Automate complex workflows
Connect knowledge, tools, and human decisions so your team can move beyond repetitive handoffs.
AI research & engineering · Tokyo
Research depth.
AI that works in your business.
BitLabs builds AI agents, adapts language models, and delivers secure applications around your workflows, data, and operating requirements. We connect research with the engineering needed to put AI into everyday use.
BITLABS / SYSTEM DESIGN
Your workflow
Relevant context
Model + harness
Permitted toolsHuman approval
Useful action
Evaluate · Observe · Improve
Start with the work you need to improve.
Improve model quality or efficiency
Identify whether better context, fine-tuning, a smaller model, or inference optimization fits your constraints.
Bring a prototype into production
Turn a promising experiment into an application with clear evaluation criteria and an operating plan.
Make the engineering visible.
An illustrative workflow shows how we think about context, permissions, and accountability. It uses synthetic data and is not a client case study or a performance benchmark.
An agent workflow with a human decision point
A synthetic purchase request illustrates retrieval, limited tool access, approval, and evaluation.
Read the annotated workflowSYNTHETIC / 001Illustrative demo · No external actions
- 1
Read the request
Four monitors, ¥30,000 each. Total: ¥120,000.
- 2
Retrieve the policy
Synthetic policy: requests up to ¥150,000. Human approval required before ordering.
SYNTHETIC-POLICY-01 - 3
Draft within tool permissions
Search and draft tools allowed. Ordering and payments denied.
draft_request → pending_human_review - 4
A person decides
Being within budget does not authorize execution. Try either decision.
Waiting for human review.
From model behavior to everyday use.
For us, AI-native design means building workflows around model behavior, context, evaluation, tool access, and human oversight.
Agents & applications
When a workflow spans documents, systems, and decisions.
- What we deliver
- Context retrieval, tool integrations, and interfaces with human oversight.
- How we evaluate
- Task completion, source grounding, and permission boundaries.
Models & training
When general models do not meet domain, cost, or latency needs.
- What we deliver
- Data preparation, model adaptation, and training pipelines where access and licensing permit.
- How we evaluate
- Held-out quality, resource use, and comparison with a simpler baseline.
Production engineering
When an AI system must fit existing operations.
- What we deliver
- Deployment architecture, monitoring, release controls, and handover documentation.
- How we evaluate
- Reliability, access control, recovery, and operating cost.
Agree on what good looks like. Then build toward it.
- 1
Understand the workflow
Map users, data, constraints, and the decisions that need human judgment.
- 2
Establish evaluation criteria
Set a baseline and agree on quality, latency, cost, and failure cases.
- 3
Build and test
Iterate on the model, context, tools, and interface against those criteria.
- 4
Deploy and hand over
Document operations, test recovery, and prepare the people who will run the system.
Security is part of the system design.
We scope controls around your data, risk, and operating environment. Deployment options can include AWS, Azure, and private infrastructure, subject to project requirements.
Data boundaries
Define what a model can see, where data can travel, and what is retained.
Tool permissions
Use scoped credentials and allowlisted actions, with approval for consequential changes.
Monitoring & recovery
Plan trace visibility, incident handling, rollback, and safe failure paths.
Research directions
Research that informs engineering decisions.
Our research directions focus on smaller models, adaptation, agent design, and reliability. These are areas of investigation, not claims of published results.
ResearchBuilt together. Based in Tokyo.
BitLabs is an AI R&D and consulting company based in Tokyo. Our work brings together language model development, agent systems, application engineering, and secure cloud deployment.
Meet BitLabsBring us the problem. We’ll work through the possibilities.
A workflow to improve, a model to adapt, or a prototype ready for its next step.
Discuss your project