Custom AI Development for Measurable Business Results

The cost of custom AI development depends on the complexity of the use case, data availability, and integration requirements. Projects involving custom AI model development typically start at $25K – $60K for a PoC, scale to $80K – $200K for an MVP, and can reach $250K and above for full-scale production systems.

Every AI project is unique, so its duration varies. Still, as a machine learning development company, we usually count the duration of AI software development in months (the active phase), plus a few more months of maintenance and support (the more passive one).

As an engineering and AI consulting company, we deliver AI solutions across industries such as manufacturing, insurance, e-mobility, logistics, and digital platforms. Our experience includes predictive analytics, demand forecasting, computer vision, NLP, and LLM-based automation. Importantly, we adapt each solution to the specific data, workflows, and business goals of your industry rather than relying on one-size-fits-all tools.

To be honest practice, the difference is minimal because we work as an extension of your internal team. Our engineers integrate deeply into your workflows, collaborate directly with your stakeholders, and take ownership of delivery, so it feels like working with an in-house team. The advantage is that you get immediate access to senior expertise without the time and cost of hiring. This approach is why many of our clients stay with us long-term, with some partnerships lasting over 15 years.

We design every solution with AI system integration in mind from the very beginning. This includes analyzing your current architecture, data flows, and tools to ensure compatibility before development starts. Our ML team builds flexible, API-driven systems that integrate seamlessly with your existing platforms, whether it’s cloud infrastructure, internal tools, or third-party services. We also use containerization and modular architectures to fit into your environment without disrupting current operations.

Yes, we do. We sign NDAs as a standard part of our engagement process and are experienced in working with sensitive business data. We follow strict data security practices, including controlled access, secure data storage, and encrypted data transfer across all stages of development. Furthermore, our specialists adhere to industry standards and compliance requirements such as GDPR and CCPA where applicable.

Your project is handled by a dedicated, cross-functional team tailored to your needs. This typically includes data scientists, ML engineers, and data engineers. We work with a flat structure, no project managers or unnecessary layers, which means faster communication, direct access to the engineers, and quicker decision-making. This approach gives you more transparency, stronger ownership from the team, and a more efficient development process overall.

Delivery is not the end of the process. After deployment, we continue to monitor model performance, retrain it with new data, and optimize it over time. We also support integration improvements, scaling, and feature enhancements as your needs evolve. This ensures your AI solution remains accurate, reliable, and aligned with your business goals long-term.