WE DON'T BUILD “GENERIC” AI

The first step is a feasibility assessment. The problem, available data, and expected outcome are evaluated to determine whether AI or traditional automation would deliver better results.

The AI development services cost depends on data complexity, model development, integrations, and infrastructure. Smaller AI applications may start around $15,000–$30,000, while enterprise AI platforms can exceed $100,000 depending on scope.

A basic AI prototype can take 6–10 weeks, while production-grade AI systems with training, testing, and integration usually take 3–6 months depending on complexity.

Not always, as some AI solutions work with moderate datasets, while others may require larger datasets. In many cases, existing business data can be cleaned and structured for model training.

Yes, AI models are usually deployed through APIs or microservices, which allows them to integrate with CRMs, ERPs, internal databases, and other enterprise systems without major infrastructure changes.

AI can automate processes such as customer support responses, document processing, predictive forecasting, fraud detection, and internal workflow decision-making depending on the industry and available data.

Traditional chatbots rely on fixed rules and predefined responses, while LLM-based systems can understand context, generate natural responses, and handle complex queries more dynamically.

We handle data security through secure environments, encrypted storage, controlled access policies, and compliance with industry data protection standards throughout the development process.

Post-deployment includes performance monitoring, model retraining, optimization, and system updates to ensure the AI continues to perform accurately as business data and requirements evolve.

ROI is typically measured through operational efficiency improvements, reduced manual workload, faster decision-making, improved customer experience, and measurable cost savings over time.