SHADOW AI USAGE
46%
employees use unapproved AI (Salesforce)
↑ growing data exposure risk
AVG BREACH COST
$4.88M
IBM Cost of Data Breach 2024
↑ +10% vs 2023
CUSTOM RAG MONTHLY
$650
50-user internal system running cost
↓ vs $3,200 enterprise SaaS
TIME TO DEPLOY
4–8 wks
with clean data and APIs ready
↓ vs 6–18 mo traditional
Why off-the-shelf AI creates a security problem
Every time an employee pastes a customer email into ChatGPT, that content leaves your organisation. OpenAI's data usage policies for non-enterprise tiers allow training on user inputs unless explicitly opted out — and most employees never configure this.
Enterprise SaaS AI tiers offer data isolation at $25–$50 per user per month. A 50-person team pays $15,000–$30,000 per yearbefore any customisation — and the model still knows nothing specific to your business. It cannot answer “what is our refund policy” or “which client is on tier B.”
A custom internal system built on a RAG layer gives you both: data stays in your infrastructure, and the AI knows your company's actual content.
Internal AI options: direct cost and capability comparison
Not every approach fits every company. The right choice depends on compliance requirements, existing infrastructure, and how frequently your internal knowledge changes.
| Approach | Monthly Cost (50 users) | Data Internal? | Knows Your Content? | Update Frequency |
|---|---|---|---|---|
| OpenAI Enterprise | $2,500–$3,500 | Yes (opt-in) | No | Never |
| Azure OpenAI (managed) | $2,000–$2,800 | Yes | No | Never |
| Microsoft Copilot 365 | $1,500–$2,000 | Yes (M365 only) | Partial | Weekly |
| Custom RAG Stack | $500–$800 | Yes, fully | Yes, always | Real-time |
Decision point: If your team regularly works with confidential client data, financial records, or legally sensitive content, the question is not whether to build internal AI — it is whether you can afford to keep relying on consumer-grade tools.
What the build process looks like
The Agency Company builds internal AI systems in four stages. Most deployments are live in four to eight weeks.
Audit your documents and data sources
Identify what you have, where it lives, and what percentage is current and accurate. Most companies discover more usable knowledge than they expect.
Connect to a vector database
Your documents are indexed for semantic search. When a user asks a question, the system retrieves the relevant section before generating a response.
Deploy with a custom system prompt
The language model is configured with your AI's role, tone, and access restrictions — defining exactly what it should and should not answer.
Add role-based access controls
Sales only sees sales content. HR only sees HR content. The AI cannot surface data outside the user's permitted scope.
The result: a private assistant that answers in plain language, cites the exact source document, and never fabricates a policy you do not have.
Sources
- Salesforce State of AI Report 2024 — salesforce.com
- IBM Cost of a Data Breach Report 2024 — ibm.com
- OpenAI Enterprise data policy — openai.com/enterprise-privacy