Decision rights
Every material decision has a named recommender, decision owner, executor, validator, escalation path, and risk acceptor.
Tesseract designs governance as an operating capability: clear authority, evidence, accountability, escalation, and controls proportional to the consequence of the decision.
Every material decision has a named recommender, decision owner, executor, validator, escalation path, and risk acceptor.
Claims are distinguished from assumptions, evidence, inference, and validated outcomes.
High-consequence decisions require stronger review, traceability, testing, and human authority.
AI may recommend, summarize, predict, or prioritize; accountable humans retain defined authority and override.
Data use is connected to purpose, source, quality, access, retention, privacy, and downstream decisions.
Material decisions and interventions remain reviewable so the institution can learn from outcomes.
The governance burden should reflect what the system can affect. A drafting assistant and a system influencing money, eligibility, compliance, employment, health, or customer rights should not be governed the same way.
| Control | Purpose | Expected evidence |
|---|---|---|
| Use-case classification | Determine consequence, reversibility, and review burden | Decision type, affected parties, impact, regulatory context |
| Human authority | Prevent responsibility from being delegated to a model | Named owner, review point, override, escalation |
| Validation | Test whether outputs are fit for the intended decision | Evaluation criteria, test set, failure modes, acceptance threshold |
| Traceability | Make consequential outputs reviewable | Source data, version, prompts/configuration, decision record where appropriate |
| Data governance | Control quality, privacy, access, and purpose | Lineage, permissions, retention, consent, data-quality controls |
| Monitoring | Detect drift, misuse, and unexpected impact | Performance, complaints, override patterns, incidents, periodic review |
Tesseract maintains distinct systems for delivery and certification so authority, commercial incentives, and quality controls remain legible.
Qualified engineering, implementation, architecture, and specialist partners who may execute approved work under defined scopes, acceptance criteria, governance, and performance standards.
A separate future system for education, credentials, methodology training, universities, independent consultants, standards, and authorized certification. It does not confer engineering delivery authority.
Good governance reduces rework, invisible risk, executive confusion, and late-stage surprise. It should enable speed by making the path to a responsible decision explicit.