LLM Fine-tuning · RLHF · Model Evaluation · Full-stack AI Engineering
From rubric design to production deployment, we handle every stage of the AI lifecycle.
We design structured evaluation rubrics tailored to your model's task, scoring accuracy, tone, safety, and instruction-following against expert-defined criteria.
Selected work that shows what we have built across AI systems, product engineering, and digital design.
Real results from real teams. Here is what our clients say about working with Nomos Insights.
"iCJ transformed how my patients track their nutrition. The food recognition is incredibly accurate, and the interface makes diabetes management feel effortless."
Elke Austenat
German Doctor and Author
"The Nomos team built our entire platform in record time. Clean code, excellent communication, and they truly understood our vision."
Carolin Holat
Senior Engineer
"Working with Nomos Insights felt like having an extension of our team. They delivered quality work on time and handled complex challenges with ease."
Harsh Rajani
Senior Software Engineer, Google
"TrackMailBox completely changed how I follow up with prospects. Knowing exactly when they open my emails helps me time my follow-ups perfectly."
Sarah Chen
Sales Director, TechFlow Solutions
From LLM fine-tuning to production deployments, everything your AI product needs to ship and scale.
AI engineering and automation built for scale.
We bring together model training, automation, and cloud engineering to help teams build smarter products. From fine-tuned LLMs to production-grade infrastructure, our work spans the full depth of what modern AI requires.
We build custom SFT and RLHF pipelines to train models on your proprietary data. The result is tighter alignment, better accuracy, and capabilities tuned to your domain.
We design evaluation rubrics and run red-teaming sessions to benchmark your model against real quality standards. Nothing ships until it performs.
Our human-in-the-loop validation pipelines have expert annotators reviewing outputs for factuality, safety, tone, and task accuracy. Quality at scale, not just at launch.
Good models start with good data. We source, filter, and annotate datasets for supervised learning and generation tasks so your training pipeline starts clean.
We build autonomous agents and multi-agent systems that reason, plan, and execute complex tasks with minimal oversight. LLM-powered workflows built to run in production.
We ship full-stack web and mobile products using React, Next.js, and React Native. Clean architecture, tested code, and production-ready from day one.
We handle AWS, Azure, and GCP deployments with CI/CD pipelines, infrastructure as code, and DevOps automation built for teams that need reliability.
We help you work through architecture decisions, pick the right tech stack, and assess AI readiness at each stage. Better decisions earlier means less refactoring later.
SWE-bench changed how the world evaluates AI coding ability. But turning a real GitHub bug report into a fair, reproducible test for an AI agent is surprisingly complex. This is how it actually works, step by step.
Pass or fail only tells you if an AI agent solved a problem. It tells you nothing about how it reasoned, where it went wrong, or what made one agent dramatically better than another. Here is what we found when we looked inside the trajectories.
Discover how intelligent AI agents can automate workflows, enhance decision-making, and drive significant productivity gains for your business.
Nomos Insights is a specialized AI training and engineering firm. We partner with companies that need more than code. They need models that learn, agents that act, and systems that scale. From RLHF pipelines to production software, we handle it all.
We architect systems from the ground up with model behavior, data pipelines, and inference optimization built in from the start. Every system we build is designed to train, adapt, and improve over time.
From dataset curation and model fine-tuning to deployment and monitoring, we own every layer of the stack. No handoffs between vendors. One team, full accountability.
Clear milestones and structured project management throughout. You get clean, documented code and models you can interpret and build on. We deliver work that holds up at scale.
We run HITL (human-in-the-loop) processes that combine expert annotation with automated pipelines, ensuring quality at every training iteration, not just at the start.
