Reliable AI and Data systems
We turn AI and data work into reliable production systems with measurable business output.
Works with the models you trust
The gap between a working demo and production is where AI stalls.
You can't measure quality
No eval suite means every change is a guess, and "almost ready" lasts three quarters.
It's too slow and too expensive
Per-query cost often lands 3–5x higher than it needs to be. At real volume, that becomes margin leakage.
It works in the demo
Retrieval returns plausible-but-wrong context and the model answers faithfully from it. Customers notice before you do.
How we get AI features into production.
A focused review of your AI/data system, delivered in 5 business days with written findings and a practical roadmap. The review is credited against implementation work if we continue together.
- Technical deep-dive & architecture review
- Sample analysis with written findings
- Prioritized roadmap you own outright
A scoped engagement to improve, rebuild, or productionize a specific AI/data workflow, with quality, latency, and cost engineered to production levels.
- Eval suite so quality is measured, not guessed
- Retrieval quality & grounding fixes
- Latency & per-query cost engineering
Continued technical ownership for teams that need senior AI/data capacity without agency overhead, from RAG and agents to the data foundations underneath.
- RAG & tool-using agents
- Data foundations & pipelines
- Monitoring, evals & cost controls
Most clients start with an AI & Data Readiness Review, then scope implementation from there. Every engagement is quoted after we understand the system.
Book a 30-minute callFractional AI lead available on a monthly engineering retainer.
Your infrastructure, your model of choice.
We are not locked into a single vendor. We deploy where your data and budget make sense, on the models that fit each job.
In-house & on-premise
Deploy models inside your own infrastructure or private cloud, so sensitive data never leaves your walls. Ideal for regulated and security-conscious teams.
Managed cloud
Ship fast on managed cloud with autoscaling and no servers to babysit. We handle setup, monitoring, and cost controls end to end.
- OpenAI GPT
- Anthropic Claude
- Google Gemini
- xAI Grok
- Perplexity
- Mistral
- DeepSeek
- GLM
- Llama
- Qwen
- Gemma
Review. Build. Run.
Review
A senior engineer assesses your system and tells you honestly what is worth building, in writing.
Build
Fixed-scope implementation with evals and monitoring from day one.
Run
Retainer-based operations: we keep your AI systems reliable, observable, and cost-efficient.
About Norviq
Norviq gives you senior AI/data engineering capacity without the agency overhead. One accountable technical lead owns the path from architecture to production.
We have spent 9 years building and running production data and AI systems: platforms handling large-scale event pipelines, LLM and RAG systems for financial institutions, and production AI workflows where quality, latency, and cost had to be measured rather than guessed.
We work directly with technical teams across the US and Europe, from discovery and architecture through implementation, production rollout, and ongoing improvement.
I'm Laze, founder of Norviq. A senior data & AI engineer with 10+ years designing and scaling production data and AI systems.
Frequently asked questions.
Norviq is a senior specialist practice for production AI. We do the evals, retrieval quality, latency, and cost engineering that move an AI feature from a working demo to something real customers depend on, plus the data foundations underneath it.
Teams in fintech, SaaS, and data-heavy businesses with an AI feature stuck between prototype and real customers. We build to the standards regulated industries expect: quality, latency, and cost that are measured rather than guessed.
Most clients start with an AI & Data Readiness Review: written findings and a practical roadmap, delivered in five business days and credited against implementation work if we continue together. From there we scope an Implementation Sprint or ongoing engineering.
We scope every engagement after understanding the system, business context, and complexity. Most clients start with a focused AI & Data Readiness Review, which is credited against implementation work if we continue together.
AI and data systems usually fail for specific reasons: unclear requirements, weak data flow, missing quality measurement, fragile integrations, or production constraints that were not visible in the prototype. The review gives both sides a clear picture of what is worth fixing before implementation begins.
Norviq works from Central European Time with clients across the US and Europe, with daily overlap for technical calls, standups, and delivery work.
Find out what's keeping your AI out of production.
Book a 30-minute call and a senior engineer will tell you where your AI feature is stuck and what it takes to ship it. No jargon, no commitment.