Not prototypes that die in a demo: real clients already operating with what we built. The recommendations are verbatim from each CEO.
AI-assisted recovery of failed payments
[to be confirmed]
We built a flows engine that orchestrates recovery end to end: it detects the failed payment, decides the play per case — retry, reminder, payment link — notifies via WhatsApp and email, charges, and keeps every step traceable. It adds a Payment Score that prioritizes where it's worth insisting, and AI-assisted customer support.
Satellite agronomy intelligence with ML models
[to be confirmed]
Two systems operating in real fields under hyperz's technical leadership: SAT Explorer, continuous crop monitoring via satellite imagery (Google Earth Engine, Sentinel, Landsat) with NDVI, NDRE, NDWI, EVI and MSI indicators; and an Intelligent Nutritional Plans System that integrates sap analysis, microbiology, soil, climate and satellite data with ML and full traceability.
“They proved able to design systems that combine diverse data into a coherent, traceable architecture, ML applied to real production data, and effective communication with non-technical teams. I recommend hyperz without reservation for projects requiring applied-intelligence system design, complex data integration, machine learning, and decision-oriented solution architecture.”
AI in a sustainability pipeline, in production
[to be confirmed]
A Sustainability and Double Materiality Analysis platform, from concept to production with full design and development by hyperz: automated scraping of dynamic web portals, analysis and classification of company information with LangChain and OpenAI, and automated PDF report generation. Not a pilot: a component that runs in the pipeline every day.
“The ability to embed AI models into an operational data pipeline — not just as a prototype but as a production component — and an end-to-end view of the whole cycle. They took the project from concept to real production, meeting deadlines and quality standards.”
