We Build AI Products

We build production-grade generative AI products — custom AI chatbots, AI SaaS platforms, RAG (retrieval-augmented generation) systems, autonomous AI agents, AI copilots embedded in existing apps, document automation pipelines, and AI-powered search. Everything we ship runs on OpenAI GPT-4, Anthropic Claude, Google Gemini, or open-source models like Llama and Mistral.

A focused AI chatbot trained on your knowledge base typically ranges from $8K–$25K. A full multi-tenant AI SaaS product (with billing, vector search, prompt analytics, and admin dashboards) ranges from $35K to $150K+ depending on complexity. We provide a fixed-scope quote after a free 30-minute discovery call.

A custom AI chatbot with RAG goes live in 3–6 weeks. An MVP AI SaaS product typically ships in 8–12 weeks. Enterprise AI integrations with multiple data sources, fine-tuning, and compliance reviews take 12–20 weeks. We work in 2-week sprints with weekly demos so you see real progress every Friday.

For LLMs: OpenAI GPT-4o, Anthropic Claude 3.5/4, Google Gemini, and open-source Llama 3, Mistral, and DeepSeek. For frameworks: LangChain, LlamaIndex, Vercel AI SDK, and custom orchestration. For vector search: Pinecone, pgvector, Weaviate, Qdrant. For deployment: AWS Bedrock, Azure OpenAI, and self-hosted on GPU clusters.

Yes. We fine-tune open-source models (Llama, Mistral) on your proprietary data and deploy them in your own VPC — so no data ever leaves your infrastructure. For OpenAI/Anthropic, we use enterprise zero-retention agreements. We also build air-gapped on-prem deployments for healthcare, finance, and government clients.

We use a layered approach: well-tuned RAG with re-ranking, structured outputs (JSON schemas), guardrails for refusal and topic-control, automated eval suites that grade every prompt change against a golden dataset, and human-in-the-loop review for high-stakes flows. Every AI product ships with monitoring dashboards tracking accuracy, latency, and cost.

Absolutely. You own 100% of the code, prompts, fine-tuning datasets, and IP — handed over via your private GitHub or GitLab repo at every milestone. We never reuse client prompts, embeddings, or training data on other projects. The contract explicitly assigns all rights to you on final payment.

Yes. AI products require continuous tuning as models evolve. Our AI Maintenance retainers (starting $2,500/mo) cover model upgrades (e.g., GPT-4 → GPT-5), prompt regression testing, cost optimization, vector index re-builds, hallucination monitoring, and quarterly performance audits.

Zeebrix is headquartered in Fremont, California (Bay Area). Our distributed AI team has shipped products for 150+ clients across 25+ countries — including the US, UK, Canada, Australia, UAE, Singapore, and across Europe. We have at least 6 hours of live overlap with any timezone globally.