Internal answers with a source you can check
An employee asks about approved onboarding guidance. A retrieval-augmented generation assistant returns a source link only when that employee can access the document.
Private AI Assistants, Agents & RAG
Find trusted answers in your company knowledge.
Make approved knowledge easier to find and use. Give people answers with source links, respect their access rights and keep agent actions within an agreed mandate.
No one-size-fits-all price. Scope, deliverables and cost are agreed in writing.
Is this your team?
Made for teams like yours.
For knowledge-heavy organisations, support teams and product teams that want AI connected to their own information and permissions.
- Internal questions keep interrupting the same experts, while useful knowledge stays scattered.
- Support or onboarding needs an assistant that can point to approved source material.
- Different users need different access, and a generic chatbot cannot reflect your business rules.
What changes for you
The answer is somewhere in your documents. Your team should not have to search five places to find it.
A private AI assistant pilot that retrieves permitted knowledge, cites its sources and declines unsupported answers. One suitable cloud—Azure, AWS or Google Cloud—is selected for the agreed architecture.
Scope first. Useful work next.
The value, in plain English
Private AI assistant development makes approved knowledge easier to find without giving every user the same access. Enterprise RAG implementation connects an assistant to a ready-to-use source, with citations, clear permissions and an evaluation baseline. Useful answers matter more than confident guesses.
From the first question to a useful handover
Choose the questions worth answering
Agree the source, user roles and pilot tasks. AI document search and an internal knowledge chatbot start with relevant, maintained content and a clear right to use it.
Build retrieval and permissions together
Permission-aware RAG applies access rules before retrieval. Knowledge base integration, source citations and a scoped interface form the assistant; custom AI agent development adds tools only when agreed.
Test before widening access
RAG evaluation checks useful answers, restricted content and unsupported-answer refusal. Prompt injection testing and agreed data-handling checks help inform the rollout decision.
Where this earns its place
Illustrative use cases. The actual work and acceptance checks are agreed in your proposal.
Support knowledge without unrestricted actions
A customer support AI assistant can help staff find approved product information. Drafts and any tool actions remain within the agreed roles and review requirements.
CLIENT FEEDBACK
What our methodology delivers
What to agree for this service
Compare services and prepare your brief ↗Deliverables
- User identity and permissions enforced before retrieval, with separation of clients and sources across embeddings, vector stores, caches and exports.
- Scoped tools, supervised write actions, separation of instructions from untrusted content, and prompt-injection and source-poisoning tests.
- Secret protection, minimal sensitive logging, answer citations, retention and deletion rules, usage and cost controls, security and acceptance tests, and handover.
- Package scope
- Private AI Assistant / RAG Pilot: one assistant, one ready-to-use knowledge source, one interface, one cloud provider, up to two user roles and up to ten pilot users. Agent actions are included only when explicitly described in the written scope.
- What your team provides
- Provide a knowledge source you are authorised to use, accurate role permissions and a pilot owner. Approve data-processing terms, retention, suppliers and hosting region before deployment. Validate the pilot before expanding its use.
- Outside the package
- Multi-cloud, fine-tuning, extensive OCR, production availability commitments and WhatsApp Business are outside the base package. Additional channels, data preparation and integration work are separately scoped.
Acceptance examples to discuss
Illustrative checks for negotiation. These are not completed test results, new contractual promises or additions to the package. The written proposal defines the actual acceptance criteria.
- The agreed restricted-document test denies retrieval and source access to a role without permission.
- Agreed supported questions cite permitted sources; an unsupported question produces the defined refusal or handoff.
Stuck on an AI decision? Get a clear next step.
A focused review of one AI purchase, integration or agent idea. Turn an uncertain decision into a written brief your team can act on.
€490 for one decision. Any applicable VAT and the agreed scope are confirmed in writing before acceptance. Requesting a review is not a purchase or a confirmed booking.
YOUR NEXT MOVE
Get your tailored proposal
Tell us about your organisation, your team and the product or process you want to improve. We will review the fit and follow up with the questions needed to shape a proposal. Scope, deliverables, timing and price are agreed before work begins.
Q&A
Good questions. Straight answers.
What does private mean here?
Access and data handling are scoped for your organisation. The project identifies who processes content, which endpoints receive it, the storage region, supplier data-use terms and processing agreements. Private does not automatically mean EU-only or on-premises.
Is the complete AI chain end-to-end encrypted?
We specify TLS in transit and encryption at rest according to the architecture. We do not describe the complete path to an LLM as end-to-end encrypted without evidence that supports that claim.
What is a private AI assistant pilot?
One assistant, one ready-to-use knowledge source, one interface, one cloud provider, up to two user roles and up to ten pilot users. An enterprise AI chatbot or a document assistant is scoped around a real question set.
What does secure RAG implementation protect?
Secure RAG implementation addresses identity, retrieval permissions and source handling within the agreed architecture. Access-controlled retrieval must also account for vector stores, caches and exports; encryption alone does not establish permission boundaries.
Can we use Azure, AWS or Google Cloud?
An Azure private AI assistant, an AWS private AI assistant or a Google Cloud private AI assistant can be discussed for the chosen architecture. The base pilot selects one cloud; hosting region, supplier terms and retention are agreed before deployment.
Can the agent update systems as well as answer questions?
AI agent tool integration is included only when explicitly scoped. Human-supervised AI agents use limited permissions and approval for sensitive writes. A retrieved document or model answer does not grant authority to take action.
How do you check answer quality?
AI assistant evaluation uses representative questions, expected evidence, citation checks, permission tests and unsupported-answer refusal. RAG evaluation gives a baseline for a rollout decision; it does not promise that every answer will be correct.
Can we add website chat or WhatsApp later?
Website AI chatbot integration and WhatsApp AI integration require separate scope, platform access, data-processing terms and supplier costs. The initial pilot includes one agreed interface, with data retention rules and handover documentation.
Make an informed move.
Practical guides to help your team ask better questions before committing.