ImpactAI guarantees accuracy by relying on a structured knowledge base comprised of validated, peer-reviewed research studies. This prevents the generation of unverified content ("hallucinations") and ensures that outputs are both accurate and reliable.
We can ensure such high-quality standards due to a three-step process:
- Verified Evidence Database: We curate a database of evidence-based impact evaluations using our advanced information extraction system, overseen by a team of annotators who manually verify the information.
- Natural Language Understanding (NLU): Our NLU module is specifically designed to recognize key concepts from impact evaluation research. It queries our database for precise, context-relevant information.
- Summarization: A fine-tuned LLM generates concise, evidence-based answers, strictly constrained to the verified database, preventing hallucinations.
This process ensures ImpactAI consistently delivers reliable, evidence-driven insights to researchers and policymakers.