Built for AI & ML Companies

Compliance for AI Startups Built for Speed & Scale

Get SOC 2, ISO 27001, and GDPR certified in 30 days. Purpose-built for AI/ML companies with model governance, data privacy, and AI safety frameworks.

⭐⭐⭐⭐⭐
4.9/5
50+
AI companies certified
28 days
average timeline

Compliance Challenges AI Startups Face

Building the future of AI while navigating complex compliance requirements

🎯

Enterprise Deals Blocked

$500K+ deals lost

Lost $500K+ deals because enterprise customers require SOC 2, ISO 27001, and AI governance frameworks before onboarding.

⚠️ Can't sign until you're certified
🤖

AI-Specific Requirements

Not built for ML

Model versioning, training data governance, bias testing, explainability docs - traditional compliance tools don't understand AI workflows.

⚠️ Not built for ML pipelines

Engineering Team Overloaded

200+ hours wasted

Your ML engineers should be training models, not collecting compliance screenshots. Traditional compliance = 200+ hours of engineering time.

⚠️ We build AI, not compliance docs

Get AI Compliance Done in 4 Weeks

Purpose-built process for AI/ML companies with model governance and data pipeline controls

Week 1
🔍

AI Infrastructure Assessment

Engineering Time: 2 days
Tasks:
  • Connect your ML stack: AWS/GCP/Azure ML, MLflow, Weights & Biases, training pipelines.
  • Map your architecture to compliance controls.
Deliverables:
  • ML stack integration
  • Architecture mapping
Week 2
🧠

Model Governance Setup

Engineering Time: 1 week
Tasks:
  • Implement model versioning, training data lineage, bias detection.
  • Set up explainability documentation.
  • AI-specific policies included.
Deliverables:
  • Model governance framework
  • AI policy templates
Week 3
📊

Automated Evidence Collection

Engineering Time: 2 weeks
Tasks:
  • Auto-collect evidence from cloud infra, model registry, data pipelines.
  • Gather access logs automatically.
  • 90% automated for AI workloads.
Deliverables:
  • Automated evidence collection
  • Compliance dashboard
Week 4

Audit & Certification

Engineering Time: 1 week
Tasks:
  • Expert review by advisors who understand AI systems.
  • Mock audit preparation.
  • Auditor coordination.
Deliverables:
  • Mock audit
  • Certification
Average Time to Certification
28 days
vs. 6-12 months with traditional consultants

AI-Native Compliance Features

Purpose-built for machine learning workflows and AI governance

🧠

Model Governance

Track model versions, training data lineage, performance metrics, bias testing, and explainability docs. Automated audit trails for ML pipelines.

  • Model versioning tracking
  • Training data lineage
  • Performance metrics
  • Bias testing documentation
  • Explainability docs
Complete ML lifecycle coverage
🔒

Training Data Security

Data classification for training datasets, PII detection, access controls, retention policies, and data lineage documentation.

  • Data classification
  • PII detection
  • Access controls
  • Retention policies
  • Data lineage
Full data governance
⚖️

AI Bias & Fairness

Document bias testing procedures, fairness metrics, demographic analysis, and remediation workflows for responsible AI.

  • Bias testing procedures
  • Fairness metrics
  • Demographic analysis
  • Remediation workflows
Responsible AI compliance
📊

ML Pipeline Monitoring

Auto-monitor feature stores, training jobs, model serving, inference logs, drift detection, and model performance degradation.

  • Feature store monitoring
  • Training job tracking
  • Model serving logs
  • Drift detection
  • Performance monitoring
Real-time ML observability
🌐

GDPR for AI Systems

Right to explanation, automated decision-making disclosures, data subject requests for training data, model deletion workflows.

  • Right to explanation
  • Automated decision disclosures
  • Data subject requests
  • Model deletion workflows
AI-specific GDPR compliance
🔗

ML Stack Integrations

Connect MLflow, Weights & Biases, SageMaker, Vertex AI, Azure ML, Databricks, Snowflake, and 50+ ML/data tools.

  • MLflow, W&B integration
  • Cloud ML platforms
  • Data warehouse connectors
  • Model registry sync
  • 50+ integrations
50+ ML tool integrations

AI Companies We've Certified

From computer vision to LLM platforms

VisionAI

Computer Vision Platform
Challenge:
Enterprise customers required SOC 2 certification before onboarding. Needed to document ML pipeline, model versioning, and training data governance.
Results:
  • SOC 2 certified in 26 days
  • Closed $1.2M in enterprise deals
  • Model governance framework implemented

LowerPlane understood our ML pipeline from day one. They helped us document model versioning, training data governance, and bias testing in a way that auditors actually accepted. Got SOC 2 in 26 days.

Sarah Chen, CTO
Time
26 days
Cost
Saved 60%
Impact
$1.2M deals

LangChain Analytics

LLM Application Platform
Challenge:
As an LLM platform, needed to prove controls around prompt injection, data leakage, and model security for SOC 2 + ISO 27001 certification.
Results:
  • SOC 2 + ISO 27001 certified
  • Enterprise-ready security posture
  • LLM-specific controls documented

As an LLM platform, we needed to prove we had controls around prompt injection, data leakage, and model security. LowerPlane mapped our AI-specific risks to SOC 2 + ISO controls perfectly.

Marcus Rodriguez, Head of Security
Time
30 days
Cost
Under $15K
Impact
Enterprise ready

Ready to Get Your AI Startup Compliant?

Join 50+ AI companies that chose LowerPlane for speed, AI-native features, and enterprise-ready compliance. Get certified in 28 days and start closing enterprise deals.

28 days
Average timeline
50+
AI companies certified
98.5%
First-time pass rate
90%
Evidence automated