The SmartScore MQI framework
Complex data.
Clear performance.
Minedco’s framework turns complex measurements into explainable scores and comparisons, helping teams understand what changed and where to look next.
signal
See what drives the signal.
| Component | Example finding |
|---|---|
| Download speed | Strong |
| Responsiveness | Inconsistent |
| Connection stability | Needs attention |
A result needs context.
Compare the same place at different times to focus the investigation.
Understand what changed.
Use a view over time to see recurring patterns and where to look next.
Illustrative interface with fictional findings and relative trends. Not calculated MQI results.
SmartScore MQI, explained
What changed?
What deserves attention?
A short narrated film about the scoring layer, visual diagnostics, and human judgment behind SmartScore MQI.
Read the film transcript
SmartScore, a Mean Quality Index, helps make sense of complex performance data. A connection can look fast, yet a video call still breaks up. Speed alone cannot explain the experience. When your dashboard has dozens of measurements, how do you know what deserves attention? SmartScore adds a translation layer to your existing data. Each performance indicator is calibrated to meaningful quality thresholds, bringing different units into a consistent scoring language. Context matters. Measurements captured together stay together, so the score reflects the same event or collection cycle. With the same inputs and calibration, the scoring is repeatable. The AI does not invent the score. Now compare sites, devices, or time periods. Trends and visual diagnostics help reveal changes, outliers, and the indicators behind them. A headline result becomes something your team can investigate. The structured score and its supporting evidence give AI a clearer basis for reviewing performance and drafting an explanation. Your team reviews findings and approves consequential actions, including alerts, tickets, or calibration changes. Minedco works with you to calibrate the model, apply it to a representative dataset, and review the results. Start with a known example, so your team can judge the findings against an outcome it already understands. SmartScore. Complex data. Clear performance. Bring us the performance question. Let's explore a focused pilot.
Featured application / Environmental monitoring
See SmartScore
in action.
PR Health Index
PR Health Index applies the SmartScore MQI framework to river monitoring, bringing results from multiple sources into a clear view of conditions, history, and patterns.
Created by Minedco, the application brings sampling information from Potomac Riverkeeper Network (PRKN) and other public sources into one view, with source information and collection dates kept visible.
The framework provides the structure. Water-specific index definitions give this application its meaning. Explore the map, the legend, and a historical rainfall example to see how that works in practice.
Performance, explained
Turn complex KPIs into
one clear performance signal.
Bring structure to the measurements, compare results in context, and keep the evidence behind the score visible.
Translate
Normalize multiple metrics into an understandable scoring framework with a defined basis for interpretation.
Compare
Use cohorts, locations, and time periods to understand differences and identify what deserves attention.
Review
Use AI to help interpret patterns while people review findings and approve consequential actions.
Many measurements. One clearer picture.
Fast internet.
Frustrating calls.
What’s missing?
Download speed tells only part of the story. SmartScore MQI brings multiple measurements into an understandable performance score, with visibility into what drives it.
AI can add context from support tickets and user feedback, helping teams connect measured performance with the experience people describe.
Discuss your use caseFast downloads.
Calls still freeze.
A clear performance view brings the missing context into focus.
- Download speed
- Strong
- Responsiveness
- Inconsistent
- Connection stability
- Needs attention
“Our video calls keep freezing in the afternoon.”Fictional employee feedback
Investigate afternoon connection stability. Speed alone does not explain the reported experience.
An edge deployment concept
Understand locally.
Escalate intelligently.
SmartScore MQI could give a small, general-purpose language model a consistent signal to interpret close to your devices. Keep routine analysis local and send concise evidence to the core when broader investigation is needed.
- 01 / AT THE EDGE
Measure & score.
Calculate MQI from local measurements and track changes over time.
- 02 / LOCAL AI
Add context.
Interpret scores, local history, and available feedback using defined guidance. Evaluate without custom fine-tuning.
- 03 / AT THE CORE
Focus the investigation.
Escalate persistent issues, missing data, or cases requiring broader evidence. Keep lightweight health summaries flowing.
Less raw data movement.
More focused central analysis.
Illustrative scenario and proposed edge architecture. Findings are fictional, not calculated MQI results. Model suitability and potential cost savings require validation for each deployment.
What would a clearer picture help you do?
Tell us about the performance questions your team needs to answer.