First, it determines what the data can support
Data may come from a meter, CT, sub-meter or compatible equipment. Sampling rate, load type and sensor quality determine what can be detected and at what confidence.
Building B demo scenario · 15-minute intervals synthetic data for product explanation
KAP, the intelligent layer for electricity use.
From meter data to an actionable decision.
KAP turns meter and sensor data into monitoring, alerts, analysis and practical reduction recommendations. Automated control is enabled only after site validation, compatible hardware and explicit authorization.
AvailableMonitoring · analysis · alerts · recommendations
RoadmapConditional manual and automatic control
Sample analysis output
3signals
Review required
+4.1 kW
Abnormal base-load increase · operator review required
Alert
1.7 kW
Lighting outside operating hours · suggested alert
Recommendation ready
-2.3 kW
Server cooling · load-shift recommendation prepared
This chart is a synthetic demonstration scenario created to explain the product workflow; it is not customer data or a performance claim.
DEMO SCENARIO · 21:00
The building is empty.
The demand curve is not.
This is a synthetic scenario. Lighting, cooling and standby loads remain visible after operating hours. KAP first establishes whether the pattern is expected, anomalous or simply missing operational context.
0candidate circuits
0estimated kWh reduction capacity
0estimated kg CO₂
Keep scrolling
Decision simulation: real switching requires compatible equipment, safety logic and authorized approval.
Decision architecture
Three layers, from measurement to an auditable recommendation.
KAP checks data quality, estimates baselines and anomalies, and reports confidence. No estimate is presented as certain and no command is executed without authorization.
It turns patterns into baselines, alerts and scenarios
Consumption history, operating schedules, weather and tariffs can enter the model. The analysis interval and forecast horizon are configured to the site data.
It recommends; control requires permission and safety logic
The current phase delivers reports, alerts and recommendations. Manual or automatic control is a later capability with compatible equipment, logging, override and fail-safe behavior.
Observe and explain
Monitoring, baseline analysis, peak and anomaly alerts, reports and actionable recommendations without autonomous switching.
Connect and approve
Connection to compatible meters, CTs or actuators; manual commands and supervised control after site-level safety validation.
Automate conditionally
Edge intelligence and conditional automation with fail-safe logic, audit trails, access control and manual override.
One engine, different operating realities
A workshop does not waste electricity the way a home does.
The analysis model and pilot scope are configured to the site. Choose a context:
Find the load that never sleeps
KAP builds a baseline, flags persistent night consumption and turns recurring patterns into a reviewable recommendation. Device-level labels are shown only when confidence is sufficient.
- Base-load review — finds consumption that persists outside normal use
- Tariff timing — identifies loads that may be shifted after user approval
- Bill trajectory — estimates where the period is heading from current behavior
Pilot analysis priority
MONITOR
Current delivery: monitoring, analysis and recommendations
A measurable pilot
Before promising savings, we define the baseline and the success criteria.
0Initial monitoring days
0Analytical deliverables
0Decision maturity levels
0Auditable final report
These figures describe the proposed pilot structure, not achieved savings. Any reduction percentage is published only after a documented baseline, operating conditions and an agreed M&V method.
Technical notes
Clear about what the technology can — and cannot — prove.
From meter data to an actionable recommendation
The complete path from sensing and data-quality checks to baselines, anomaly detection, confidence scoring and a recommendation an operator can review.
What load signatures can identify — and where they fail
Detection quality depends on sampling rate, sensor quality, similar loads and simultaneous events. KAP reports confidence instead of presenting every estimate as a fact.
A dashboard is not a verified saving
The pilot defines a baseline, operating conditions, exclusions and an M&V method before any reduction or payback claim is made.
Company
Kara Pardazan Smart Energy
We are building KAP as a practical intelligence layer between electricity data and operational decisions. The goal is not another dashboard; it is a measurable, safe and gradually automatable process for reducing waste.
Evidence before claims
Human approval before control
Local-first architecture where required
Start with one clear problem
Introduce one site; first, we will determine what needs to be measured.
No pre-set percentage promise; we review the data, baseline and constraints first.
Start with the site, not a sales pitch
Tell us what is connected and what you need to prove.
Share the site type, operating hours, available meter or CT data and the main concern. The initial response will define the first measurement step and the limits to validate.
- Project phone
- +982191091013
- Response target
- Within one business day