Reality Check
Common misconceptions about RAG adoption
Feed internal materials into ChatGPT and it gets smart right away
The moment you upload confidential data to a general-purpose SaaS, the information is sent to an external server. There are NDA-violation and terms-change risks, and you cannot step into the tasks where you truly want value.
Add AI and the effort of search disappears
Adopting only a tool without designing the mechanism means answers with an unclear basis cannot be trusted by the front line. Only when you design it to reference your own drawings and regulations with cited sources does it become usable in real work.
RAG is only for special large enterprises
In recent years, combinations of build templates and cloud have made it possible for mid-sized and small companies to adopt at a realistic cost. There is also room to use subsidies.
Readiness
If this sounds familiar, it is time to consult
The more confidential the task, the more important architectural design becomes — before tool selection.
You are reluctant to entrust confidential data and drawings to external services
A configuration that leverages AI while keeping data inside is possible. We design to fit your security requirements.
Veteran knowledge is concentrated in specific people
We convert tacit knowledge — drawing intent, response know-how, customer characteristics — into a searchable form. We aim for an internal AI dictionary that even new employees can reference.
You do not know where materials are, and time vanishes just searching
We integrate scattered information — specs, regulations, minutes — into a single knowledge base, retrievable instantly with cited sources.
You tried ChatGPT etc., but did not reach full use due to the confidential-data wall
There is an option to resolve the dilemma of “convenient but information control collapses” structurally.
Approach
What we value
In RAG adoption, the two most important things are building the structure that keeps information from leaking out first, and securing answer accuracy that the front line can trust. If either is missing, it becomes an unused system.
We take an approach of first confirming safety and answer accuracy in a small scope, then expanding gradually while reflecting the front line’s voice. This is a shared philosophy with our DX promotion support.
Design premise
Do not bolt security on afterward
Handling confidential data, security is a design premise. We build in the necessary configuration from the initial stage — encryption via KMS, traffic control via WAF, automatic data deletion after a fixed time, and more.
Verify small
Start with a specific department or task, and expand the scope only after confirming that impact occurred.
Make the basis visible
A state where not only the answer but also the referenced materials and basis can be confirmed, making it a mechanism the front line can easily decide with.
TAS GenAI Core
Our technology foundation
At the core of this service, we use TAS GenAI Core, an AI platform we have developed.
Based on the OSS “Gennai” published by Japan’s Digital Agency, it is designed to make minimal modifications to a quality-assured RAG platform and run stably. At the deal stage, you can experience a Gennai-based RAG environment and TAS’s proprietary security mechanism in a sales-demo environment that uses no real APIs or customer data.
Answers with cited grounds
Equipped with a RAG pipeline that references your proprietary data and answers while showing sources. Because the basis of an answer is verifiable, it can be shaped into a form easy to use on the front line.
Automatic answer-quality evaluation
Equipped with a reflection loop that automatically evaluates answer quality and regenerates answers that fall below standard. Aims to suppress what is known as hallucination.
Closed, encrypted, auto-deleted
Combines WAF, CMEK, S3, DynamoDB, and TTL to build in traffic control, encryption, audit trails, and automatic deletion from the initial stage.
The deployment cloud can be selected from AWS, Azure, or GCP to fit your requirements. Even when long-running processing is required, an asynchronous architecture that separates intake and processing runs stably without timeouts.
※ TAS GenAI Core consists of Gennai-derived code (MIT license) and our proprietary code (proprietary).
Process
Adoption flow
We deliver clear deliverables at each phase, keeping it always visible what changed.
Phase 1
Current-state grasp & security-requirement confirmation
We organize which tasks and which data to let the AI reference. Data confidentiality and constraints from NDAs and internal regulations are always confirmed at this stage.
Phase 2
Environment setup
We cleanly build a private cloud area dedicated to you. The cloud used is selected to fit requirements; if a subsidy is used, we advance the application in line with this phase.
Phase 3
Knowledge learning (RAG build)
We ingest specs, drawings, contracts, etc., into a state that can answer with cited grounds. We confirm accuracy with real data before moving to full operation.
Phase 4
Rooting & company-wide rollout
Starting from the department where impact occurred, we gradually expand to other departments — sales, development, general affairs. With screens and procedures that prevent users from getting lost, we aim for a state everyone uses daily.
Cost Support
About subsidy use
Secure RAG build and consulting costs may be eligible for digitalization / AI-adoption subsidies. Depending on the scheme, a substantial portion of the build cost may be covered.
Alongside Secure RAG development support, we can consult on subsidy eligibility and organizing information needed for application preparation. However, subsidies involve screening and selection is not guaranteed. They are also paid in arrears, so the adoption cost must be advanced.
About subsidy application support
Our subsidy application support is currently in preparation (business registration and support structure). We are accepting consultations on confirming schemes, assessing eligibility, and preparing for applications. Formal application representation and post-selection procedures will begin once our structure is ready.
Frequently asked questions
Q. Can we feed this data of ours into the RAG?
A. Suitability depends on the data’s form and confidentiality classification. In the initial hearing we hear the target data and tell you learnability and expected accuracy.
Q. Does the information really not go out?
A. We adopt a configuration in which processing completes within a closed cloud environment dedicated to you. We build in encryption, traffic control, and automatic deletion, designing so that a path to the outside is structurally not created. Specific requirements are confirmed individually.
Q. We have no IT lead — is that okay?
A. No problem. We accompany you through build, operation, and rooting. The operation screen is designed simply, and procedures are prepared.
Q. Can we start with just one task?
A. Yes. We recommend an approach that starts small with a specific department or task and expands after confirming impact.
Start with a free preliminary hearing
Can this data be used for RAG, and is it eligible for a subsidy? Tailored to your situation, we propose an individual estimate and configuration. The first hearing is about 30 minutes and can be held online.