Who they are
Qompass is a decision-support product designed for large enterprise groups that manage complex operations and siloed data across divisions.
All case studies
10 / Case study · Qompass
AI-Powered Decision Support System
Turning scattered information into a decision brief.
What they set out to do
Leaders wanted internal and external data consolidated into one intelligent dashboard that spots patterns, predicts issues and recommends actions with transparent reasoning.
The problem they were living with
Operational and external information was spread across divisions and sources. Leaders depended on manual reports and disconnected views, which made it harder to spot an emerging issue or see which action the data supported.
What it was costing them. Decisions stayed slow and siloed: data was scattered across divisions, procedures were inefficient and most insights arrived too late to prevent losses.
What changed
- Decision-making time reported up to 60% shorter
Real-time issue alerts replace manual reviews.
- Reporting time reported around 50% lower
Automated aggregation and visualization cut manual reporting hours.
- Potential issues surfaced before they escalate
Pattern and anomaly detection feed early warnings for review.
- Every recommendation carries its reasoning
Outcomes as recorded in the QuantumByte enterprise case-study portfolio (2025). The percentages are the engagement’s own reporting, not an independent audit.
Designed solutions
What we designed for Qompass’s people.
Unified data view
Internal operational information and external signals meet in a common dashboard.
Source collection and monitoring
The data-management view shows source connections, crawler state and collection progress.
Early-warning analysis
Pattern and anomaly detection surface issues and potential risks for review.
AI recommendations
Recommendations turn observed patterns into proposed actions with supporting reasoning.
Executive and departmental dashboards
Tailored views bring relevant indicators and issues to leadership and individual departments.
Priorities and reporting
A priority view and automated aggregation turn collected information into material for decisions.
The workflow
How the work flows now.
Connect the sources
The team collects internal data and relevant external information.
Watch the data flow
Operators review source connections and collection status.
Find the issue
Leaders use the shared view to inspect patterns, anomalies and emerging risks.
Understand the recommendation
They review the proposed action alongside its reasoning.
Prioritize the response
The issue moves into the appropriate leadership or departmental view.
The interfaces
A closer look at what the team uses.
Where else this applies
The same approach, in other industries.
| Industry | Fit | Why |
|---|---|---|
| Government agencies | High | Integrating data across agencies improves oversight and policy response. |
| Energy and infrastructure | High | Tracks asset utilization, environmental risk and regional disruptions. |
| Banking and finance | High | Predictive alerts support compliance, risk exposure and fraud detection. |
| Healthcare | Medium | Monitors operational KPIs, patient flow and regulatory compliance. |
Kevin’s part
Kevin led delivery with the Quantum team: the unified data view, the recommendation design and the executive dashboards.
How I think about work like this
Working on something like Qompass’s?
Tell me where the workflow breaks today and who carries it. I’ll tell you what the smallest useful slice would be, and whether I’m the right person to build it.