Frequently Asked Questions
Everything you need to know about implementing enterprise AI solutions, security, and our process.
Q.What is an AI Agent, and how does it differ from traditional software?
A. An AI Agent is an autonomous or semi-autonomous system that uses language models and machine learning to understand intent, make decisions, and take actions using tools (like APIs, databases, or browsers) to achieve a goal. Unlike traditional software that follows rigid if-then logic, agents can adapt to novel situations and reason through complex, multi-step workflows.
Q.How long does it take to implement a custom AI solution?
A. Implementation timelines vary depending on complexity. A standard internal AI copilot or proof-of-concept might take 2-4 weeks. Full enterprise system integrations with custom models and complex workflow automation typically range from 8 to 16 weeks from discovery to production deployment.
Q.Is my corporate data secure when using your AI systems?
A. Absolutely. Security and data privacy are foundational to our architecture. We implement private, isolated model instances (like Azure OpenAI or dedicated Anthropic clusters) where your data is never used to train foundational models. We also integrate with your existing RBAC (Role-Based Access Control) and VPC requirements.
Q.Do we need an in-house engineering team to manage the AI after launch?
A. No. We offer ongoing Optimization and Managed Services to ensure your AI systems run smoothly, handle edge cases, and scale as your business grows. However, if you prefer to manage it internally, we provide comprehensive training, documentation, and handover processes.
Q.Which LLM (Large Language Model) do you use?
A. We are model-agnostic. We select the best model for your specific use case based on reasoning capabilities, speed, and cost. We frequently work with OpenAI (GPT-4o), Anthropic (Claude 3.5 Sonnet), Google (Gemini 1.5 Pro), and open-source models like Qwen or Llama 3 for specialized, self-hosted applications.
Q.What is an Enterprise Knowledge System (EKS)?
A. An Enterprise Knowledge System is an AI-powered infrastructure (often using RAG - Retrieval-Augmented Generation) that connects to all your company's disparate data sources (Notion, Google Drive, Slack, Salesforce). It allows your team to instantly query, synthesize, and extract insights from your entire organizational knowledge base.