Gerald - The Enterprise Cloud Architects
Security first, AI second

AI Security Adopt AI Without Losing Control

AI is only as trustworthy as the data practices behind it. We secure your AI tools, your Copilot rollout, and the data they touch — with the discipline of two decades in banking IT, sized for your business.

What actually goes wrong

AI security failures are rarely exotic. They are ordinary data hygiene problems that AI amplifies at machine speed.

Copilot finds what you forgot

Copilot respects your permissions perfectly — including the over-shared folders nobody cleaned up for years. Day one of Copilot is judgment day for your access rights.

Data walks out through prompts

Customer lists, contracts, and source code pasted into public AI tools leave your perimeter invisibly. No firewall sees it happen.

Vendor AI is your risk too

Your tools quietly added AI features that process your data on someone else's infrastructure. Most contracts were never updated for that.

Responsible AI is a security property

Biased outputs, hallucinated facts in customer communication, AI decisions nobody can explain — reputational incidents are security incidents.

The difference preparation makes

With Gerald AI Security

  • Copilot launched on cleaned-up permissions
  • DLP policies that cover AI scenarios
  • Approved AI tools, securely configured
  • An incident runbook before you need it
  • Security that enables instead of blocking

Without preparation

  • Copilot surfacing files nobody knew were shared
  • Data leaving through prompts, invisibly
  • Every employee improvising their own tools
  • The first AI incident handled in panic
  • Blanket bans that quietly get ignored

Banking-grade practices, SMB-sized

1

Assess your AI attack surface

Weeks 1–2

Where AI touches your data: Copilot scope, tool inventory, permission sprawl, vendor AI exposure. Including a Copilot-readiness check of your M365 permissions.

2

Fix the foundations

Weeks 3–6

Access rights cleanup, sensitivity labels, Microsoft Purview DLP policies tuned for AI scenarios, Entra ID conditional access. The unglamorous work that makes AI safe.

3

Secure the AI layer

Weeks 6–8

Copilot deployment with guardrails, approved-tool catalog with secure configurations, monitoring for AI-related data movement, response runbooks for AI incidents.

4

Keep watch

Ongoing, optional

AI security as part of managed services: monitoring, new-feature reviews as Microsoft ships them, periodic permission audits.

What we secure in practice

Copilot rollouts

Permission cleanup, scoping, and guardrails so day one of Copilot is a win, not an exposure.

Most requested

Microsoft 365 permissions

The over-shared folders and stale access rights that AI turns from theory into risk.

Foundation

Public AI tool usage

DLP controls for genuinely sensitive data plus securely configured alternatives people will actually use.

Realistic controls

Vendor AI data flows

Where your data goes when your tools' AI features process it — assessed and contained.

Third-party risk

Custom AI applications

Security baselines for Azure OpenAI and custom builds: identity, secrets, data paths, logging.

Azure OpenAI

AI output guardrails

Human review points where AI writes to customers — accuracy and reputation protected.

Responsible AI

Industry-specific security needs

Financial Services

Core applications:

  • • Client-data boundaries
  • • Regulator-grade logging
  • • Fraud-sensitive AI controls

Business impact:

Banking-grade discipline, fund-sized delivery.

Healthcare

Core applications:

  • • Patient-data DLP
  • • Vendor AI containment
  • • Access reviews

Business impact:

AI assistance without patient-data exposure.

Manufacturing

Core applications:

  • • Design & IP protection
  • • OT/IT boundaries for AI tools
  • • Supplier data controls

Business impact:

Your know-how stays inside the company.

Professional Services

Core applications:

  • • Client-file protection in AI workflows
  • • Engagement isolation
  • • Confidentiality controls

Business impact:

Every client's data treated like your own.

Retail & E-Commerce

Core applications:

  • • Customer PII in AI flows
  • • Payment-adjacent data boundaries
  • • Marketing-AI controls

Business impact:

Personalization without privacy incidents.

Construction & Real Estate

Core applications:

  • • Bid and contract confidentiality
  • • Document-AI controls
  • • Field-team tool policies

Business impact:

Competitive information stays confidential.

What you get

  • AI attack-surface assessment with prioritized findings
  • Copilot readiness report and permission remediation plan
  • Purview DLP policies covering AI usage scenarios
  • Secure configuration baseline for approved AI tools
  • Responsible-AI guardrails: human review points for customer-facing AI output
  • Incident runbook for AI-related data events

Trusted where security is non-negotiable

For an investment fund, we run the complete M365 environment — cybersecurity monitoring, data loss prevention, and tailored AI integrations with VIP support. AI features were introduced without a single DLP exception being weakened, because security came first and AI second.

Our background: migrating a legacy banking application serving 10,000+ investors to Azure with improved resilience and security — the standard we bring to every environment, whatever its size.

What we'll tell you straight

Sometimes the right answer is 'don't enable that feature yet.' If your permission structure isn't ready for Copilot, we'll say so and fix the foundations first — a delayed rollout costs you weeks; a data exposure costs you customers. Security advice you can trust has to include 'no.'

How we can work together

Copilot Readiness Check

2 weeks

Find out what Copilot would expose before Copilot does. Permission analysis with a concrete remediation plan.

  • Permission & sharing analysis
  • Sensitive-data hotspots
  • Remediation plan
  • Go/no-go recommendation

Fixed scope — quoted after your free assessment.

Most popular

AI Security Hardening

6–8 weeks

Foundations fixed, AI layer secured: from access cleanup to DLP, secure configurations, and runbooks.

  • Everything in the Readiness Check
  • Access rights cleanup
  • Purview DLP for AI scenarios
  • Secure tool baseline
  • Incident runbook

Fixed scope — quoted after your free assessment.

Managed AI Security

Ongoing

AI security as part of managed services: monitoring, new-feature reviews, periodic audits.

  • Continuous monitoring
  • Microsoft feature-release reviews
  • Periodic permission audits
  • Integration with your existing security operations

Fixed scope — quoted after your free assessment.

Frequently Asked Questions

Common questions about AI security for SMBs

Related services & solutions

Know your AI exposure

The free assessment maps where AI touches your data today and what to fix first — concrete, prioritized, and in plain language.

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    Gerald US

    AI where it makes sense. We guide businesses through AI and cloud transformation — strategy first, with our own teams in the US, Japan, and India.

    Founded in Tokyo in 2007 — in the US since 2017

    100+ projects delivered for 40+ clients worldwide.

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