We don't sell services: We solve problems.
It all converges
Diagnosis
The real problem isn't always the obvious one at first glance. We see the situation without the bias of being inside the organization.
Right-sized solution
We propose the simplest and most fitting solution for your specific problem. Never a bazooka to kill a mosquito.
Installed capacity
When we're done, your team has full ownership of the solution. If we keep working together, it's because you want to and we can help, not because we've got you trapped in a black box.
Diagnosis
The real problem isn't always the obvious one at first glance. We see the situation without the bias of being inside the organization.
Right-sized solution
We propose the simplest and most fitting solution for your specific problem. Never a bazooka to kill a mosquito.
Installed capacity
When we're done, your team has full ownership of the solution. If we keep working together, it's because you want to and we can help, not because we've got you trapped in a black box.
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Everyone wants an AI agent. Few understand what it takes to go from a demo to a product that handles thousands of users without token costs exploding, hallucinations appearing, or everything becoming unmanageable.
Generative artificial intelligence and applied
GenAI features, chatbots, agents. From proof of concept to production solution, we know how to solve every technical and business challenge that appears when you try to scale.
MODO: generative AI features in the app (19 M+ users). Techint: institutional conversational assistant.
You've got data scattered across a dozen systems, no single source of truth, and every new project starts by re-inventing the wheel. Sound familiar?
Data infrastructure that works
Data architecture, pipelines, data lakes and warehouses. The unglamorous work that makes everything else possible. Without this, any AI model is a house without a foundation.
CCM/DataVue: datalake + ETLs for encrypted credit data. Moni: migration from legacy ETLs to modern architecture.
Your data science team built a great model in a notebook. Six months later, it's still in the notebook. Meanwhile, business decisions keep being made on gut feel.
ML models that reach production
Predictive model development, deployment, monitoring, and retraining. You can confirm intuitions with data, not with PoCs that stay in a notebook but with solutions that run in production and generate measurable impact.
Moni: delinquency prediction model that improved high-risk loan recovery by 20%. MODO: contextual Search a year before the competition.
Your models are in production. Retraining is manual, monitoring is a spreadsheet, and when the data scientist who built it leaves, nobody knows how it works.
MLOps and operational maturity
CI/CD/CT for ML models. Replicable frameworks so your team can operate independently.
MODO: MLOps framework that MODO adopted and operates independently today. CTF Capital: deployment, retraining, and monitoring of predictive models.