OpenAI AI Services

1 Summary

OpenAI provides advanced AI language models and API services for content generation, analysis, and automated intelligence across business operations. Used for internal productivity, content creation, and operational automation with strict client data protection controls.

2 Support Channels

3 Key Integrations

  • Claude Code Integration: Development assistance and code review via official Claude Code CLI
  • Content Generation: Blog post drafting, documentation creation, client communication templates
  • Data Analysis: Investment research insights, market analysis, and trend identification
  • Operational Automation: Process documentation, workflow optimization, and task automation

4 Technical Implementation

  • Authentication: API Key (OPENAI_API_KEY) managed via Doppler credential system
  • Rate Limits: Tier-based limits depending on usage volume and subscription level
  • Model Access: GPT-4, GPT-3.5-turbo, and specialized models based on use case requirements
  • API Integration: RESTful API calls with JSON request/response format
  • Usage Monitoring: Built-in usage tracking and cost management through OpenAI dashboard

5 AI Usage Categories

5.1 Development & Operations

  • Code Review: Automated code analysis and improvement suggestions
  • Documentation: Technical documentation generation and maintenance
  • Process Optimization: Workflow analysis and efficiency recommendations
  • Debugging: Error analysis and troubleshooting guidance

5.2 Content & Communications

  • Blog Content: Investment insights, market analysis, educational content
  • Client Communications: Email templates, newsletter content, educational materials
  • Marketing Materials: Website copy, strategy explanations, value proposition development
  • Internal Communications: Meeting summaries, process updates, training materials

5.3 Research & Analysis

  • Market Research: Industry trend analysis, competitive intelligence, regulatory updates
  • Investment Analysis: Company research, sector analysis, risk assessment
  • Data Interpretation: Financial data analysis, performance reporting, trend identification
  • Compliance Support: Regulatory requirement analysis, policy interpretation

6 Client Data Protection Controls

6.1 Strict Data Isolation

  • No Client PII: Personal identifiable information never submitted to OpenAI APIs
  • No Financial Data: Client account balances, transactions, or holdings excluded from AI processing
  • No Proprietary Information: Client-specific investment strategies and personal details protected
  • Anonymization Required: Any client-related data must be fully anonymized before AI processing

6.2 Usage Boundaries

  • Internal Operations Only: AI assistance limited to internal business processes
  • Content Creation: General educational and marketing content that doesn’t reveal client specifics
  • Research Support: Market analysis and investment research using public information only
  • Process Documentation: Internal workflow and procedure documentation

6.3 Data Handling Procedures

# Example of approved AI usage pattern
doppler run -- python -c "
import openai
import os

# APPROVED: General market analysis
prompt = 'Analyze current trends in sustainable investing without referencing specific portfolios'
response = openai.ChatCompletion.create(
    model='gpt-4',
    messages=[{'role': 'user', 'content': prompt}]
)

# PROHIBITED: Client-specific analysis
# prompt = 'Analyze John Smith portfolio performance' # NEVER DO THIS
"

7 Cost Management and Monitoring

7.1 Usage Tracking

  • API Call Monitoring: Track requests per day, model usage, and token consumption
  • Cost Alerts: Automated alerts when monthly usage approaches budget thresholds
  • Usage Attribution: Tag requests by use case (development, content, research) for cost allocation
  • Efficiency Optimization: Regular review of prompt efficiency and model selection

7.2 Budget Controls

  • Monthly Spending Limits: Hard limits configured in OpenAI dashboard
  • Usage Policies: Guidelines for appropriate use cases and cost-effective model selection
  • Regular Reviews: Monthly analysis of usage patterns and cost optimization opportunities

8 Risk Management

8.1 Data Privacy Risks

  • Accidental Data Exposure: Risk of accidentally including sensitive data in prompts
  • Model Training: Understanding that conversations may be used for model improvement
  • Third-Party Access: Data processed by OpenAI systems outside direct control
  • Mitigation: Strict data classification and review procedures before AI processing

8.2 Operational Dependencies

  • Service Availability: Dependency on OpenAI service uptime for operations
  • Model Changes: Risk of model updates affecting existing workflows
  • API Changes: Potential breaking changes requiring code updates
  • Cost Volatility: Usage-based pricing creating unpredictable costs

8.3 Compliance Considerations

  • Regulatory Review: Ensure AI usage complies with investment advisor regulations
  • Client Disclosure: Potential need to disclose AI assistance in client-facing materials
  • Audit Trail: Maintain records of AI usage for compliance and audit purposes
  • Data Retention: Understanding of how long data is retained by OpenAI systems

9 Usage Guidelines and Best Practices

9.1 Approved Use Cases

  • ✅ Internal process documentation and improvement
  • ✅ General market research and analysis using public information
  • ✅ Content creation for blog posts and educational materials
  • ✅ Code review and development assistance
  • ✅ Email template creation for general communications

9.2 Prohibited Use Cases

  • ❌ Processing any client personal information or account details
  • ❌ Analysis of specific client portfolios or investment positions
  • ❌ Generation of personalized investment advice for named clients
  • ❌ Processing of confidential business strategies or proprietary methodologies
  • ❌ Any usage that could create regulatory compliance issues

9.3 Quality Assurance

  • Human Review: All AI-generated content requires human review before use
  • Fact Checking: Verification of factual claims in AI-generated research or analysis
  • Compliance Review: Legal/compliance review for client-facing AI-assisted content
  • Attribution: Clear attribution when AI assistance is used in published materials

10 Integration with Development Workflows

10.1 Claude Code Integration

  • Official Integration: Claude Code CLI provides authenticated access to Claude AI
  • Development Assistance: Code review, documentation generation, debugging support
  • Project Context: AI assistance with full project context for better recommendations
  • Security: Integrated credential management through established authentication systems

10.2 Content Management

  • Documentation Pipeline: AI-assisted creation of technical documentation
  • Blog Content: Market insights and educational content development
  • Template Generation: Standardized communication templates for various use cases

11 Monitoring and Compliance

11.1 Usage Audit Trail

  • Request Logging: Log all API requests with timestamp, user, and use case classification
  • Content Review: Periodic audit of AI-generated content for compliance
  • Policy Adherence: Regular review of usage against established guidelines
  • Cost Analysis: Monthly review of spending patterns and efficiency optimization

11.2 Compliance Reporting

  • Usage Summary: Monthly reports on AI usage categories and data protection compliance
  • Risk Assessment: Quarterly review of AI usage risks and mitigation strategies
  • Policy Updates: Regular updates to AI usage policies based on regulatory changes
  • Training: Team training on appropriate AI usage and data protection requirements
Owner: Ops: AI Operations
Last reviewed: 2025-09-24
SLA: N/A
Controls: ?invalid meta type:ops_controls
Commit: 8f0c18729ae96125ef5caf6824600a75c4928c16