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Puig had the world's best fragrance data. We turned it into a platform.
AI development starts with a business problem, not a model. We design and build artificial intelligence and machine learning systems. Systems that automate decisions, surface patterns buried in data, and handle work no team could do by hand. Recommendation engines. Forecasting. Workflow automation. Each one tied to a clear goal.
Some projects need a fully custom model. Others just need pre-trained intelligence wired into an existing product. We help you figure out which path fits. Then we build AI solutions that move the numbers.
AI for its own sake is a liability. We build systems that solve real problems and prove it with measurable impact.
Historical data turns into actionable predictions. Teams act before the problem lands.
Complex, repetitive tasks run without human hours behind them.
Content, services, and interfaces adapt to real behavior in real time.
Pattern detection and live analytics speed up decisions across the business.
Classification and prediction. Understand user behavior, segment audiences, forecast events.
Recommendation engines. Suggest content, products, or next actions from usage patterns.
Computer vision. Detect, track, or classify objects in images and video.
Natural Language Processing (NLP). Extract insights from text, power chatbots, automate language-based tasks.
Custom model training. Supervised and unsupervised models trained on your domain data.
Scale customer support with smart assistants. No headcount explosion.
Run predictive analytics, dynamic pricing, and visual search across e-commerce.
Automate internal workflows with models that make operational calls.
Pull hidden insights from unstructured data. Images, voice, logs, documents.
We design, train, and deploy machine learning systems tied to your business goals. Every solution is grounded in your data. It holds under real load, from first experiment to production.
We map where AI makes sense and where it doesn't. Your data, your workflows, your goals. Honest answers up front.
We train custom models in TensorFlow and PyTorch. We pick the architecture that fits the problem, not the trend.
We clean, structure, and annotate your datasets. Great AI starts with great data.
We package models as APIs or edge-ready apps and wire them into your product or backend.
Metrics, alerts, and retraining pipelines keep your AI accurate as the data shifts.
We build systems that are auditable, interpretable, and GDPR-aware.
Not always. We work with existing datasets, use transfer learning, or set up pipelines to gather and label new data as we go.
Yes. We handle the full development process. Models ship as standalone services, APIs, or integrated features.
We start with a discovery phase. We evaluate the problem and the technical feasibility before recommending a solution.
Cost depends on complexity. We structure projects to prove value early. Most start with a pilot or proof-of-concept before scaling up.
Balanced datasets, transparent model design, and testing protocols aligned with fairness goals. Optional audits when the use case is sensitive.
Yes. We build modular, API-ready models. They plug into your frontend, backend, or infrastructure cleanly.
Puig had the world's best fragrance data. We turned it into a platform.
Nobody had solved fragrance discovery online. We built the first AI that does.
A logistics company that ships to 190 countries built something to ship to itself.















