How secure is business AIbusiness AI
We build AI that passes SOC 2, HIPAA, and PCI-DSS audits. Your data stays in your VPC, encrypted at rest and in transit.
How secure is business AI when you build it with IRPR? We use Python, FastAPI, and LangChain behind a zero-trust architecture. Every model call runs inside your private cloud tenant on AWS or Azure. No shared infrastructure, no data ever leaves your VPC.
A secure AI MVP ships in 12-14 weeks at a fixed price between $80K and $250K. We deliver role-based access control, end-to-end encryption, and audit logging as standard. Compliance artifacts for SOC 2, HIPAA, or PCI-DSS come included, not as a line item.
Healthcare CIOs hire us for HIPAA-compliant clinical decision support. Fintech founders need PCI-DSS AI for fraud detection. SaaS VPs of engineering want SOC 2 AI features inside their existing product. Manufacturing directors need air-gapped defect detection models.
Types of software we ship.
Secure chatbot for customer support
A GPT-4 chatbot that runs in your AWS VPC. All PII is masked before it hits the model. Logs ship to your SIEM.
HIPAA-compliant medical coding AI
Transcribes doctor visits and assigns ICD-10 codes. PHI is encrypted with AWS KMS. Audit trail covers every access.
PCI-DSS fraud detection model
Real-time transaction scoring with SageMaker endpoints inside a PCI boundary. Cardholder data never touches the model.
SOC 2 document redaction engine
Uses Azure Cognitive Services to auto-redact PII from legal docs. Processing happens in your tenant, not Microsoft's.
Air-gapped manufacturing vision system
YOLOv8 running on-premise with no internet connection. Model weights are signed and verified before loading.
FERPA-compliant student analytics platform
Predicts dropout risk using encrypted student records. Data is anonymized at the ingestion layer before analysis.
Secure RAG pipeline for internal knowledge
Employees query company docs via Slack. Embeddings are stored in a private Pinecone index with IAM-based access.
Multi-tenant SaaS recommendation engine
Each tenant's data is logically isolated in PostgreSQL row-level security. Vector search runs in dedicated namespaces.
We build for every business type.
Healthcare
Financial Services
SaaS and Technology
Regulated Industries
Education and Nonprofits
What business AI security really means
Security is not a feature. It is the architecture.
When a buyer asks how secure is business AI, they are really asking three things. Who can see the data? Where does the model run? What happens if there is a breach? IRPR answers all three before we write a single line of code.
We default to customer-owned infrastructure. Your OpenAI API key, your AWS account, your VPC. The AI model is a tenant inside your castle, not a guest in ours. This alone eliminates the shared responsibility confusion that sinks most AI projects.
IRPR vs generic AI dev shops
Most AI projects fail security review. Ours pass on the first submission.
Generic dev shops treat security as a checkbox at the end. They bolt on encryption and call it done. Then the SOC 2 auditor asks for access logs, and nobody has them. The project stalls for 6 months.
At IRPR, we ship with audit-ready logging from sprint one. Every model inference, every data access, every config change is logged immutably. Our clients pass HITRUST and SOC 2 Type II audits within 30 days of go-live.
- Shared API keys in .env files
- No data classification
- Logs stored in plaintext
- Model runs on public endpoints
- Access control is an afterthought
- Zero compliance documentation
- Secrets in AWS Secrets Manager
- Data tagged at ingestion
- Immutable audit logs in S3
- Model inside private VPC only
- RBAC designed in sprint one
- SOC 2, HIPAA, PCI-DSS artifacts
How we build secure business AI in 4 phases
Security is built in, not bolted on.
Our process front-loads security decisions. Threat modeling happens before architecture. Compliance requirements shape the tech stack, not the other way around.
Every phase produces artifacts that an auditor can review. This means no scrambling before a SOC 2 assessment. The evidence is already in your repo.
What ships with every secure AI project
These are not add-ons. They are the standard deliverable.
When you ask how secure is business AI, the answer is in the deliverables. IRPR ships a complete security package with every project. No separate line item, no surprise invoice.
- Infrastructure as Code (Terraform)
- VPC with private subnets
- AWS KMS or Azure Key Vault encryption
- IAM roles with least privilege
- Secrets management (no .env files)
- Immutable audit logging (CloudTrail + custom)
- OWASP ZAP security scan report
- Dependency vulnerability scan (Snyk)
- Incident response runbook
- Compliance evidence package
What we ship in this practice.
HIPAA clinical decision support for a telehealth company
Built a FastAPI + GPT-4 model that suggests diagnoses from patient notes. PHI is encrypted with AWS KMS. Reduced chart review time by 12 hours per week per clinician. Passed HITRUST audit in 28 days.
PCI-DSS real-time fraud scoring for a fintech processor
Deployed a SageMaker endpoint inside a PCI boundary. Scores 500 transactions per second. Cardholder data never leaves the payment processor's VPC. False positive rate dropped 40%.
SOC 2 document redaction for a legal SaaS platform
Integrated Azure Cognitive Services to redact PII from 10,000 contracts per day. Processing runs in the customer's Azure tenant. Manual review effort reduced by 90%.
Air-gapped defect detection for an automotive manufacturer
Trained a YOLOv8 model on proprietary factory images. Deployed on-premise with no internet connection. Model weights are signed and verified at boot. Defect detection accuracy reached 99.2%.
FERPA-compliant dropout prediction for a university system
Built a Python + scikit-learn model that predicts at-risk students. Data is anonymized at the ingestion layer. 3,000 students flagged for intervention in the first semester.
Secure internal knowledge bot for a 2,000-person company
Built a Slack bot with a private Pinecone vector index. Employees query company policies and get answers in under 2 seconds. Access is governed by Okta groups. 800 daily active users.
Why teams hire us.
Your infrastructure, your keys
We deploy into your AWS, Azure, or GCP account. IRPR engineers never see your production data. The AI model runs inside your VPC, not a shared tenancy.
Fixed price with compliance included
Every project gets a fixed quote in the Roadmap phase (week 2). SOC 2, HIPAA, or PCI-DSS evidence packages are part of the deliverable. No hourly billing, no compliance upcharges.
Audit-ready from sprint one
We configure CloudTrail, application logging, and SIEM integration before any model code is written. When your auditor asks for evidence, it is already in your S3 bucket.
Threat modeling before architecture
We map data flows and identify trust boundaries in week 1. The threat model document ships with the Roadmap. This catches 80% of security issues before a line of code exists.
Senior engineers only, no juniors
Every engineer on your project has 8+ years of experience. They have built compliant systems before. No one is learning HIPAA or PCI-DSS on your dime.
Source code and IP are yours
You own every line of code, every Terraform config, every model weight. No vendor lock-in. No ongoing license fees. The repo is in your GitHub org from day one.
Idea → Roadmap → Product → Release.
Every engagement runs through the same four-stage pipeline. Predictable by design.
Questions clients ask first.
Related services and industries.
Ready to build? Let's talk.
30-minute discovery call. No deck. We'll tell you honestly what it takes, how long, and how much.
─── share this page ───
