Automated machine learning
for enterprise solutions
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Protogen’s machine learning modules specialize in computer vision, time series and tabular data analyses.
With Protogen you can transform your enterprise data to produce critical insights on main business flows.
Protogen engine consists of 2 building blocks
- Time series analyses
- Tabular data analyses
- Deep motion analyses
- Anomaly detection
Machine Learning/ Deep learning modules
- Neural Nets
- Boosting trees
- Advanced reporting generation
- Individual level predictions
How AutoML works
Produces high-quality model
Automatically handles tabular data input
Saves time and money
Main Business Use Cases
Maximize your revenue
Accurately predict customer demand and maximize your revenue by optimizing product distribution, promotion and pricing.
Understand your customer
What’s your average customer’s lifetime value? Make the most of your marketing spend by using Protogen to estimate lead conversion and churn probability.
Optimize your portfolio
Foresee and optimize your policyholder portfolio’s risk and return by zeroing in on the potential for large claims and likelihood of fraud.
Maintain your equipment
Proactively anticipate asset, device, and equipment breakdowns to ensure your fleet operates at optimal performance with minimal costs.
- Fraud detection
- Ad optimization
- Sales forecasting
- Anti-money laundering
- Product failure prediction
- Resume screening
- Sales prioritization
- Credit risk
- Store layout
- Customer retention/churn
- Store location optimization
- Recommendation systems
- Staff scheduling
- Insurance risk classification
- Insurance loss prediction
Protogen vision modules provide state of the art results for a broad set of deep learning problems in the domain of computer vision, including video motion analyses and anomaly detection.
The user defines the problem and, if necessary, supplies task-related dataset.
The general model is selected from our vision module and fine-tuned on the task.
After successful testing, the model is deployed in production.
Meet the Team
Armen Ghambaryan is a lead Data Scientist in Develandoo. He has been developing analytical systems based on the state-of-the-art machine learning models for central banks.He holds a Ph.D. degree in Economics. He sees a big promise in Protogen, since it aims to unlock the full potential of financial data by building fast, accurate and interpretable predictive systems.
Davit Tumasyan is a chief technology officer. He is a former chief architect and backend developer. Davit has more than 6 years of experience in designing and developing large scale applications and big data solutions. He is confident that combining his experience with AI solutions and his business acumen, he is capable of developing protogen into robust solution that can cater to diverse clients and markets. He has excellent communication skills, enabling him to deeply engage with clients’ business requirements, operating markets to help them do develop modern and flexible solutions.
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