Frequently Asked Questions
Answers to common questions about our AI solutions and services.
What is context engineering?
Context engineering is the process of structuring and optimizing the information fed to AI models to ensure relevant, accurate, and consistent outputs. We use RAG (Retrieval-Augmented Generation), custom data integration, and prompt optimization to give your AI the right context for your business needs.
How long does a typical AI implementation take?
Timelines vary by project scope. A readiness assessment takes 2-4 weeks, custom model development 4-12 weeks, and ongoing support is continuous. We provide detailed timelines during the initial consulting phase.
Do you offer on-premise or cloud deployments?
Yes, we support both. Our solutions are tailored to your infrastructure preferences, ensuring data privacy, compliance, and optimal performance whether in the cloud or local environments.
What makes your AI services different?
We focus on complete control and ownership. Unlike generic providers, we customize models, prompts, and contexts to your specific processes, avoiding the 95% failure rate of unfocused AI pilots.
How do you ensure AI ethics and bias mitigation?
Ethics is core to our approach. We conduct bias audits, implement fairness checks, and follow best practices like diverse training data and transparent decision-making to build trustworthy AI systems.