Ragate 生成AIの全社導入支援
: How to use it, features, and the business problems it solves
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What is Ragate 生成AIの全社導入支援?
An AI consulting service for company-wide generative AI adoption, launched on October 5, 2026 by Ragate, Inc. (Chuo-ku, Tokyo), an AWS Advanced Tier Services Partner. A single team handles taking stock of business tasks and the company-wide vision, designing AI usage policy, data classification and audit, building the execution environment, and working alongside the frontline in four two-week sprints. Pricing is quoted individually (not disclosed). For companies that want to try one task first, the "AX Sprint Program" offers two months of basic support free of charge (AWS usage fees etc. are extra).
Business problems it solves
About "Ragate 生成AIの全社導入支援"
What is Ragate 生成AIの全社導入支援 (Ragate Company-wide Generative AI Adoption Support)?
Ragate 生成AIの全社導入支援 is a service that Ragate, Inc. (ラーゲイト, Chuo-ku, Tokyo) launched on October 5, 2026. It is a generative AI adoption consultancy in which a single team supports everything from taking stock of business tasks to setting up usage rules and the execution environment, through to embedding AI in day-to-day work. One cycle consists of four two-week sprints (two months in total), and cycles are repeated while swapping in new target tasks.
Ragate is an AWS Advanced Tier Services Partner. It says the execution environment is built primarily on AWS, with Google Cloud, Microsoft Azure and local LLMs also supported.
Pricing is not published. The official FAQ says Ragate will "confirm the scope, the roles needed and platform usage fees, and then present the support content and cost for each sprint." For companies that first want to try AI on a single task, there is the "AXスプリントプログラム" (AX Sprint Program), whose basic support is free for two months (AWS usage fees and add-on menus are charged separately).
Service overview
How the engagement works
Ragate describes one cycle as taking stock of tasks → four sprints → review. After the review, the team returns to the task inventory (business backlog) to swap in or add new target tasks.
- Sprint 1 (2 weeks) — Inventory business tasks and development processes and turn candidates into a backlog. Agree on scope and owners
- Sprint 2 (2 weeks) — Update priorities on three axes (expected impact, ease of implementation, risk) and design usage rules and the target state
- Sprint 3 (2 weeks) — Build a PoC for the target task and the execution environment it needs, and check quality and safety
- Sprint 4 (2 weeks) — Trial it on site, measure impact and improvements, and confirm conditions for production
- Cycle review — Measure results and decide the targets and team for the next cycle. From the second cycle on, work moves toward standardization, roll-out and in-house ownership
Each sprint starts with a Day 1 kickoff to agree on scope and deliverables, followed by interviews, analysis and implementation on Days 2–9, and a Day 10 review to decide the next scope. Before starting, the client is asked to appoint a lead (a "champion") who coordinates departments and gathers information. As a guide, the lead spends about 30–40 hours over the two months and each participating member about 15–20 hours.
Source: Ragate 生成AIの全社導入支援 official site (all images on this page are from that site)
Service menu
01Vision and planning
Take stock of management policy and each department's work, and produce the company-wide AI vision, roadmap and materials for investment decisions.
- Typical deliverables — AX vision, task inventory, priority matrix
02Governance and execution environment
Design the company-wide AI usage policy, data classification and audit, and select, procure and build an AI execution environment that meets requirements such as closed-network connections, no use of data for training, and domestic regions.
- Typical deliverables — Usage policy, logical and physical architecture, IaC (infrastructure as code)
- Main supported products — Models and platforms such as Amazon Bedrock, Claude, OpenAI, Google Gemini, Dify and LangChain; local LLMs such as Ollama, vLLM and LM Studio; AI coding tools such as Kiro, Cursor, Claude Code and GitHub Copilot
03Working alongside the frontline
Repeat two-week sprints with each department to trial, improve and embed AI, including training in-house instructors.
- Typical deliverables — Working apps and PoCs, impact measurement, training materials
Six deliverables are produced during the engagement: a layer map, an evaluation sheet, usage rules, architecture diagrams, an impact estimate and an operating structure chart. The launch press release says they are handed over not as reports but as editable diagrams, tables and configuration files that can keep being used in-house after the engagement ends.
The figure on the right is an example of the layer map. Work is inventoried across five layers — organization, business processes, applications, data and platform — to decide where to start.
Pricing
Pricing for the company-wide adoption support is not published (as of October 2026).
| Menu | Price | Notes |
|---|---|---|
| 生成AIの全社導入支援 (company-wide adoption support) | Not disclosed (custom quote) | Support content and cost per sprint are presented after confirming scope, roles needed and platform fees |
| AX Sprint Program (basic support) | ¥0 (free under a campaign) | Two months, four two-week sprints. Task inventory and evaluation, a prototype AI usage policy, building and trialing one standard PoC, impact estimate, AX STUDIO setup and training, biweekly reviews and chat consultation |
| AX Sprint Program add-on menus | Paid, custom quote | Up to three PoCs in total (including the standard one) can be considered as an add-on |
| Support after the AX Sprint | Paid | Scope and cost agreed in two-week units |
| AWS usage fees | Actual cost (paid by the client) | Separate from basic support. Model, search/storage and other service costs are estimated before starting |
The AX Sprint Program is a trial package to "prototype and validate AI for your work in two months." On Ragate's side, a consultant and a tech lead take part, with a combined commitment of about one day per week. No end date has been set for the campaign, and the scope and conditions are fixed in an agreement before starting. Production operation and maintenance, large-scale integration with existing systems, a company-wide control platform, security audits and formal, legally reviewed policies are outside the scope of basic support. Clients are in principle asked to cooperate with a published case study, but if that is not possible it can be discussed individually, and Ragate says it will not turn a client down solely because a case study cannot be published.
The company-wide FAQ on Ragate's corporate site says a small PoC starts from around ¥500,000 and a monthly advisory contract from ¥1 million per month (whether tax is included is not stated; these are not stated as prices for the company-wide adoption support).
The official site does not mention subsidies that can be used for consulting fees.
Track record and case studies
01Company case studies
The "Works" page of the corporate site lists 21 case studies (as of October 2026). They include cloud infrastructure and system development projects and are not case studies of the company-wide adoption support itself.
- Generative AI cases — Joint proposal and development of a large AI adoption project for a government agency (NHN Techorus, September 2026); support from AX strategy to building AI-driven development capability during a government system renewal (Cube System, March 2026); an Amazon Bedrock × Dify hands-on workshop (LTS, August 2025)
02Certifications and awards
- AWS — AWS Advanced Tier Services Partner, AWS Rising Star Partners of the Year – Japan award, AWS FTR (Foundational Technical Review) certification
- Information security — ISO/IEC 27001:2022 (ISMS) certified (scope: system development)
The company-wide adoption support only started on October 5, 2026, and no client counts or results for this service have been published yet.
How it differs from other AI consulting and adoption support
Compared with other companies that help embed generative AI across an organization:
| Company / service | Operator (listing) | Scope | Pricing (published) |
|---|---|---|---|
| Ragate 生成AIの全社導入支援 | Ragate, Inc. (unlisted) | Strategy, PoC, development, adoption | Not disclosed. Basic support in the AX Sprint Program is free under a campaign |
| JAPAN AI CONSULTING | JAPAN AI, Inc. (parent Geniee is listed on TSE Growth) | Strategy, PoC, development, adoption | Not disclosed (first consultation free) |
| ギブリー AIイネーブルメント | Givery, Inc. (unlisted) | Strategy, PoC, development, adoption | Consulting not disclosed. AI advisory from ¥330,000/month (tax incl.) |
| AVILEN AI戦略コンサルティング | AVILEN Inc. (TSE Growth) | Strategy, PoC, development, adoption | Not disclosed |
| AIパートナーズ AI導入支援 | AGENT, Inc. (TSE listed) | Strategy, PoC, development, adoption | Not disclosed |
Columns for other companies reflect the content on each product page as of its check date.
What sets Ragate apart is that the same team that writes the rules and works with the frontline also builds the company-wide generative AI platform on AWS (including authentication, search and audit) and local LLMs, and that it offers a free entry point (the AX Sprint Program) for trying a single task. If you want to work on a vendor's own AI platform, consider JAPAN AI CONSULTING; if you want to compare published monthly advisory fees, consider ギブリー AIイネーブルメント. Other companies are listed in our comparison of AI consulting and adoption support companies.
Who it suits and who it doesn't
It suits companies that want generative AI to go beyond trials in a few departments and to spread it department by department while putting usage rules and a company-wide platform in place. It also fits companies that cannot send confidential data outside and are considering a closed network or local LLMs, and companies already on AWS. If you want to check the effect on one task before spending money, you can start with the AX Sprint Program.
It is less suited to companies that want to narrow down vendors by looking at price lists, or that choose by the number of clients for this specific service. Pricing for the company-wide support is not published, and because the service only started in October 2026, no client count has been published. You also need to appoint an internal lead and set aside about 30–40 hours over two months.
FAQ
How much does Ragate's company-wide generative AI adoption support cost? Pricing is not published. The official FAQ says Ragate presents the support content and cost for each sprint after confirming the scope, the roles needed and platform usage fees (as of October 2026).
Can I try it for free? Yes. Basic support in the AX Sprint Program, which prototypes and validates AI on one task, is free for two months under a campaign. AWS usage fees, internal staff time, add-on menus and continued support after completion are extra, and no end date has been set for the campaign.
Can I use it without AWS knowledge? Yes. The official FAQ says Ragate handles platform design and technical decisions, while the client shares business information and takes part in decisions.
Does it support clouds other than AWS, or local LLMs? Yes. It is built mainly on AWS but also supports Google Cloud and Microsoft Azure, and where confidential data cannot leave the company, closed-network or on-premises local LLMs are considered.
The information on this page is based on what was published on the official site as of October 2026. Please check the official site for the latest pricing and details.
