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Shadow AI
Your teams already use AI.
You just can't see it.
Your employees are pasting client data, internal documents, and proprietary code into public AI tools your security team cannot see, audit, or control. IDT builds secure, private AI on AWS to replace uncontrolled usage with governed infrastructure.
AWS ADVANCED TIER PARTNER
What is Shadow AI
Unauthorized use of public AI tools outside IT oversight. Free, fast, zero friction. Employees use whatever helps them deliver. Every prompt is data leaving your environment with no audit trail, no governance, and no guarantee of deletion.
- Client data, contracts, case notes pasted into public tools
- Internal docs and financials used as prompt context
- No audit trail. No visibility. No control over data retention.
The risk to your business
#ModelTraining
#DevOpsForAI
#MLPipelines
#DataEngineering
#CloudAI
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Data exposure Sensitive data leaves controlled environments. No deletion guarantee.
Compliance risk SOC 2, PCI DSS violations. Regulatory exposure.
Loss of control Zero visibility into usage. No enforcement. No defensible posture.
Why restricting AI access backfires
Employees bypass restrictions with personal devices and browser tools. Bans push usage underground, drop productivity, and create friction between security and engineering. Demand for AI is accelerating, not slowing down.
How we do
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01
Before anything is built, we define what governed AI looks like in your environment. Compliance requirements, data policies, and team needs set the scope. Architecture follows your constraints, not a default template.
Scope the environment
02
Controls, monitoring, and policy enforcement configured directly into your infrastructure. CloudWatch, CloudTrail, Macie, IAM, and Service Control Policies aligned to your compliance framework.
Build governance into your AWS environment
03
Amazon Bedrock inside your VPC with PrivateLink. PII redaction and content filtering through Guardrails. SageMaker available for self-hosted models. Role-based access, full audit trail, tuned to your workflows.
Deploy private AI that replaces the shadow tools
04
One real use case goes live. Full audit trail, full access controls, full policy enforcement from day one. The platform is built so the next use case is a configuration decision, not another project.
Launch a real workflow in production
Outcomes
● Full visibility into AI usage
● Uncontrolled exposure eliminated
● Compliance-aligned AI usage
● Faster adoption, lower risk
● Production-grade AWS foundation for scaling AI, personalized to your business
Shadow AI
Your employees are pasting client data, internal documents, and proprietary code into public AI tools your security team cannot see, audit, or control. IDT builds secure, private AI on AWS to replace uncontrolled usage with governed infrastructure.
AWS ADVANCED TIER PARTNER
Unauthorized use of public AI tools outside IT oversight. Free, fast, zero friction. Employees use whatever helps them deliver. Every prompt is data leaving your environment with no audit trail, no governance, and no guarantee of deletion.
- Client data, contracts, case notes pasted into public tools
- Internal docs and financials used as prompt context
- No audit trail. No visibility. No control over data retention.
What is Shadow AI
The risk to your business
Data exposure Sensitive data leaves controlled environments. No deletion guarantee.
Compliance risk SOC 2, PCI DSS, HIPAA violations. Regulatory exposure.
Loss of control Zero visibility into usage. No enforcement. No defensible posture.
Why restricting AI access backfires
Employees bypass restrictions with personal devices and browser tools. Bans push usage underground, drop productivity, and create friction between security and engineering. Demand for AI is accelerating, not slowing down.
From exposure to governed AI in four steps
Scope the environment
Before anything is built, we define what governed AI looks like in your environment. Compliance requirements, data policies, and team needs set the scope. Architecture follows your constraints, not a default template.
01
Build governance into your AWS environment
Controls, monitoring, and policy enforcement configured directly into your infrastructure. CloudWatch, CloudTrail, Macie, IAM, and Service Control Policies aligned to your compliance framework.
02
Deploy private AI that replaces the shadow tools
Amazon Bedrock inside your VPC with PrivateLink. PII redaction and content filtering through Guardrails. SageMaker available for self-hosted models. Role-based access, full audit trail, tuned to your workflows.
03
04
Launch a real workflow in production
One real use case goes live. Full audit trail, full access controls, full policy enforcement from day one. The platform is built so the next use case is a configuration decision, not another project.
Outcomes
- Full visibility into AI usage
- Uncontrolled exposure eliminated
- Compliance-aligned AI usage
- Faster adoption, lower risk
- Production-grade AWS foundation for scaling AI, personalized to your business