Security
AI Agent Security & Governance Model
Tessera builds AI workflow systems that can operate inside real businesses without asking you to trust invisible automation. Access, approvals, logs, and human review are designed in from the start.
Last updated: 11 May 2026
✅ At a glance
- ✓Least-privilege access by default
- ✓Human approval gates for sensitive actions
- ✓Audit logs for agent activity and decisions
- ✓Scoped credentials and per-system access boundaries
- ✓Prompt-injection boundaries for untrusted content
- ✓Human review before public, financial, or destructive changes
What this page covers
This is the practical security model behind Tessera's AI operator work: agents that help with analysis, reporting, content, workflow automation, ecommerce operations, internal tooling, and client-facing processes. The exact systems change by engagement; the operating principles stay the same.
Access model
Agents only get the access a workflow needs
Tessera starts with the smallest useful permission set: read-only where possible, scoped write access only when the workflow genuinely requires it, and separate credentials for separate systems. Broad admin access is not the default operating mode.
Client systems are separated by scope
Each engagement is configured around the systems, tools, accounts, and data boundaries that belong to that client. Credentials, logs, and operational context are not mixed across clients or reused casually between workflows.
Approval gates
Sensitive actions stay human-approved
Agents can draft, prepare, analyse, and recommend. Human approval is the gate for external messages, production changes, financial actions, customer-impacting work, public publishing, destructive operations, and anything outside the agreed scope.
Autonomy expands only after the workflow is proven
Tessera does not jump straight from idea to unsupervised automation. We start with supervised runs, inspect outputs, define failure modes, and only widen permissions when the workflow is reliable and the risk is understood.
Auditability and review
Agent work should be inspectable after the fact
Important runs should leave a trail: what source material was used, what the agent proposed, what changed, what was escalated, and who approved it. The aim is operational clarity, not a black box that everyone has to trust blindly.
Human review remains part of the system
Tessera designs AI workflows so a person can review decisions at the right level: PRs for code, approval queues for messages, task comments for handoffs, and logs for operational activity.
Data and prompt-injection boundaries
External content is treated as untrusted data
Emails, web pages, support tickets, task comments, documents, and webhook payloads can contain hostile instructions. Tessera separates those inputs from system instructions and avoids executing commands embedded in third-party content.
Data handling is defined before automation scales
For each workflow, we define what data the agent may read, store, summarise, transmit, or forget. Sensitive data movement is minimised, and retention is tied to the operational need rather than collected because it is convenient.
Operational controls
Revocation and fallback paths are part of the design
Access should be easy to narrow or remove. Tessera builds workflows with clear ownership, alert paths, manual fallbacks, and rollback options so a problem can be contained without dismantling the whole system.
Security language has to match real behaviour
We avoid vague claims and security theatre. The controls described here are the controls we design around in actual AI operator systems: scoped access, approvals, logs, boundaries, and review.
Planning an AI workflow that needs real access?
We can help define the safe first version: what the agent may read, what it may change, where a human approves, and what gets logged.
Book a 15-minute intro call or email hello@tessera-systems.io.