Frequently Asked Questions
We use multiple layers of safeguards to minimize errors (reducing "hallucinations") and ensure our AI delivers consistent, trustworthy results for real business workflows:
Quality Controls:
• Temperature optimization - We adjust creativity parameters to prioritize factual accuracy over creative variation, ensuring responses remain consistent and grounded
• Model selection - We use premium, high-quality AI models specifically chosen for their reliability and performance on business-critical tasks
• AI Guardrails – Safety, compliance, and business rules define what the AI can and cannot do, preventing unsafe or off-topic results
• Structured outputs – Templates and validation rules ensure responses follow correct formats and meet quality standards
Data Grounding:
• Retrieval-Augmented Generation (RAG) - Our AI draws directly from your actual business documents and verified data sources rather than relying solely on its training, ensuring responses are based on your specific information (where applicable)
• Prompt engineering - Carefully tested instructions guide the AI toward clear, accurate, and relevant responses for your specific use cases
Human Oversight:
• Human-in-the-loop - Sensitive or complex decisions can be escalated for manual review
• Human-on-the-loop - We continuously monitor AI performance with regular quality checks and audits
Continuous Improvement:
• Regular evaluations - We run systematic tests to measure accuracy, consistency, and relevance
• Audit trails - We maintain detailed logs of AI interactions for quality review and ongoing refinement
Together, these safeguards ensure AI delivers reliable, business-ready results. We maintain transparency about AI limitations and continuously refine our safeguards based on real-world performance and client feedback.
For a deeper dive into why AI hallucinations occur and how the technology works, check out our Business AI Newsletter article.
Understanding the technology behind AI helps you make informed decisions about automation.
We've covered this in depth! Check out our LinkedIn post for a clear explanation, or explore our Business AI Newsletter where we regularly break down AI technology and its business applications.
We integrate your internal documents (policies, procedures, product catalogs, pricing lists, customer records, invoices, knowledge bases, contracts depending on a use case) through Retrieval-Augmented Generation (RAG). This technology ensures the AI grounds its responses in your real information.
For a detailed explanation, check out our Business AI Newsletter article on RAG, or read about RAG vs Agentic RAG to understand which approach fits different use cases.
