AI Data Analysis
Your data is telling you things you haven't heard yet
We turn your company's scattered data into clear, actionable insights using AI. Evidence-based decisions, not intuition.
Benefits
Why Deepyze for your AI Data Analysis?
We work with industry best practices to guarantee real results.
Executive dashboard
Clear visualizations of the KPIs that matter. Real-time data so leadership always has the pulse of the business.
Demand predictions
Predictive models that anticipate future demand based on historical trends, seasonality and external factors.
Anomaly detection
AI automatically detects outliers: unusual sales, suspicious behavior, quality defects. Alerts before they become problems.
Customer segmentation
We group your customers by purchase behavior, lifetime value and other variables so you can communicate in a personalized way.
Churn analysis
We identify which customers are most likely to leave before they do. Timely intervention to retain them.
Automated reports
Reports generate themselves and are sent to the team at the right time. No more spending hours building Excel every week.
Process
How we build your AI Data Analysis
A clear and transparent method so you always know which stage your project is at.
- 1
Data inventory
We survey all your data sources: CRM, ERP, e-commerce, social media, sensors. We evaluate quality and availability.
- 2
Data architecture
We design how to integrate and centralize all data in a data warehouse. Every analysis starts from clean, trustworthy data.
- 3
Models and visualizations
We develop the AI models and visualization dashboards based on prioritized use cases.
- 4
Training and adoption
Data analysis is only valuable if the team uses it. We train users in interpreting reports and models.
Pricing
How much does it cost?
It depends on the scope: we define it together in a free discovery meeting and send you a fixed-price proposal.
FAQ
Frequently asked questions about AI Data Analysis
How much data do we need for AI models to work?
It depends on the model. For demand predictions we need at least 1-2 years of history. For customer segmentation, hundreds of transactions are enough. We evaluate case by case.
What tools do you work with?
Python with scikit-learn, pandas and TensorFlow for models. Power BI or Metabase for dashboards depending on the case. All integrated with your existing stack.
How much does implementing AI data analysis cost?
It depends on the scope: we define it together in a free discovery meeting and send you a fixed-price proposal.
Does our company's data stay in third-party cloud?
We can implement on your own cloud infrastructure (AWS, GCP, Azure) or on dedicated servers so your data doesn't leave your control.
Can you connect with Google Analytics, Facebook Ads, etc.?
Yes. We integrate with major digital marketing platforms for a unified view of all channels.
How long does a data project take?
A data analysis MVP can be ready in 4-8 weeks. More complex projects with multiple sources and advanced models can take 3-6 months.
Products we built
Our own software, running in production
- Fixed price
- We quote with closed scope and price. You know what it costs from day one, no surprises.
- The code is 100% yours
- When we finish, the repository, the infrastructure and the documentation are entirely in your name.
- Same time zone
- We work South American business hours. Meetings and answers with no time-zone delays.
- Proposal in 24-48 h
- After the first meeting you get a detailed written proposal, with no commitment and no fine print.
Damián Oliva
Founder of Deepyze
You work directly with the person who builds. Years building digital products in LATAM, Google Cloud Machine Learning certified.
Meet the founderReady to start your AI Data Analysis project?
Tell us your idea and we'll prepare a no-commitment proposal in 24 hours.