AI in PartnerAlly

PartnerAlly uses artificial intelligence to automate compliance analysis, identify gaps, prioritize risks, and generate remediation workflows. This section explains how AI works in the platform and how to get the most from it.

AI-Powered Features

Document Analysis

AI reads and understands your policy documents:

• Extracts key compliance information
• Identifies what controls are present
• Detects gaps against frameworks
• Suggests improvements

Learn more: Document Analysis

Chat Assistant

Ask questions about your compliance program:

• Natural language queries
• Context-aware responses
• Cites sources from your documents
• Helps navigate complex requirements

Learn more: Chat Assistant

Workflow Generation

AI creates remediation plans automatically:

• Analyzes gaps to understand needs
• Generates step-by-step workflows
• Assigns tasks appropriately
• Suggests timelines

Learn more: Workflow Generation

Risk Prioritization

AI helps prioritize what matters most:

• Scores risks by multiple factors
• Considers business context
• Recommends focus areas
• Adapts as you address issues

Learn more: Risk Prioritization

How AI Works

The Analysis Process

When you upload a document:

1. Extraction: AI reads the document content
2. Understanding: Identifies policies, controls, and procedures
3. Mapping: Matches content to framework requirements
4. Gap Detection: Finds missing or incomplete controls
5. Scoring: Assigns confidence levels to findings
6. Presentation: Shows results with explanations

AI Models Used

PartnerAlly uses advanced language models:

• Google Gemini (primary provider)
• Groq (fallback provider)
• Models optimized for compliance understanding

Data Processing

How your data is handled:

• Documents sent to AI for analysis
• Results stored in your organization
• No training on your data
• Encrypted in transit
• Processed per privacy policy

AI Accuracy

Understanding Confidence

AI provides confidence scores:

• High (85%+): Strong match, clear evidence
• Medium (60-84%): Reasonable inference
• Low (below 60%): Uncertain, needs review

Why Confidence Varies

Factors affecting accuracy:

• Document clarity and format
• Specificity of language
• Completeness of content
• Framework complexity
• Control overlap

Improving Accuracy

Get better AI results by:

• Uploading clear, well-formatted documents
• Including complete policy content
• Using standard compliance terminology
• Providing multiple related documents

Human-AI Partnership

AI Assists, Humans Decide

PartnerAlly follows a human-in-the-loop model:

• AI identifies potential issues
• AI suggests possible solutions
• Humans review and validate
• Humans make final decisions

When Human Review is Critical

Always have humans review:

• Critical or high-severity findings
• Low-confidence results
• Unusual or unexpected gaps
• Framework interpretation questions
• Business context decisions

Learn more: Human Review

AI Transparency

Explanations

AI provides reasoning for its conclusions:

• Why a gap was identified
• What evidence supports the finding
• How confidence was determined
• What framework requirements apply

Audit Trail

All AI actions are logged:

• When analysis occurred
• What was analyzed
• What results were generated
• Who reviewed findings

No Black Box

We aim for transparency:

• Explanations for every finding
• Confidence scores for uncertainty
• Source citations where possible
• Clear escalation paths

AI Limitations

What AI Cannot Do

Be aware of limitations:

• Cannot guarantee compliance
• May miss nuanced requirements
• Cannot replace legal advice
• Cannot make business decisions
• May not understand unique contexts

When AI May Struggle

Lower accuracy in:

• Highly customized frameworks
• Industry-specific terminology
• Complex multi-document relationships
• Ambiguous control language
• Emerging regulations

Mitigation

How PartnerAlly addresses limitations:

• Confidence scores show uncertainty
• Human review workflows
• Continuous model improvement
• User feedback incorporation

Best Practices

For Best Results

1. Upload quality documents

   • Clear formatting
   • Complete content
   • Standard terminology

2. Review AI outputs

   • Check confidence scores
   • Validate high-impact findings
   • Provide feedback

3. Use multiple documents

   • AI cross-references
   • Better context understanding
   • More accurate mapping

4. Keep frameworks current

   • Enable relevant frameworks
   • Update as requirements change
   • Remove outdated ones

Common Mistakes

Avoid these pitfalls:

• Blindly accepting AI findings
• Ignoring low-confidence results
• Uploading poor quality scans
• Not reviewing generated workflows
• Assuming AI understands context

Privacy and Security

Data Protection

Your documents are protected:

• Encrypted in transit and at rest
• Access controlled by your organization
• Not shared with other customers
• Not used for model training

AI Provider Security

Our AI providers maintain:

• SOC 2 compliance
• Enterprise security standards
• Data processing agreements
• Privacy commitments

Your Controls

You control AI usage:

• Choose what to analyze
• Review before taking action
• Export your data
• Delete when needed

Getting Started with AI

First Steps

1. Upload a document
2. Review the AI analysis
3. Examine confidence scores
4. Validate a few findings manually
5. Generate a workflow from a gap
6. Try the chat assistant

Building Trust

Start small:

• Analyze one document first
• Compare AI findings to manual review
• Calibrate your expectations
• Gradually expand usage

AI Feature Summary

Learn More

Explore each AI feature in detail:

• Document Analysis - How AI reads your documents
• Chat Assistant - Asking questions naturally
• Workflow Generation - Auto-generated remediation
• Risk Prioritization - AI-powered risk ranking
• Confidence Scores - Understanding certainty
• Human Review - Human-in-the-loop process