D-coupleStrategic intelligence for autonomous growth
By Kenneth Melchor, Founder & Technology Director

Overview
This case study covers how D-couple needed a strategic intelligence platform that could transform raw market data into actionable business decisions — autonomously, enabling autonomous growth. We built an AI-powered engine that monitors, analyses, and reports on competitive landscapes in real time, freeing their team to focus on execution rather than data collection. The platform ingests data from over 40 structured and unstructured sources, applies machine-learning classifiers to filter noise, and delivers executive-ready summaries through an interactive dashboard. The system's anomaly detection module identifies statistically significant market shifts within minutes of occurrence, pushing alerts to designated stakeholders via Slack, email, and the executive dashboard simultaneously.
The project scope included designing and deploying AI-powered data pipelines using Python and TensorFlow, a machine-learning report generation engine that produces executive summaries from raw market signals, an executive dashboard built in Next.js with real-time market feeds via WebSocket connections, and a custom alert system that notifies stakeholders when competitive movements exceed predefined thresholds. The platform replaced manual research workflows that were consuming over 60% of the team's productive time, processing data from over 40 structured and unstructured sources. A custom role-based access layer ensures that different team members see only the intelligence relevant to their vertical, maintaining information compartmentalisation across business units.
The Challenge
D-couple's team was spending over 60% of their time manually gathering competitive intelligence, assembling reports, and tracking market movements across dozens of sources. The data was scattered across industry databases, news feeds, regulatory filings, and social channels — the process was slow, and by the time insights reached decision-makers, opportunities had already passed. They needed a system that could centralise data ingestion, apply intelligent filtering, and deliver strategic summaries without human intervention — while maintaining the analytical rigour their clients expected. Additionally, the existing reporting tools could not adapt to new data sources without engineering intervention, creating a bottleneck every time the competitive landscape shifted or a new market vertical was added.

The Solution




"Within three months of launch, D-couple's leadership had real-time visibility into market movements that previously took weeks to compile."
Results
The strategic intelligence platform delivered transformational results within its first quarter of operation. Reporting cycles that previously consumed weeks of manual data gathering were compressed to automated deliveries in under two seconds. D-couple's leadership team gained 24/7 real-time visibility into competitive movements across their target markets — a capability that previously required a dedicated full-time analyst. The 85% reduction in reporting time freed over 60% of the team's productive capacity for strategic execution rather than data collection. Revenue grew 32% in the same period, directly attributed to faster market response times and data-driven decision-making enabled by the platform's automated alerts and trend analysis. The machine-learning classifiers improved their accuracy from 78% to 94% over the first 90 days as the system learned from analyst feedback loops.
85%
Reporting time reduction
32%
Revenue increase
24/7
Continuous monitoring
<2s
Insight delivery
Performance
Mobile · Google PageSpeed Insights
KAUFAST Track Record
97+
Lighthouse score on kaufast.com across all four categories — verified via Google PageSpeed Insights, June 2026
20+
Years delivering technology solutions — founded in Barcelona, 2004
50+
Projects delivered across 6 countries and 3 continents
< 100ms
Time to First Byte via Vercel Edge Network — every managed project, worldwide
All metrics independently verifiable. Last audited June 2026.

Credits
Technologies
- Python
- TensorFlow
- PostgreSQL
- Redis
- AWS Lambda
- Next.js
Team
- Strategy Lead
- AI/ML Engineer
- Full-Stack Developer
- Data Engineer
- UX Designer
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