Ship production AI features without turning your product into a science project.
New Empire helps teams move from AI idea to a reliable shipped feature: grounded answers, clean integrations, measurable workflow automation, and architecture that can survive real users.
Best fit
Founders, CTOs, and product teams that already have a useful AI use case and need senior engineering to make it safe, useful, and shippable.
Outcomes
- A scoped AI roadmap tied to user value and delivery risk
- Production integration with OpenAI, Gemini, Hugging Face, or self-hosted models
- RAG and automation patterns that reduce manual work without hiding failure modes
- Cost, latency, and quality controls that make AI practical after launch
What we deliver
- Architecture review and integration plan
- Model/provider selection with cost and reliability tradeoffs
- Implementation sprint for the highest-value AI workflow
- Observability, fallback behavior, and launch checklist
Proof you can inspect
- Built a Generative AI SaaS foundation using OpenAI, RAG, multi-LLM routing, Node.js, Python, AWS, and PostgreSQL.
- Automated 60%+ of manual workflows in a production AI SaaS context.
- Delivered regulated and high-uptime platforms for enterprise environments including aviation and banking.
How the sprint works
- Map the business workflow and decide where AI should not be used.
- Design the retrieval, tool, and model boundaries before writing prompts.
- Ship a narrow production slice with logs, eval hooks, and fallback paths.
- Review usage data and harden the system around real user behavior.
LinkedIn post angles
Use these as post hooks and point each one back to this page with UTM tags.
- Why the expensive part of AI integration is usually workflow design, not model access.
- A production AI feature checklist: grounding, fallback behavior, logs, evals, and human override.
- How to pick the first AI workflow worth automating in a B2B SaaS.
Questions buyers ask
Can you work with our existing product?
Yes. Most engagements start inside an existing SaaS, internal tool, or workflow. The first step is narrowing the integration to one valuable, testable path.
Do you only use OpenAI?
No. OpenAI is often a strong default, but the architecture can support Gemini, Hugging Face, vLLM, or provider routing when cost, privacy, or latency require it.
How fast can we start?
A focused audit can start with a short review call. A build sprint usually begins after a scoped outcome, access requirements, and acceptance criteria are agreed.
Next step
Have a product or AI workflow worth shipping?
Send the context, the risk, and what a useful first version needs to do. We will turn it into a practical build path.
Book a project call