gap |
| Haywood | 94% | 66% | 100% | 96% | 87% | 49% | 83% | Temperature running warm |
41 of 43 devices are healthy. 2 on Floor 3 dropped below −85 dBm.
The weak devices are clustered near a recently relocated partition wall — likely blocking line of sight to the gateway.
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Built to understand your building.
See Kaiterra AI in action
See what you can ask.
Real questions from real people. Tap any tile to see how Kaiterra AI answers it.
Less time clicking.
More time deciding.
Getting an answer used to take multiple clicks. Now you just ask, and spend your time deciding what to do instead of hunting for the right chart.
Charts, talking points, and slides come out ready to drop into your report or deck. No more manual screenshotting.
Stay ahead of the changes that matter. Problems surface, get explained, and get addressed before they become complaints.
Your AI sees exactly what you see. Nothing more, nothing less.
Kaiterra AI doesn't get special access to your data. It gets your access. Every question is answered using your own login session, governed by the same role-based permissions as the rest of your Kaiterra data platform. If you can't see a building, neither can the AI.
Frequently asked questions
Kaiterra AI is reliable for the questions it's built to answer: diagnostics, reporting, compliance checks, and event investigations against your own data. Every answer cites the underlying data points and the calculation behind them, so you can verify before acting.
