Problem
Three failure patterns in AI adoption
Introduced but unused
Adopting AI with a “let’s just try AI” approach, without analyzing the front-line workflow.
AI answers cannot be trusted
With no way to see the basis of an answer, the front line cannot use it for decisions. There is no countermeasure against hallucination — AI confidently stating things that are untrue.
Unclear whether it is working
Without measuring pre-adoption task time and quality, there is no baseline to compare improvements against.
Approach
Start with a diagnosis
The most important decision in AI adoption is “where to introduce it.” We begin with a current-state analysis, identify the areas where impact is visible, and then propose a plan.
Step 1
Workflow hearing
1–2 days
We interview both management and the front line. We visualize each department’s workflow, tools in use, and pain points. We especially identify “tasks where information search takes time” and “tasks that rely on individuals.”
Step 2
AI suitability diagnosis
3–5 days
Based on the hearings, we assess each task’s suitability for AI. We prioritize areas with high impact and low adoption barriers. Confidential-data handling requirements are also confirmed at this stage.
Step 3
Adoption plan delivery
1 week
We deliver a plan covering target tasks, recommended tools, adoption schedule, cost estimate, and expected impact. No contract is required at this stage. Understanding your current state is the starting point.
Before / After
Before and after adoption
What changes, in concrete tasks, before and after AI adoption. Below are examples commonly seen in typical organizations.
Searching internal documents
BEFORE
Searching past materials and manuals by hand. Verification takes time, and outdated versions are sometimes referenced.
AFTER
Answers are generated that cite the source document and relevant section. The basis is verifiable, so the output can be used directly in work.
Replying to inquiries
BEFORE
The person in charge checks regulations and manuals each time before replying. Answers vary, and explaining the basis takes time.
AFTER
Answers based on regulatory documents are auto-generated with cited sources. The basis can be shown, meeting accountability.
Invoice data entry
BEFORE
Invoices on paper/PDF are entered into the accounting system by hand. 5–10 minutes per item. ~20 hours for 200 items/month.
AFTER
OCR + AI auto-extracts invoice data. Entry into the accounting system is confirmation only. Compressed to 3–4 hours/month.
Quality & Security
Answer quality and data safety
Commitment to quality
AI with visible grounds
Every AI-generated answer is annotated with the source document name and the relevant section. Because the basis is verifiable, we pursue a quality level that lets front-line staff use it directly for business decisions.
We adopt a mechanism that automatically evaluates answers from multiple perspectives — accuracy, completeness, relevance, and consistency — and regenerates answers that fall short of the standard, working to guarantee output quality.
Data protection
Client data is encrypted at rest with restricted access. When handling confidential information, a configuration that keeps data within the internal environment while operating AI is also possible.
Avoiding vendor lock-in
We adopt a design that does not depend on a specific cloud provider. Because it adapts to your existing infrastructure, future migration costs are kept low.
Scope & FAQ
Scope and frequently asked questions
What we cover
- +Visualizing workflows and identifying issues
- +Prioritizing task areas with high AI suitability
- +Designing and operating answer-quality evaluation criteria
- +Selecting and piloting recommended tools
- +Front-line operation training and manual creation
- +Post-adoption impact measurement and improvement proposals
What we do not cover
- -We do not steer you toward a specific vendor’s products
- -We do not make expert legal, tax, or labor judgments
- -We do not force proposals for out-of-scope tasks
- -We do not push company-wide adoption from a single hearing
Frequently asked questions
Q. What happens if the AI gives a wrong answer?
A. Because every answer is annotated with its source, the person in charge can verify the basis. We also build a quality-evaluation mechanism that auto-detects inaccurate answers and regenerates them.
Q. I am uneasy about letting AI read confidential materials.
A. A configuration that keeps data within your internal environment is possible. We can build an AI environment that completes internally without sending data to an external cloud.
Q. Is it possible to stop at the diagnosis?
A. Yes. If the AI suitability diagnosis shows that AI adoption is not appropriate at this time, we tell you straight. We do not force proposals.
Q. Do you recommend a specific AI tool?
A. We have no vendor tie-ups. We select tools objectively based on your business requirements, budget, and existing infrastructure.