PROTECTED ENVIRONMENT
Internal AI
Company documents, CRM, ERP and databases. The model uses data authorized under the user's identity.
No uncontrolled internet accessALTAMENTE DIGITAL / ARCHITECTURE AND INTEGRATION
Secure enterprise AI
Company data inside.Public information from the internet.
Access for authorized users only.
Make company knowledge accessible, automate analysis and use current public information. With rules that determine who can use which data and where it may be processed.
ALTAMENTE designs and integrates AI environments where technical controls govern access and data flows. Security must not depend solely on a model following instructions.
01 / DATA FLOW BOUNDARIES
Internet access. Without company secrets.
Internal processing and public search are separated. Only a query approved under organizational policy may cross the security boundary.
ENFORCED SECURITY BOUNDARY
Security & Declassification Layer
Identity, classification and policy determine what may leave. Declassification is the controlled release of specific information, not automatic removal of protection.
Allow | modify | internal only | denySEPARATE ENVIRONMENT
Public Research
Public websites, search and approved APIs. No permission to access internal documents, accounts or systems.
Approved public query onlyReturn through content checks
Internal synthesis
Public results return as untrusted content. They may be combined with authorized internal data only inside the protected environment.
If a query cannot be shown to be safe, it stays internal, is denied or is referred to an authorized person. Semantic checks support the decision. They cannot guarantee detection of every sensitive intent.
ILLUSTRATIVE EXAMPLE
Internal request
Compare our confidential margins with public market trends.
What may leave
A general query about public market trends, if policy approves it.
What stays inside
Margins, internal project names, strategy and the resulting company comparison.
02 / YOUR RULES COME FIRST
What must your AI protect?
Department permissions are only the beginning. We account for individual users, specific records and the sensitivity of derived results.
Employee isolation
Conversations, documents and personal working context must not cross into unauthorized users' sessions.
Individually sensitive data
Pay, commissions, contract amendments and targets require controls at record level or based on the relationship to its owner.
Business information
Strategy, pricing, acquisitions and confidential projects belong only in approved processing environments.
Controlled internet access
Public search should not receive internal context simply because the model knows it.
Source permissions
AI must respect identity and access rules in CRM, ERP, document systems and databases.
Auditability
Traceable tool use, access and policy decisions. With limited retention and controlled access to audit records.
Data sovereignty
Control over inference, embeddings, document processing, conversations, logs and automated analysis.
03 / SECURITY IS NOT A PROMPT
A model is not an access-control system.
We separate what a user may receive, which data a model may process, which tools may run and what may leave the protected environment.
Identity and permissions
Integration with SSO, Active Directory or another identity provider. Policies based on users, groups, classification and relationships to specific records are evaluated outside the model.
Secure access to knowledge
RAG retrieves and provides only authorized content. We address permission changes, revocation, caches and derived outputs. Classification inheritance must be validated for each data path.
Separating highly sensitive data
Pay and other sensitive structured data can remain in source systems. AI uses narrowly scoped functions with checks on the user, record and permitted fields.
Secure tools and agents
Each tool, API, file space and network connection has a defined policy. Writes and consequential actions may require human approval. Agents do not receive a universal administrator account.
Controlled internet access
The default network posture blocks unapproved outbound traffic. A separate research zone receives only an approved query, its own identity and limited tools.
Preventing information leakage
We combine classification, DLP, protected entities and company project lists with semantic checks. Uncertain cases are not released automatically. The checking model must also be approved for the data.
Untrusted content and prompt injection
Websites, documents and tool responses are inputs, not new instructions. Permission separation, constrained tools and content checks limit attack impact. A detector does not replace the security boundary.
Automated analysis
Scheduled processes have their own identities, purpose and minimum permissions. Result recipients are checked separately. Outputs can inherit source classification under a validated policy.
Audit and governance
Record identity, source type, tool use, decisions and policy versions. Prompts need not appear in ordinary logs. Retention, redaction and auditor permissions are explicitly defined.
04 / INFRASTRUCTURE BY SENSITIVITY
Where may your data be processed?
Define data boundaries first. Then select models, storage and operating environments.
Fully internal AI
Models, document processing, embeddings and automation within the organization's infrastructure. For the strictest data-control requirements.
Internal AI with internet access
Sensitive processing stays inside. A separate zone obtains current public information through an approved boundary crossing.
Private or sovereign cloud
An isolated environment, private networking and controlled outbound traffic. Assess jurisdiction, key management, administrator access and the contractual chain.
Hybrid environment
Different data categories use approved models and infrastructure. Public and strictly restricted data need not follow the same path.
05 / ARCHITECTURE BEFORE TECHNOLOGY
You do not need to build everything from scratch.
We select and connect existing components. These platforms address different layers of a solution. They are not interchangeable products.
Palantir AIP / Foundry
What it already addresses
Enterprise data and propagating mandatory controls. AIP supports custom models and policies controlling model access to marked data.
What ALTAMENTE adds
Validation of protection through outputs, declassification rules and separate public research. Row filtering alone does not protect subsequent use of data already read.
NVIDIA OpenShell
What it already addresses
Agent sandboxing with filesystem, process and network policies. Outbound connections are denied unless policy permits them.
What ALTAMENTE adds
Employee identity, enterprise data permissions, secure RAG and decisions on releasing information.
Palo Alto Networks Prisma AIRS
What it already addresses
Prompt injection, URL and data leakage checks using Enterprise DLP as a security layer for AI traffic.
What ALTAMENTE adds
Application architecture, source permissions and sensitivity rules reflecting the company's business context.
Microsoft Foundry
What it already addresses
Agent operation with private networking and network isolation options. Tool support depends on the selected networking mode.
What ALTAMENTE adds
Data classification, controlled declassification and enterprise integration where the organization approves processing in Azure.
Amazon Bedrock AgentCore
What it already addresses
Gateway and policies with guardrails for tool inputs and outputs. Sensitive content and prompt attack detection complement authorization.
What ALTAMENTE adds
Internal classification, source permissions and public research policy where AWS is an approved processing environment.
Capabilities depend on version, license, region and configuration. Naming a technology does not imply an ALTAMENTE partnership or certification. Semantic guardrails can fail and do not replace authorization.
INTEGRATION IS THE KEY LAYER
ALTAMENTE Security & Declassification Layer
The integration layer designed for a specific organization. It connects identity, data sensitivity, models, tools and public research policies.
- Who is asking?
- Which data may they use?
- Which model may process it?
- Which tool may run?
- What may leave the internal environment?
One environment for employeesUser and role isolationPublic information without full internal contextAutomation with its own permissionsReuse of existing infrastructure
06 / FROM ANALYSIS TO OPERATION
AI that knows your business. Within the limits of its permissions.
We design the solution around your data, infrastructure and security requirements.
Analysis and design
Map data, identities and risks. Define target architecture and compare technologies.
Integration and policies
Identity, RAG, models and tools. Access, declassification and outbound communication rules.
Validate security boundaries
Test user isolation, permission changes, data flows and unexpected requests. Deliver evidence of the results.
Operation and development
Monitor and update models, policies and integrations. Review changes continuously.
A description of your environment and requirements is enough for an initial conversation. Do not send sensitive documents or access keys through the standard form.