A model wrapper
Calls a hosted model and ships a thin interface. When cost, latency, privacy, or quality breaks, there is nothing deeper to fix.
Tokyo Deep-Tech AI Lab
Enterprise AI, engineered to betrained
A Tokyo deep-tech lab. From model weights to production, every layer our own.
Five disciplines, done deeply
We don't wrap someone else's API. We pre-train and fine-tune models with JAX and Unsloth, build agentic systems and RAG on Claude Agent SDK, LangChain, LangGraph, and Codex, run production inference, evaluate everything we ship, and engineer the harness that keeps agents safe to run.
Pre-train & fine-tune
Agentic systems & RAG
Scale, integrate, deploy
Evals & quality
Harness engineering
End to end
We are not AI model wrappers
Most “AI companies” call someone else’s model API and wrap it in a UI. BitLabs owns the entire stack, from the GPU infrastructure to the application that runs on it. Every layer is ours to design, tune, and operate.
BitLabs
Owns infrastructure, models, inference, and the application. We tune the whole system, not just the prompt, so it holds up in production.
The full stack
Layer 04 / Application
Agents & applications
The product your team actually uses: AI agents, RAG, and custom apps built around your workflow.
Layer 03 / Models
Models
Pre-trained from scratch with 5D parallelism or fine-tuned, open or closed source, shaped to your task and data.
Layer 02 / Inference
Inference & serving
High-throughput serving with tensor and pipeline parallelism: runtime, tooling, and orchestration.
Layer 01 / Infrastructure
Infrastructure
Secure cloud and GPU foundations, provisioned and operated for real production load.
Expertise
Deep-tech AI expertise, from model weights to production
BitLabs goes deep on model training with JAX and Unsloth, agentic systems and RAG on Claude Agent SDK, LangChain, LangGraph, and Codex, and production-level enterprise deployment. We are not just builders. We are experts in evaluation, and we use it to keep improving quality after launch.
Production-level enterprise AI
We build, scale, integrate, and deploy AI systems around your real systems, approvals, and data boundaries, then evaluate them before and after release.
Model pre-training & fine-tuning
We pre-train LLMs and SLMs at scale with 5D parallelism, closed or open source, and fine-tune with modern techniques including JAX and Unsloth, scored against task benchmarks, not guesswork.
Agentic systems & RAG
We build sophisticated multi-agent solutions and RAG pipelines on Claude Agent SDK, LangChain, LangGraph, and Codex, evaluated on traces you can audit.
How we work
From your problem to a deployed AI system
We map the whole path up front so the big decisions stay aligned.
01
Your problem
02
Data boundary
03
Model strategy
04
Inference stack
05
Agent workflow
06
Evaluation
07
Secure deployment
Security & Deployment
Built for production from day one
We design data handling, access, and release checks into the first architecture pass.
- Private or regional deployment with clear trust boundaries
- Controlled model access, tool use, and sensitive data handling
- Release checks for regulated, high-accountability environments
Research
The lab behind the delivery
Our production work is grounded in ongoing research on pre-training, fine-tuning, inference, and agent reliability.
Pre-training
Training models from scratch
Models built for the task, not borrowed and forced to fit.
Fine-tuning
Adapting open and closed models
Changes you can measure before release.
Inference
High-throughput serving
Predictable performance under real load.
Agents & RAG
Reliable agentic systems
Agents that stay useful and in control.
Platforms
Microsoft Azure
AWS
Anthropic
OpenAI
Experts in enterprise AI, on the platforms you run
We build and deploy on Microsoft Azure, AWS, Anthropic, and OpenAI, matching the model and infrastructure to what your enterprise already relies on.
Talk to us