Questions,
answered.

›We're an independent AI engineering studio. We design, build, and operate production AI systems, agents, RAG, and automation, for enterprises in telecom, tourism, education, fleet management, procurement, and operations. Every project on our portfolio is a system we've actually shipped.

›We start with a short discovery call to understand the problem. Then we scope a working prototype, usually 1–2 weeks, built against your real workflow. Once it proves out, we move to production deployment and ongoing operation.

›Most prototypes are usable within the first 1–2 weeks. Production rollout depends on integrations and data, but most clients see a deployed system live within the first month.

›Pricing is per engagement and depends on scope, integrations, and operational support. Share your problem on the Contact page and we'll come back with a scoped proposal, including a fixed-price prototype option where possible.

›We're headquartered in Muscat, Oman, and work with enterprises across the GCC and South Asia. Our team operates remotely and on-site as needed.

›We're model-agnostic. We use OpenAI, Anthropic Claude, Google Gemini, and open / local models depending on the workload, sensitivity, latency, cost, and accuracy all factor in. For sensitive data we deploy local LLMs on-prem.

›All three when they fit. Most enterprise problems are best solved with retrieval (RAG) layered with orchestration agents and human-in-the-loop checkpoints. We only fine-tune when retrieval and prompting genuinely aren't enough.

›Your data stays yours. We deploy into your infrastructure where possible (Cloudflare, your cloud, on-prem). For sensitive workflows we use local LLMs so nothing leaves your environment. We never train models on client data.

›We deliver the full system around the AI, frontend, backend, integrations, dashboards, and workflows. AI is rarely useful in isolation; we ship the product, not just the model.

›Often, yes. We've inherited half-built RAG systems, internal tools, and automation pipelines. Send us what you have via the Contact page and we'll tell you honestly whether we can pick it up.

›Yes. AI systems drift, models change, data changes, edge cases surface. Most clients keep us on a lightweight operate-and-iterate retainer once the system is live.

›Zyra is a hybrid retrieval system: a curated knowledge base of Zavia-AI content is scored against your question, the top chunks are passed to an LLM with strict guardrails, and answers cite the source pages. It's a small example of the same patterns we deploy for clients.