People responsible for informed decisions
- Builders and knowledge owners
- AI product owners and data stewards
- Security, privacy, and governance practitioners
- Reviewers responsible for retrieval quality and operations
Batoi Learn Lab
Governed RAG and Knowledge Lab
Govern sources, access, provenance, retrieval, grounding, citations, adversarial tests, monitoring, deletion, and retirement for knowledge-enhanced AI.
Individual developers can begin in a free, non-production Developer workspace. Team assignments, teaching, and governance features depend on plan and role.
Bring a real, bounded context
- A synthetic or approved sanitized knowledge use case
- Named source owners, intended users, purpose, and access classes
- Known freshness, retention, deletion, security, and answer-support expectations
Learning Outcomes
Develop reasoning that can withstand review
The Lab combines method, guided practice, evidence, assessment, reflection, and an applicable output.
Authorize knowledge
Define authoritative sources, owners, purpose, users, access, sensitivity, freshness, retention, and exclusions.
Preserve ingestion lineage
Keep source identity, versions, permissions, transformations, citation anchors, deletion, and derived content traceable.
Design grounded retrieval
Apply access before disclosure and define ranking, conflicts, citations, clarification, and abstention.
Test and operate
Evaluate relevance, support, leakage, injection, poisoning, freshness, deletion, latency, cost, incidents, and retirement.
Guided Learning Path
Learn → Try → Assess → Reflect → Apply
Each stage strengthens the evidence and preserves the distinction between learning and operational authority.
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1
Learn
Review source authority, access, lineage, grounding, citations, adversarial risks, monitoring, and retirement.
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2
Try
Design a governed workflow using a synthetic multi-source corpus and role boundaries.
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3
Assess
Test permitted, restricted, conflicting, poisoned, deleted, and unsupported cases.
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4
Reflect
Identify the source or access condition that most changes the operating decision.
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5
Apply
Prepare a governed knowledge and retrieval decision pack for authorized Build review.
Evidence produced through the Lab
A governed decision pack covering source authorization, access, ingestion and lineage, retrieval, grounding, citations, abstention, adversarial tests, refresh, deletion, incidents, recovery, retirement, limitations, and accountable ownership.
Transparent criteria support improvement
- Knowledge purpose and source authority
- Workspace and role access
- Ingestion provenance and deletion lineage
- Retrieval, grounding, citation, and abstention
- Adversarial evaluation, monitoring, recovery, and retirement
Feedback and reflection support retry and mastery; they do not replace destination review or approval.
Responsible Boundaries
Practice remains bounded and reviewable
A completed Lab demonstrates learning evidence. It does not grant production authority, certify compliance, accept risk, or bypass human decisions.
The Lab connects no production corpus, vector service, provider, model, or credential.
Synthetic retrieval outcomes do not prove authorization, grounding, security, or production readiness.
Application requires reviewed evidence, and Build revalidates source, access, current versions, and authority before action.
Frequently Asked Questions
About this Lab
No. It uses a versioned synthetic corpus to design and assess a governed workflow without contacting a provider or production source.
Filtering after generation can expose restricted content to the model, response, cache, or logs. The Lab treats authorization as an upstream retrieval boundary.
Continue Through My Batoi
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My Batoi manages authentication and workspace selection before you enter the workspace-scoped Learn capability.