ruru/ruen
ai
Artificial Intelligence and Machine LearningWe develop AI products that improve business processes, automate routine tasks, and optimize resources.
Benefits of Working with Us
20+Developed Projects
Custom SolutionsUnique business requirements are met by selecting or developing AI models perfectly suited to the task at hand.
Modern TechnologiesPython, C++, TensorFlow, PyTorch, ONNX
Service IntegrationsWe integrate our models into websites, applications, and Telegram bots to enhance user experience.
High PerformanceOptimizing the codebase and server load ensures maximum model processing speed.
Support and Project DevelopmentWe maintain and improve the models we've created to adapt to evolving business needs.
Work ProcessKey Stages
Analysis
Collecting requirementsDefining model quality metricsPreparing technical specifications
Business AnalystSystem AnalystML engineer
Design
Selecting from existing models or designing a model from scratchPreparing training data for the model
System AnalystML engineerEnterprise architector
Development
Creating or integrating the modelTraining the model on pre-prepared dataTesting its functionality
Back-end developerML engineerQADevOps
Support
Model refinement as new data emergesEnsuring server and technical supportConsulting on further project development
QABusiness AnalystDevelopment team
Technologies and Methods
We select the optimal technology stack for each project, using only proven and modern tools that we excel in.
manager
Igor TarakinProject Manager
Data Collection
ETL PipelinesText/Image/Audio Annotation
Model Development
PythonC++PyTorchTensorFlow
Deployment & MLOps
Docker/K8sAirflow/KubeflowTensorFlow Serving/TorchServe
Frequently Asked Questions
01Do I need my own data to use your services?
No, not always. If you choose to integrate ready-made solutions via API, your own data is not required. For additional training of pre-existing models or development from scratch, data is preferred, but we can help collect and prepare datasets if you don’t have them.
02How long does it take to implement a neural network solution?
It all depends on the chosen approach. API integration can yield results within one to two weeks. Fine-tuning a pre-trained model takes from a few weeks to six months, depending on task complexity and data volume. Developing a model from scratch may take six months or longer.
03What accuracy guarantees can you provide?
We focus on metrics such as Accuracy, F1-score, Recall, etc., which we agree upon during the technical specification stage. The more extensive and high-quality your dataset, the higher the potential accuracy. When integrating pre-trained API solutions, accuracy depends on the provider, but in most cases, they already offer high-performance models.
04How can we scale the ready-made solution?
We use modern MLOps tools and cloud technologies (Docker, Kubernetes, AWS, GCP, Azure), which allow easy scaling as demand increases. For API-based integration, scalability is usually handled by the provider.
05How much does it cost and what does the price depend on?
The cost is calculated based on project complexity, required time, and data volume. API integration is the most cost-effective option as it does not require significant computing resources. Fine-tuning pre-trained models is more expensive but still saves time compared to creating a model from scratch. Full custom development is the most resource-intensive approach, but it offers the highest flexibility and control over the final outcome.
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