How eSora Labs approaches AI systems with human judgment, governance, traceability, and accountability.
eSora Labs designs, builds, and supports technology for high-trust environments. Our responsible AI approach is based on human judgment, governance, traceability, auditability, security, and accountability.
This policy applies to AI-related websites, products, prototypes, research, internal tools, and services operated by eSora Labs, Barnabus Inc., eSora Studio, and related affiliates, unless a separate written agreement provides additional requirements.
Human judgment first: AI should support accountable people, not replace them.
Governance by design: AI systems should include policies, review gates, traceability, and escalation paths.
Evidence and auditability: Important AI outputs should be connected to records, evidence, rationale, and version history.
Safety and accountability: AI systems should be evaluated for intended use, foreseeable misuse, limitations, and potential harm.
In high-trust or regulated settings, AI outputs should be reviewed by qualified human users before use in consequential decisions. AI-generated content should not be treated as final professional advice without human review.
We do not use customer confidential data, PHI, government data, or enterprise data to train public or third-party foundation models unless expressly authorized in writing. Public forms must not be used to submit sensitive or regulated data unless an approved secure channel has been provided.
AI systems should be evaluated based on intended use, data quality, limitations, performance, security, safety, usability, and user context. Evaluation may include human review, test cases, bias checks, and operational monitoring.
AI systems may reflect limitations in data, model behavior, user input, or deployment context. We work to identify, reduce, and communicate relevant risks including bias, incomplete data, overreliance, and inappropriate use.
For high-impact use cases, AI systems should include appropriate safeguards, escalation paths, and review gates. Barnabus workflows may include pre-authorization harm verification, audit trails, and human-controlled release.
Where appropriate, AI outputs should be traceable to inputs, system state, evidence, model version, policy checks, and user actions.
AI systems in healthcare, government, defense, aerospace, semiconductor, or other regulated settings may require additional validation, documentation, contracting, privacy safeguards, and institutional approval before deployment.
Users may not use our websites, tools, or services to unlawfully discriminate, create harmful content, bypass security controls, process unauthorized sensitive data, make unsupported medical or legal decisions, or deploy AI without appropriate agreements.