Web Apps That
Think & Evolve

A standard web app typically follows a pre-defined logic: input leads to a specific output. An AI-enabled web app, however, uses machine learning algorithms to analyze data, learn from user interactions, and make decisions or predictions. This allows for features like personalized recommendations, automated customer support, and predictive analytics that evolve over time.

Not necessarily. While data is fuel for AI, we can start with pre-trained models and fine-tune them as you gather more data. We can also implement strategies to collect high-quality data from day one, ensuring your AI capabilities grow alongside your user base.

Security is our top priority. We implement robust encryption, secure API gateways, and follow best practices for data privacy (GDPR, CCPA). When using third-party AI models, we ensure that sensitive data is anonymized and handled according to strict security protocols.

The timeline varies based on complexity. A prototype or MVP with basic AI features can be developed in 3-4 months. A fully-fledged enterprise solution with custom model training and complex integrations may take 6-12 months. We provide a detailed roadmap during the discovery phase.

Yes, absolutely. We specialize in modernizing legacy applications by integrating AI microservices. Whether you need a chatbot, a recommendation engine, or automated data processing, we can seamlessly embed these features into your current infrastructure.

We use a modern stack including Python (TensorFlow, PyTorch, Scikit-learn) for model development, and robust web frameworks like React, Next.js, and Node.js for the application layer. We also leverage cloud AI services from AWS, Google Cloud, and Azure for scalability.

Costs depend on the scope of the project, the complexity of the AI models, and the level of customization required. We offer flexible engagement models, from fixed-price projects for MVPs to dedicated teams for ongoing development. Contact us for a tailored quote.

Yes, we offer comprehensive post-launch support and maintenance packages. This includes monitoring AI model performance, retraining models as new data comes in, fixing bugs, and ensuring your application remains secure and up-to-date.