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ISE&S AI-Powered Chat

Our AI Resources combines OpenAI’s latest models with a Pinecone-backed RAG system to strengthen nonprofit capacity through on-demand, data-driven equity guidance. Incoming queries are first vetted by our custom guardrails module and client-side validations, keeping conversations mission-focused and tone consistent. Each document undergoes a structured bias assessment before entering the knowledge base, and our embedded system prompt ensures the assistant draws first on these vetted materials. The result is guidance that leverages conversational AI’s strengths in contextual understanding to empower nonprofits in designing and implementing sustainable strategies that support their mission.

Prompt Recommendations:

AI Resources Chat
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Note: Large language models may occasionally generate incomplete or inaccurate information. Please verify critical details with trusted sources.

Aligning Our Mission with AI

AI Guardrails with Custom Module

We leverage OpenAI’s SDK together with our custom guardrails module to enforce dynamic request filtering at the edge, evaluating every incoming query against mission-focused logic, guiding conversations toward equitable guidance, and maintaining consistency with our values and tone.

Bias Assessment & Cybersecurity

Before any resource enters our RAG knowledge base, it undergoes a structured bias assessment process examining source diversity, author perspectives, and factual accuracy, and our system prompt embedded within the guardrail framework ensures the assistant draws on these vetted materials first, reinforcing data-driven equity in every response. We also perform a cybersecurity compliance pass at this stage aligned with relevant data-protection regulations (e.g., GDPR and NJDPA), stripping personally identifiable information, enforcing schema validation, anonymizing sensitive fields, and applying secure deletion policies.

Energy Efficiency

By catching invalid or out-of-scope inputs client side, we avoid unnecessary GPU inference, reducing per-request energy use from approximately 0.011 Wh for a GPU call to just 0.00001 Wh for a JS check—over a thousandfold efficiency gain that underscores our efforts to environmentaly sustainable AI services. Feel free to try a simple arithmetic problem or homework question above to see this energy-saving guardrail in action.

Interested in leveraging AI in a similar way at your organization?

Get in touch to explore how our AI-driven equity guidance can advance your nonprofit goals.

Contact Us

Note: Our custom guardrails module is in an early prototype stage. It already filters some out-of-scope queries, but we are continuously refining its logic and plan to introduce more robust validation features as development resources become available. If you’re interested in supporting this initiative, please get in touch.

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