Responsible AI & Human-in-the-Loop Governance
How Funding Bangladesh deploys artificial intelligence exclusively as a citation-backed research assistant with strict human official oversight.
AI research architectures, citation schemas, and explainable risk calculation algorithms are fully implemented in code. Because enterprise LLM API keys are not active in production, Automated AI Research is currently NOT LIVE. The platform strictly relies on deterministic checks, known-source document retrieval, and human official compliance review.
1. Strict Source Grounding & Mandatory Citations
Every AI research run must link claims directly to verified public registries, company domains, or documentary filings. Uncited AI assertions are rejected automatically by the system.
2. Zero Final Authority (Human-Only Verification)
AI research models assist compliance officers by cross-referencing information and flagging risk signals. AI cannot assign final 'VERIFIED' or 'REJECTED' status; all decisions require authorized human official sign-off.
3. Explainable Risk Intelligence (No Black-Box Scores)
Every calculated risk level (Low, Moderate, Elevated, High, Critical) is accompanied by positive trust factors, negative risk signals, confidence indicators, and actionable mitigation guidance.
4. Anti-Hallucination Guardrails
When public search finds insufficient registry data, the engine returns 'INSUFFICIENT_PUBLIC_EVIDENCE' instead of interpolating or hallucinating corporate facts.
5. Dual-Gate Controlled Publication
Creating an applicant profile or project draft does not publish it to the marketplace. Verified sponsor status and separate official project publication approval are mandatory.
6. Data Privacy & Confidentiality Isolation
Private investor mandates, confidential financial feasibility models, and NDA-protected data room documents are strictly isolated and never used for public model training.