Operix01 / CONTEXT
Common challenges
- A demonstration looks promising, but no owner can define the production decision
- Answers lack reliable sources or use outdated internal documents
- Confidentiality and user access rules are unclear
- Human review takes as long as the original work
02 / SCOPE
Scope of support
We start with the business decision and operating responsibility rather than a general chatbot. Source ownership, access rules, evaluation questions, human review, and stop conditions are designed before wider use.
- Use-case definition tied to a real workflow and accountable owner
- Knowledge-source inventory, ownership, versioning, and access design
- Evaluation set covering frequent, ambiguous, unsupported, and restricted questions
- Human review, escalation, feedback, monitoring, and stop procedures
Use cases
- Internal policy and procedure search
- Drafting responses with cited source material
- Summarizing controlled document collections
- Assisting classification and review while retaining human approval
How we work
- Define the user, task, decision, and unacceptable failure
- Review source documents, ownership, versions, and access
- Create representative evaluation questions and expected evidence
- Prototype within restricted users and data
- Measure answer quality, citations, review effort, and risk
- Decide whether to continue, revise, narrow, or stop
Who this is for
- Teams that have tested AI but cannot move to daily operation
- Organizations that need evidence and access control
- Companies prepared to assign content and operating owners
03 / HANDOVER
Deliverables
Deliverables are agreed for the project scope.
- 01Use-case and risk definition
- 02Knowledge-source and permission design
- 03Evaluation dataset, criteria, and results
- 04Operating guide, review checklist, monitoring, and stop procedure
04 / IMPLEMENTATION
Implementation considerations
Begin with a decision, not a chatbot
A useful demonstration does not prove the workflow is ready. We define who uses the output, what decision it supports, what evidence is required, and what happens when the system is uncertain.
If existing search or a clearer document structure solves the problem with less risk, generative AI is not forced into the design.
Treat source quality and permissions as product requirements
Duplicate, obsolete, and ownerless documents weaken the answer before model selection matters. Each source needs a system of record, owner, effective date, and access classification.
Retrieval must respect the user's permissions. Administrator access is not a reason to expose the same sources to every user.
Evaluate production behavior with representative questions
The evaluation set includes common, multi-condition, unsupported, outdated, contradictory, and unauthorized questions. Expected answers and evidence are reviewed by people who understand the work.
Quality includes citations, omission of critical conditions, refusal when evidence is absent, and the time a reviewer needs—not only fluent wording.
| Question type | Purpose | Evidence to record |
|---|---|---|
| Frequent | Daily usefulness | Answer, source, review time |
| Multiple conditions | Critical omissions | Coverage of each condition |
| No supporting information | Behavior under uncertainty | Can it avoid an unsupported claim? |
| Unauthorized | Access enforcement | Can it refuse correctly? |
| Old or conflicting sources | Version control | Does it select valid information? |
Design human review and the stop procedure
The workflow identifies who reviews the output, what they compare, and when approval is required. If every answer must be researched from scratch, the proposed benefit may not exist.
Serious errors, inappropriate use of confidential information, excessive review effort, or uncontrolled cost can trigger narrowing or suspension. Production ownership includes feedback, reevaluation, model changes, and incident response.
05 / FAQ
Frequently asked questions
Do you guarantee answer accuracy?
No. We define and measure quality for the selected workflow, retain appropriate human review, and document limitations and stop conditions.
Can internal confidential documents be used?
Potentially, after confirming storage, external transmission, model settings, user permissions, logs, retention, and contractual conditions.
Do we need perfectly organized documents first?
Not perfectly, but source ownership, validity, duplicates, and access must be sufficiently controlled for the intended use.
What is the outcome of a proof of concept?
A decision to continue, revise, narrow, or stop, supported by evaluation results, remaining risks, owners, and the next review date—not only a demo.
06 / REFERENCES
References
Check current official documentation when assessing methods and operating conditions.
- Ministry of Economy, Trade and IndustryAI Guidelines for Business, version 1.2 ↗
- Information-technology Promotion Agency, JapanCybersecurity guidelines for SMEs, version 4.0 ↗