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AI and machine learning
RAG on internal content and machine learning models on historical data, with permissions, sources and costs under control.
- RAG on internal content
- Predictive models
- Architecture
- Monitoring
What we do · Development
We design and develop it in-house, and support it over time. If the one already in use can work, we start from there.
Development

Data copied by hand between management systems, CRM and vertical tools; software grown through successive add-ons that nobody wants to touch any more.
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RAG on internal content and machine learning models on historical data, with permissions, sources and costs under control.
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CMSs the team manages on its own, ecommerce integrated with CRM and marketing, data with no manual exports.
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Software, web apps, portals and native or hybrid mobile apps, from analysis to release and beyond.
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With APIs, webhooks, middleware and DWAY, so that every system works on up-to-date data.
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Corrective and evolutive maintenance, monitoring and security, without stopping operations.
Goals, flows and users, before writing code.
Architecture and interface.
Development with continuous testing and feedback.
The software evolves with the processes.
Technologies
The method
The three phases repeat for every solution. In development, this is what they mean.
How we workIt starts with an analysis phase on goals, flows and expectations. From there we define timing, costs and releases, with the flexibility of an agile approach.
With REST APIs, webhooks and middleware; for legacy systems, with data mapping and orchestration. Where needed, with DWAY, the integration platform of the DEGG ecosystem.
The stack is chosen for each project: among others Laravel, Vue.js, React Native, Flutter, Django, .NET and Express, with databases such as MySQL.
A process to digitise, a tool to put to work or an idea to develop: it all starts with a conversation.
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