From "trying AI"
to running your business on it.
From shaping your AI strategy to building AI agents and systems, and improving them after launch. We help you take AI beyond the PoC, starting with an assessment.
Do any of these sound familiar?
We cover the full path from strategy through build and operations.
"Use AI," they said — but where do we start?
You have tried ChatGPT, but lack the evidence to decide where AI would actually pay off in your business.
The PoC works, but never sticks in production
The demo ran, but accuracy, operations, and security concerns keep blocking the move to production.
AI tools were rolled out, then quietly abandoned
Usage never took off, ROI is hard to explain, and nobody owns the improvement loop.
You want AI coding, but not just licenses
Handing out Claude Code or Copilot alone does not move the needle — the team needs a designed way of working.
- A company where AI is a stated executive priority, but no one internally can drive it
- A company that wants to take PoC-stage AI projects all the way to production
- A company with 10–300 people automating routine work such as inquiries, document processing, or reporting
- A SaaS company or agency introducing AI coding / agentic workflows to raise developer productivity
- A company expanding AI services into the Chinese market (Alibaba Cloud / Chinese models)
What we offer
From strategy to operations — engage us for only the phases you need.
AI adoption consulting
From inventorying your workflows and identifying where AI applies, to ROI estimates and an adoption roadmap.
- Workflow inventory and AI opportunity mapping
- ROI estimation and prioritization
- Tool and model selection (Claude / OpenAI / Gemini / local LLMs)
- Internal AI usage guidelines and security policies
- Executive briefing materials and approval support
AI agent & system development
From requirements through design, implementation, testing, and production release — we build systems with AI inside.
- Internal knowledge search and RAG systems
- Business AI agents for inquiries and document processing
- Automation integrated with Slack, Google Workspace, Notion, and more
- Adding AI features to existing systems (API integration)
- Multi-agent design with MCP / Agent SDK
Agentic workflow / AI coding design
We design development and business workflows that actually run on AI — not just tool rollouts.
- Claude Code / AI coding adoption design (skills, subagents, hooks, CI integration)
- AI in code review, testing, and deployment
- Agentizing business workflows (autonomous routine tasks)
- Standardized prompt and context design, internal templates
- Hands-on training for development teams
AI Ops / continuous improvement
We keep improving accuracy, cost, and adoption after launch — monthly, alongside your team.
- Accuracy and response-quality monitoring (evaluation infrastructure)
- LLM cost optimization (model selection, caching, prompt improvements)
- Usage visibility and internal adoption support
- Keeping pace with model updates and new capabilities
- Incident response and security monitoring (with our security assessment)
We are vendor-neutral — no tool reselling; we design the right architecture from both the business and technology sides. We select from Claude, OpenAI, Gemini, and local LLMs based on your requirements, cost, and security constraints.
Three steps from assessment to operations
AI is not build-and-done. We work in three steps — assess, build, operate — and stay until the results show.
Assess
We interview your workflows, data, and systems to map AI opportunities and ROI. Where, what, and in which order — delivered as a report.
Build
Based on the assessment, we build AI agents and systems starting from the highest-priority areas — built small, verified, then moved to production in stages.
Operate
After release, we improve accuracy, optimize cost, and drive adoption on a monthly basis — keeping your system current as models evolve.
How we work
The first consultation is free. We review your business and current AI usage, then propose the right entry point.
Consultation
We review your business, current AI usage, systems, and team structure.
AI Assessment
We inventory workflows and data, then report AI opportunities, priorities, and ROI estimates.
Proposal
Based on the assessment, we propose scope, schedule, and cost.
AI Build
Design, implementation, testing — showing working software every 2–4 weeks.
AI Ops
After production release, we improve and operate monthly.
"Build and done"
is not how we work.
From strategy-stage reports to a working system to post-launch improvement reports — every phase leaves you with tangible deliverables.
- AI Assessment report (opportunity list, ROI estimates, adoption roadmap)
- Requirements and system design documents
- Working AI agents / systems (source code included)
- Operations manual and internal user guide
- Monthly improvement report (with an AI Ops contract: accuracy, cost, usage)
Service plans
Assessment, Build, and Ops. Start from whichever phase fits where you are today.
AI assessment
For companies that want to see their current position first.
- AI Assessment report
- Adoption roadmap
- Prioritized initiative list
AI build
We build the AI agents and systems your assessment calls for.
- A working AI system
- Design documents
- Operations manual
AI operations
We keep your AI delivering results.
- Monthly improvement report
- Implemented improvements
Assessment-only and Build-only engagements are welcome. We start by reviewing where you are and propose the right entry point.
What makes Trustray different
Strategy, implementation, operations, and security — every phase of AI adoption from one partner.
AI adoption with security built in
Designs aligned with the OWASP LLM Top 10 and Top 10 for Agentic Applications eliminate AI-specific risks like prompt injection and over-privileged agents from day one. Combined with our security assessment, adoption and defense come from a single partner.
We ship working software
Not slideware — we implement in-house, showing working software every 2–4 weeks, which keeps rework low.
Hands-on agentic know-how
We run Claude Code, MCP, and multi-agent setups in our own daily work, and only propose configurations that actually hold up.
China market & Alibaba Cloud
Trilingual support in Japanese, English, and Chinese. Ask us about AI services for the Chinese market and builds on Alibaba Cloud.
Frequently asked questions
We are not tied to any vendor. We select from Claude, OpenAI, Gemini, and local LLMs based on use case, cost, and security requirements.
We design for that: data classification and masking, training opt-out settings for API usage, and local LLM configurations where needed.
Yes. You can start with an assessment only, or agentize a single workflow.
We integrate with Slack, Google Workspace, Notion, kintone, other SaaS, and your in-house systems via API.
Start by finding out what AI can do for you.
"We do not know where to start" is a fine place to start. The first consultation is free — we review where you are and propose the scope and approach for an AI Assessment.