Building Intelligent Enterprises with Custom AI, Predictive and Scalable AI Development

Generative AI (like ChatGPT) creates new content such as text, code, or images. Predictive AI analyzes historical data to forecast future outcomes, such as sales numbers or equipment failure.

We use RAG (Retrieval-Augmented Generation) and private cloud deployments. Your data is indexed in a secure vector database and is never used to train public models like GPT-4. We adhere to GDPR and ISO 27001 standards.

Costs vary by complexity. A simple GenAI chatbot pilot typically starts around $15,000–$25,000, while enterprise-grade predictive systems or custom LLM fine-tuning can range from $50,000 to $150,000+.

Yes. We build AI microservices that connect to your existing ERP, CRM (Salesforce/HubSpot), or custom software via RESTful APIs, ensuring no disruption to your current workflows.

We typically deliver a functional Minimum Viable Product (MVP) in 4 to 6 weeks. This allows you to validate the value quickly before investing in a full-scale deployment.

Yes, we offer MLOps (Machine Learning Operations) packages. AI models degrade over time (model drift); we monitor accuracy, retrain models, and manage server scaling.

We have deep vertical expertise in Fintech (Fraud Detection), Healthcare (Patient Triage), Retail (Dynamic Pricing), and Manufacturing (Predictive Maintenance).

No. We provide a full-service team, including Data Engineers, ML Architects, and AI Developers. We also offer training to help your internal team manage the solution post-handover.

RAG is a technique that connects an LLM to your live company data. It enables the AI to answer questions based on your specific documents (PDFs, emails, databases) rather than relying solely on general internet knowledge.

Off-the-shelf tools offer generic capabilities and low data privacy. Custom AI provides a competitive advantage by being trained on your proprietary data, ensuring 100% data sovereignty and alignment with your specific KPIs.