We analyze the operational process
We map every step of the current workflow to identify bottlenecks, repetitive manual tasks, and areas where human fatigue might introduce errors.
Design · Research & Development
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AI — How we view Artificial Intelligence at DigitalSolutions
Technology must serve people, not the other way around.
A human, pragmatic and conscious approach. Not a gold rush, not a trophy to show off: a high-precision digital tool that demands craftsmanship, respect for corporate data and a thorough understanding of human workflows.
The principle
We start with people, not with the trendiest model.
At DigitalSolutions, our Research and Development team operates under a simple guiding principle: technology must serve human potential, not replace or overcomplicate it. We do not view Artificial Intelligence as a shiny trophy to exhibit in sales decks or a buzzword to shoehorn into every software project.
In our daily practice, we never start with a trendy AI model and attempt to force a problem to fit it. We do the exact opposite: we start with people, their actual daily work, and the real friction points they face.
01 · Listening
Listening before coding
Analyze, gather, measure. When embarking on a new project we don't retreat into an isolated room to write code: we sit down at the table with the people who carry out the work every single day.
We gather true requirements
We collect ground-level requirements, carefully separating nice-to-have features from core operational needs.
We define technical specifications
We translate business requirements into clean, scalable, and sustainable technical specifications.
We measure AI's actual utility
Does introducing AI into this specific step deliver measurable, tangible value, or is it merely adding unnecessary cost and friction? If the measurement shows marginal benefits, we have the integrity to advocate for a simpler alternative.
If the benefit is marginal, we have the integrity to say no.
02 · Simplicity
The pyramid of simplicity
We firmly believe in avoiding over-engineering. We follow a ladder of minimal necessary complexity, always aiming for the most stable, cost-effective and transparent solution: we climb a step only when the one below isn't enough.
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Cloud Generative AI
Only when local falls short, with encryption and anonymization.
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Local Generative AI
Natural language and synthesis, with data kept in-house.
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Machine Learning & Deep Learning
Patterns, profiling, prediction: lightweight and specialized.
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Standard algorithm or Flow Manager
Clear rules, 100% deterministic: we always start here.
A standard algorithm or a Flow Manager?
Quite often, what a business truly needs isn't artificial intelligence, but a well-designed deterministic process. If a problem can be solved using explicit rules, logic flows and predictable conditions, the best answer is a traditional algorithm or a structured flow manager.
- Instant execution
- Near-zero operational costs
- 100% deterministic reliability, no hallucinations
Machine Learning or Deep Learning?
When the task demands pattern recognition, predictive analytics or complex data classification, we evaluate specialized Machine Learning or Deep Learning models. Remarkably fast, highly accurate and computationally lightweight compared to modern generative neural networks.
- Large-volume data analysis
- Patterns, profiling, prediction
- Fast, readable, lightweight
03 · Data sovereignty
Local AI first.
If, and only if, our evaluation proves that natural language reasoning, advanced synthesis or creative generation make Generative AI strictly necessary, our first instinct is never to immediately connect to public cloud APIs.
Our immediate next question is: can we manage this with Local AI?
Prioritizing Local AI (on-premise or within private, dedicated instances) represents our commitment to privacy and engineering discipline.
Absolute data protection
Sensitive business data never leaves the client's controlled network and is never exposed to third-party model training.
Technological independence
No unpredictable token-based pricing, no reliance on external APIs that could change policies or terms at any time.
Tailored integration
A localized model can be fine-tuned specifically for the domain, creating a precise, secure and context-aware enterprise tool.
04 · Cloud
Cloud is an intentional, controlled step
Only when local hardware limits or the vast scope of the task exceed what on-premise infrastructure can handle do we expand toward Cloud Generative AI. Even then, it is never a default or a lazy shortcut.
Encryption
Strict encryption protocols on everything that leaves.
Minimization
We send only the data that is strictly necessary.
Anonymization
Anonymization layers applied before every call.
ROI under watch
Continuous ROI monitoring: every call must yield real value.
DigitalSolutions
True leadership isn't about implementing AI everywhere.
It's about seamlessly blending technological power with human process intelligence.