Frequently Asked Questions

We typically start with a Discovery Phase (2-4 weeks). We audit your existing data infrastructure, identify high-impact AI use cases, and deliver a strategic roadmap. This ensures we build the right thing before writing a single line of code.

Timelines vary by complexity. A Proof of Concept (PoC) usually takes 4-6 weeks. A production-grade MVP (Minimum Viable Product) typically takes 3-4 months. We work in agile sprints to deliver incremental value.

Yes. We believe in enabling your team, not creating dependency. We offer workshops on Prompt Engineering, AI Governance, and RAG Architecture to ensure your team can maintain and evolve the systems we build.

We are stack-agnostic but specialize in the modern AI ecosystem: Python for backend logic, LangChain/LangGraph for agent orchestration, and vector databases like Pinecone, ChromaDB, or Weaviate. For the frontend, we use React or Next.js.

We use a RAG (Retrieval-Augmented Generation) architecture. By grounding the AI's responses in your own verified documents and using strict system prompts, we virtually eliminate hallucinations. We also implement "citation" features so you can verify the source of every answer.

Seamless integration is our specialty. We connect AI agents to your existing ERP, CRM (Salesforce, HubSpot), and databases (SQL, NoSQL) via secure APIs. The AI acts as an intelligent layer on top of your existing tools.

Security is paramount. We design Private AI systems where your data is processed within your secure cloud environment (Azure, AWS, GCP). We ensure your data is never used to train public models like ChatGPT.

Yes. For highly regulated industries (Finance, Healthcare, Government), we can deploy open-source models (like Llama 3 or Mistral) entirely on your own infrastructure using tools like Ollama or vLLM, ensuring zero data egress.