AI Implementation
Netsujo Inc. supports generative AI and LLM adoption end to end from Kyoto: identifying where AI genuinely applies to your operations, PoC and prompt design, production implementation, and operational adoption. Pricing starts at an AI Applicability Diagnosis (JPY 300,000, 10 business days) and a concept phase from JPY 500,000–1,500,000.
We take on enquiries from the earliest stage — "how much would AI development cost" or "where do we even start" — and can also combine generative AI with blockchain where transparency and traceability of AI decisions matter.
Three walls companies hit adopting AI
- Which technology to choose
- With generative AI options multiplying, it’s hard to judge which technology genuinely fits your problem rather than chasing the trend.
- Stopping at PoC
- A proof of concept ran, but it never moved into production or organizational adoption — the bridge from technical validation to business outcome is missing.
- Adoption that doesn’t stick
- Operational workflow and staff training after rollout are under-designed, so a promising AI tool falls out of use and the improvement cycle never keeps turning.
What we offer
- AI strategy consulting
- Framing the business problem, selecting the right AI technology, and building an adoption roadmap — generative AI, machine learning, or NLP, matched to the goal.
- AI PoC design and delivery
- PoC design that starts small and validates real effect, built around integration into the actual workflow so it produces a clear path to production.
- AI × blockchain integration
- Recording and proving AI decisions on a blockchain, or building a distributed data foundation for AI — combining the strengths of both technologies.
- Generative AI adoption support
- Bringing tools such as ChatGPT and Claude into daily operations — prompt design, workflow integration, and security measures.
Pricing by phase
| Phase | Price range | Duration |
|---|---|---|
| Concept & applicability | JPY 500,000–1,500,000 | 2–4 weeks |
| PoC & prompt design | JPY 1,500,000–5,000,000 | 1–2 months |
| Production implementation & operation | JPY 5,000,000+ | 2–6 months |
Generative AI API usage (GPT/Claude/Gemini) typically adds JPY tens of thousands to a few hundred thousand per month, separately. You can start small and invest in stages as effect becomes visible, rather than committing tens of millions up front.
Track record and capabilities
- Kyoto University of Art and Design — guest lecture on data science and AI literacy (January 2026)
- Ryukoku University — introductory blockchain seminar
- Multi-LLM support (GPT, Claude, and others)
- AI × blockchain integration
Frequently asked questions
- Where should generative AI adoption start?
- Start with repetitive, time-consuming work — meeting-minute summaries, email drafting, internal FAQ responses, report drafting, and coding assistance tend to show effect quickly. We recommend a business-process inventory (2–4 weeks, JPY 500,000–1,500,000) to build an ROI hypothesis before moving to a PoC, rather than a company-wide rollout on day one.
- What does AI implementation cost?
- Our published ranges are JPY 500,000–1,500,000 for concept and applicability (2–4 weeks), JPY 1,500,000–5,000,000 for PoC and prompt design (1–2 months), and JPY 5,000,000+ for production implementation and operation (2–6 months), plus separate generative-AI API usage costs.
- What kind of work suits generative AI?
- Work that’s text-heavy, has clear judgment criteria and many similar cases, or is research/summarization/translation/classification. Advanced professional judgment, legally binding final decisions, and rare edge cases are not suited to AI alone — a human review step is required by design.
- What should be prepared before AI adoption?
- Prepare three things before implementation: decision criteria after the PoC, how the tool will fit into the workflow, and security and usage guidelines. First define the measurement metric, design workflow integration before building, develop security and usage guidelines in parallel, and assign an internal champion who owns adoption through to habit — treating this as an operating-model change, not a tool rollout.
Enquiries about AI adoption and real-world implementation are welcome.
Talk to us about AI adoption