Custom Artificial Intelligence (AI) solutions for your business

This is the foundational step in artificial intelligence development services, where we identify the opportunities to implement Artificial Intelligence and Machine Learning for a particular business. During this stage, we:

• analyze the company’s existing data, its quality, volume, variety, and sources;
• collect, clean, and preprocess data; 
• Identify business challenges that the AI solution needs to address;
• access the company’s existing IT infrastructure to determine how well the existing systems can integrate with AI;
• system architecture, considering computational and data processing and storing needs; 
• technology stack; 
• develop the roadmap with steps, milestones, timelines, resources required, and clear goals.

This step is about developing the framework within which the AI operates, including user interfaces for applications and the backend activities. We work on: 

• how the app should look and draw mockups;
• integration with existing systems; 
• backend system development; 
• comprehensive testing. 

We establish selection criteria like accuracy, efficiency, scalability, speed, ability to handle different data types, etc. Then we train the model. 

• model selection: supervised, unsupervised, semi-supervised, reinforcement learning, deep learning;
• preparation of training, validation, and testing datasets;
• evaluating the model and parameter tuning;
• documentation of the model selection process, model training parameters, validation results, and any iterations made.

We transition the solution from the development and testing environment into live and operational use. 

• deployment planning; 
• environmental setup; 
• model deployment; 
• application integration; 
• data migration;
• monitoring and logging; 
• user training and support; 
• post-deployment monitoring

We offer an extra mile in fine-tuning and calibrating the AI system. We monitor the system after the deployment, adjusting its work based on gathered data about its performance and feedback.

Defining a mathematical representation of your business challenge to clearly describe the AI task. Our AI developers identify variables, constraints, goals, and select appropriate AI methods to achieve optimal results.

We examine your business processes and gather necessary data from all available sources. We establish clear data governance, clean, preprocess, and structure the data  to ensure high-quality inputs for training accurate and effective AI models.

Building and training AI models using relevant datasets, machine learning algorithms, and statistical techniques to achieve accurate, reliable predictions or classifications.

Rigorous testing and validation of AI models to measure their performance, accuracy, and reliability. Our AI developers split the datasets into two parts: one is used for training and the other for validation. Our experts  fine-tune the model’s parameters to minimize discrepancies between predicted and actual outputs.

Deploying the AI model into your existing business systems or infrastructure, including integration with your software environment, APIs, cloud platforms, or devices. The model starts to get real-time data inside your business.

Life-cycle doesn’t end on deployment. During the post-deployment period, our AI developers continuously monitor the model performance, accuracy, and behavior. Our goal here is to detect issues, prevent drift and hallucinations, and maintain consistent results.