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Human-in-the-Loop Assurance Statement

At Complēre.ai, we believe AI is a powerful tool, but not a substitute for human judgment. All curated sources are vetted by professionals who have spent decades identifying the best available evidence, conducting meta-analyses, and applying benefit-cost models to guide both state and philanthropic budgets. Every part of Complēre has been built by people with long-standing experience in philanthropy and direct service nonprofit work, ensuring that critical thinking, context, and community insight remain at the core of every output.

Research Integrity

Complēre's core knowledge base is built on a foundation of high-quality, peer-reviewed, and policy-relevant research curated by experts with decades of experience in evidence-based philanthropy, economic analysis, and direct service. The studies we include reflect rigorous standards, drawing from meta-analyses, longitudinal data, and cost-benefit frameworks used by state agencies and leading funders to guide investment decisions. Our database is continuously updated to reflect new findings, and we welcome user contributions. Funders and practitioners can recommend research for expert review and possible inclusion, ensuring that Complēre remains a living resource grounded in both community insight and the evolving evidence base. We stand behind the integrity of the work we share, so you can move from insight to action with confidence.

AI & Hallucination Policy

Complēre uses large language models (LLMs) to rapidly synthesize, organize, and surface insights from vast bodies of evidence. This capability is central to our mission, but like all LLM-powered systems, ours can occasionally produce inaccuracies or “hallucinations,” including information that is fabricated, overstated, or imprecisely sourced.

We take this seriously. To reduce risk, we employ multiple layers of safeguards: automated detection and validation processes, and ongoing pressure testing by professional researchers who assess the frequency, patterns, and types of errors our system produces. These measures meaningfully improve reliability, but no system is perfect, and we will not overstate our confidence in any output.

Accuracy is a shared responsibility between Complēre and the people who use it. Our platform is designed to inform and reflect, not to make decisions on your behalf. Users are encouraged to apply critical judgment, cross-reference important claims, and report any output that seems questionable, inconsistent, or wrong. When issues are flagged, we commit to prompt investigation, transparent communication about how the output was generated, and corrective action where warranted.

We are continuously improving our models, validation processes, and research infrastructure to ensure that the facts, data, and insights surfaced by Complēre are as reliable as possible, while remaining honest about the inherent limitations of this technology.

If you encounter a potential inaccuracy, please report it to emailus@complere.ai. Your vigilance helps make this platform better for everyone.

Human-in-the-Loop Assurance Statement∨

At Complēre.ai, we believe AI is a powerful tool, but not a substitute for human judgment. All curated sources are vetted by professionals who have spent decades identifying the best available evidence, conducting meta-analyses, and applying benefit-cost models to guide both state and philanthropic budgets. Every part of Complēre has been built by people with long-standing experience in philanthropy and direct service nonprofit work, ensuring that critical thinking, context, and community insight remain at the core of every output.

Research Integrity∨

Complēre's core knowledge base is built on a foundation of high-quality, peer-reviewed, and policy-relevant research curated by experts with decades of experience in evidence-based philanthropy, economic analysis, and direct service. The studies we include reflect rigorous standards, drawing from meta-analyses, longitudinal data, and cost-benefit frameworks used by state agencies and leading funders to guide investment decisions. Our database is continuously updated to reflect new findings, and we welcome user contributions. Funders and practitioners can recommend research for expert review and possible inclusion, ensuring that Complēre remains a living resource grounded in both community insight and the evolving evidence base. We stand behind the integrity of the work we share, so you can move from insight to action with confidence.

AI & Hallucination Policy∨

Complēre uses large language models (LLMs) to rapidly synthesize, organize, and surface insights from vast bodies of evidence. This capability is central to our mission, but like all LLM-powered systems, ours can occasionally produce inaccuracies or “hallucinations,” including information that is fabricated, overstated, or imprecisely sourced.

We take this seriously. To reduce risk, we employ multiple layers of safeguards: automated detection and validation processes, and ongoing pressure testing by professional researchers who assess the frequency, patterns, and types of errors our system produces. These measures meaningfully improve reliability, but no system is perfect, and we will not overstate our confidence in any output.

Accuracy is a shared responsibility between Complēre and the people who use it. Our platform is designed to inform and reflect, not to make decisions on your behalf. Users are encouraged to apply critical judgment, cross-reference important claims, and report any output that seems questionable, inconsistent, or wrong. When issues are flagged, we commit to prompt investigation, transparent communication about how the output was generated, and corrective action where warranted.

We are continuously improving our models, validation processes, and research infrastructure to ensure that the facts, data, and insights surfaced by Complēre are as reliable as possible, while remaining honest about the inherent limitations of this technology.

If you encounter a potential inaccuracy, please report it to emailus@complere.ai. Your vigilance helps make this platform better for everyone.

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