Governed private AI infrastructure

Private AI for operations that cannot afford to leak, hallucinate or lose control.

mAIb Tech builds governed private AI infrastructure for telecom operators and regulated enterprises — deployed within your environment, controlled by your policies and supported by verifiable evidence.

Review the security architecture →

Diagram: approved knowledge sources flow through governed ingestion to a local model runtime, wrapped by policy, approval and audit layers, serving operational teams — all inside the customer environment with no uncontrolled data egress. YOUR ENVIRONMENT ● PERIMETER SEALED Approved sources SOPs · runbooks tickets · RCA reports policy documents Governed ingestion classify · redact secret blocking human approval Local model runtime your servers air-gap capable Policy & approval layer role-based access in-query · approval gates · refusal of unsafe actions · kill switch Audit & evidence layer tamper-evident audit trail · provenance · decision records · evidence export Operational teams BSS & charging · NOC · care — cited, logged answers
Approved knowledge sources pass through governed ingestion into a local model runtime, wrapped by policy and audit layers, serving operational teams. No uncontrolled data egress.
  • On-premises deployment
  • Air-gapped option
  • Customer-controlled environment
  • Controlled knowledge lifecycle
  • Approval gates
  • Evidence & audit lineage
  • Built for regulated operations
The problem

Enterprises want AI. Regulated operations cannot pay for it with their data.

Sensitive knowledge is escaping controlled environments

Employees increasingly paste incident logs, configurations, customer records, internal procedures and source code into external AI tools — invisible to security, and irreversible once sent. Banning AI removes visibility while usage continues.

Generic AI lacks operational governance

A capable model is not enough when nobody controls which knowledge it uses, who may ask what, which actions are allowed, which sources count as valid, and which approval is required before its knowledge changes.

Enterprises cannot prove what happened

Without lineage, evidence and lifecycle control, an organisation cannot prove what the system knew, which version answered, which policy applied, who approved a change — or roll any of it back.

The mAIb approach

Private infrastructure. Governed knowledge. Verifiable evidence.

Three layers that turn a capable model into an operational system a regulated enterprise can defend.

01

Private infrastructure

Local or customer-controlled deployment. Approved models behind a neutral adapter layer. Controlled connectors, data residency by construction, and network-boundary enforcement — with customer-held keys where supported.

02

Governed knowledge & execution

Source approval, classification, redaction and versioning. Permissions enforced inside retrieval. Human approval gates, policy controls and rollback for every change the AI depends on.

03

Verifiable evidence

Tamper-evident audit events, decision records, provenance for every answer, and evidence export designed for security review, internal audit and renewal decisions.

Flagship — Locs

Governed private AI infrastructure for sensitive telecom operations.

Locs is enterprise software you run on your own servers. It connects approved telecom knowledge to customer-controlled AI, answers with citations and confidence scores, refuses when it does not know, and records everything it does — advisory only, inside your environment.

  • Telecom-focused: BSS/charging, NOC and customer-care copilots
  • Local deployment — hardened container package, air-gap capable
  • Answers only from operational knowledge your administrators approved
  • Governed knowledge updates with human approval and rollback
  • Evidence centre your auditors can use
  • A pilot-to-production path measured in evidence, not slideware
How it works

Six steps from deployment to defensible evidence.

  1. Deploy within the approved environment

    On-premises, private cloud or air-gapped — installed by your ops team on infrastructure you control.

  2. Connect approved knowledge sources

    Read-only connectors for SharePoint/M365, ServiceNow and file systems create governed drafts.

  3. Classify, redact and govern

    Secrets block ingestion outright; identifiers are redacted before embedding; humans approve activation.

  4. Serve controlled AI experiences

    Authorised users get cited, confidence-scored answers from approved knowledge — advisory only.

  5. Apply policy, permissions and approvals

    Role-based access enforced in-query; unsafe actions refused; changes pass approval gates.

  6. Produce evidence, monitor, roll back

    Tamper-evident audit lineage, exportable evidence, and tested rollback for knowledge and models.

Framework alignment

Alignment stated precisely. Certification never implied.

Framework alignment status
FrameworkCurrent positionEvidence availableStatus
EU AI Act Designed to support applicable governance requirements for high-risk AI use in enterprise operations Internal control mapping in preparation; available under NDA on request By design
NIST AI RMF Architecture designed around the Govern / Map / Measure / Manage functions Architecture-to-function mapping available on request By design
ISO/IEC 42001 (AI management) On the certification roadmap; no issued certification claimed Gap assessment planned Roadmap
ISO/IEC 27001 (information security) Security controls designed in alignment with Annex A control themes; on the certification roadmap Control alignment notes available under NDA Roadmap
SOC 2 On the certification roadmap; trust-service criteria inform the control design No audit performed yet Roadmap
GDPR / UK GDPR Privacy-by-design principles; on-premises deployment keeps personal data in the customer environment Privacy documentation; data-processing terms on request Alignment
Regional telecom & data regulation (e.g. CITRA, TRA, central-bank circulars) Regulatory mapping capability — packs can be mapped to applicable circulars per engagement Mapping produced per customer engagement By design

mAIb Tech does not claim an issued certification unless explicitly stated. Frameworks listed reflect design principles, alignment work and roadmap goals — not certifications, audit results or regulatory approvals.

Readiness assessment

How ready is your organisation for private AI?

A 15-question self-assessment across data exposure, deployment boundaries, identity, knowledge governance, approvals, auditability, rollback and operational ownership. Immediate results — no email required for your score.

Approximately 5–8 minutes. A preliminary, non-binding self-assessment — not an audit, certification or legal advice.

  • Data exposure & shadow AI
  • Deployment boundaries
  • Identity & access
  • Knowledge governance
  • Model governance & approvals
  • Audit, evidence & rollback
  • Operational ownership
  • Regulatory accountability
The company

A focused company with an honest stage.

mAIb Tech LLC is a Delaware limited liability company building governed private AI infrastructure, designed from firsthand telecom and BSS operations experience. We are founder-led, pre-launch, and onboarding a limited design-partner cohort. We do not publish customer names or testimonials we cannot legally back.

Legal entity
mAIb Tech LLC (Delaware, USA)
Stage
Pre-launch · design partners onboarding
Flagship
Locs — governed private AI for telecom
Foundation
AOS-1 governance runtime · GAIO platform
Contact
support@maib.io

Deploy private AI without surrendering control.

A briefing takes one call. No obligation, NDA available on request, and technical or executive sessions to suit your team.