We build production-grade AI systems — autonomous agents, fine-tuned LLMs, and decision platforms that turn ambition into infrastructure.
[ A studio building intelligence as infrastructure ]
Every model is evaluated, red-teamed, and benchmarked before it touches production.
We don't ship notebooks. We ship services with SLOs, monitoring, and on-call rotations.
Success is measured in retained users and revenue — not model benchmarks.
A full-stack AI practice — from foundation models to guardrails. We deploy what we design, and operate what we deploy.
Custom fine-tuning, RAG systems, and production deployment of GPT-, Claude-, and open-source models with evaluation harnesses.
Planning, tool-using agents that execute complex enterprise workflows — from research to scheduling to code generation.
Training clusters, vLLM inference servers, monitoring, and CI/CD for ML — built for teams shipping at enterprise scale.
Embedding pipelines, hybrid search, and vector databases that power retrieval-grounded intelligence.
Red-teaming, guardrails, hallucination suppression, and regulatory alignment for high-stakes deployments.
Detection, segmentation, OCR, and multimodal understanding — deployed to edge and cloud.
Behind every deployment is a team obsessed with latency, reliability, and the quiet victories of production AI done right.
Three leaders. Three disciplines. One obsession: shipping AI that earns its place in production. Meet the operators architecting ReimeiTech's edge.
"We're not chasing AGI. We're building the infrastructure that runs under it."
15+ years shipping ML at Google Brain and Tokyo Financial Hub. Kenji believes intelligence is not a product — it's a posture. He leads ReimeiTech's thesis on building AI that outlives the companies that ship it.
"If you can't measure alignment, you haven't shipped it."
A distributed-systems engineer with deep roots in ML infrastructure, Satomune architects every system ReimeiTech deploys — from token budgets to evaluation harnesses. He ensures reproducibility is never sacrificed for velocity.
"Hiring is a systems problem. Build the pipeline, the people follow."
With over 6 years of experience in talent acquisition and HR operations, Vira specialises in aligning recruitment strategies with business objectives. She has a strong track record of transforming manual and fragmented hiring processes into structured, scalable, and data-driven systems — including the implementation of applicant tracking systems and automated hiring pipelines.
Ready to deploy AI that matters? Write to us with a rough brief — we'll respond within one business day with next steps.
