Security & governance

Trust is an architecture decision, not a feature.

An AI system that can read company information has to know who is asking and what they are entitled to see. That check happens before the model is ever involved.

Server-side authorization

Access rules are applied before retrieval results are used — never delegated to prompt text.

Dedicated environment

One organization per deployment, with its own database, storage and credentials.

Encrypted credentials

Connector tokens and secrets are encrypted at rest and scoped to least privilege.

Human approval gates

Sensitive actions pause for a named approver before anything executes.

Audit logging

Questions, retrieved sources, generated output and approvals are recorded.

No model training

Foundation models are used for reasoning only; your content never becomes training data.

Permission-aware AI

Your AI should know what you know — and what you're allowed to know.

Not every employee should see every piece of company information. Select a role to see how retrieval changes.

Signed in as

CEO

Broad authorized company access

Authorization is enforced before protected information is provided to the AI model.Security is not left to a prompt.

Retrievable

Management
Finance
HR
Sales
Operations

Blocked

Individual employee medical records

Dedicated deployment

This is your company's AI. Not a shared chatbot account.

Every client receives a dedicated AI environment configured specifically for their organization.

Nothing is assembled from someone else's setup, and nothing about the way your business works has to bend to fit a platform.

ABC COMPANY AIDedicated

ABC Knowledge
ABC Users
ABC Permissions
ABC Agents
ABC Connectors
ABC Workflows
ABC Templates
ABC Audit Logs

One organization · One environment · One set of rules

Technical architecture

Under the hood.

Enterprise AI infrastructure, without enterprise complexity for your employees. Expand any layer for a plain-English explanation.

01Company knowledgeDocuments and systems your organization already owns.
02Document processingFiles are read, cleaned and converted into usable text.
03ChunkingLong documents are split into passages that can be cited precisely.
04EmbeddingsEach passage gets a numeric fingerprint representing its meaning.
05Vector storageFingerprints live in PostgreSQL with pgvector alongside metadata.
06Permission filterServer-side rules remove anything the user may not see.
07RAG retrievalThe most relevant authorized passages are assembled as context.
08AI orchestrationThe system decides which agent, tools and model to use.
09GPT / Claude / GeminiFoundation models generate the response from that context.
10AgentA configured specialist responsible for the task at hand.
11ToolAn approved integration the agent may call — email, sheets, CRM.
12ActionThe result: an answer, a document, or an executed step.
13Audit logWho asked, what was retrieved, what was produced, who approved.

In plain language

Instead of asking an AI model to guess what your company knows, the system retrieves relevant authorized information from your knowledge sources and gives the model that context before it writes a single word. The model is powerful; the facts are yours.

No foundation model is trained on your company data. Your information is retrieved at the moment of the request, under your access rules.

Next.js
React
TypeScript
PostgreSQL
pgvector
Docker
Secure API integration
OAuth
Background workers
Object storage

Your company already holds an extraordinary amount of intelligence. It's time to make it accessible.

Let's turn the knowledge, systems and workflows you already have into a private AI workforce built around the way the business actually runs.

Book a Private AI Assessment See what we can build

No generic chatbot · No one-size-fits-all setup · A private environment for one company