Engagement length
Usually a short review and controls sprint before or during agent rollout.
AI agent security · trust before autonomy
AI agent security for teams that cannot afford invisible automation
Useful agents need access. Safe agents need boundaries. Tessera designs agent systems around scoped permissions, human approval gates, audit trails, and clear data handling rules.
The point is not to make agents harmless toys. It is to let them do valuable work without handing them the keys to the business on day one.
Buying question
How do we avoid unsafe access or bad decisions?
If you are considering agents inside real operations, security is not a footnote. You need to know what the agent can read, what it can write, who approves risky actions, and how mistakes are detected.
Tessera reviews agent workflows for access risk, designs safe operating boundaries, and implements controls that make the system observable and governable.
Fit guidance
You probably need this if…
- You are about to let agents read or write real business systems and need boundaries before rollout.
- Stakeholders are worried about credentials, prompt injection, sensitive data, or invisible decisions.
- You need a practical governance model: permissions, approvals, logs, rollback, and escalation.
You probably do not need this if…
- Your agent is still a private prototype with no external actions or sensitive data access.
- You want legal compliance certification rather than operational security design.
- You are unwilling to reduce scope or add human approval gates where the risk demands it.
What you get
Starting point
Existing or planned workflows, tool permissions, credentials, data flows, and risky actions.
Client involvement
Access inventory, risk review, approval decisions, and sign-off on operating boundaries.
Output
Permission model, approval gates, logging plan, incident paths, and safer implementation recommendations.
Use cases
Permission design
Define read/write scopes, per-tool access, environment separation, credential handling, and least-privilege defaults.
Approval gates
Keep humans in the loop for external messages, destructive actions, financial changes, public publishing, and sensitive data movement.
Audit logging
Record what the agent saw, decided, changed, and escalated so incidents can be understood instead of guessed at.
Prompt injection resistance
Treat external content as hostile data, separate instructions from evidence, and avoid executing commands embedded in third-party content.
Data boundaries
Classify what the agent may store, summarise, transmit, or forget across sessions and workflows.
Incident response
Plan fallback modes, revoke paths, alerting, and remediation steps before autonomy expands.
Matched proof
Scoped access model
Tessera separates external content from instructions, limits tool permissions, and keeps secrets out of prompts and logs.
Review security modelHuman approval gates
External messages, destructive actions, financial changes, and reputation-sensitive outputs stay behind explicit human review.
Read security practicesObservable operation
Agent workflows run with logs, state, rollback paths, and alerts so failures are diagnosable instead of mysterious.
See operation proofProcess
01
Inventory access
List every system, credential, data class, read/write action, external surface, and approval point the agent may touch.
02
Threat model
Identify prompt injection, overbroad permissions, data leakage, silent failure, and bad-decision paths before rollout.
03
Design controls
Define least privilege, human gates, logs, rollback paths, environment separation, and incident response for the workflow.
04
Validate
Test the boundaries against realistic cases and adjust scope before autonomy or write access expands.
FAQ
Can agents be secure enough for business workflows?
Yes, if autonomy is earned incrementally and bounded by least privilege, approvals, logs, and clear rollback paths.
Is our data safe?
The system is designed around least-privilege access, private credentials, limited retention, and human-controlled permissions. The agent connects only to what the workflow needs.
How do you stop an agent making bad decisions?
Tessera uses narrow scopes, approval steps, logs, limited data access, and human review for decisions that affect money, customers, legal exposure, or brand reputation.
What is the biggest practical risk?
Overbroad permissions. Most agent risk comes from giving a vague system too much access before the workflow is proven.
Do you support human-in-the-loop workflows?
Yes. Human approval is the default for sensitive actions. The agent can prepare the work; a person approves the outcome.
How does this relate to Tessera’s security page?
This page covers agent-specific governance. The security overview explains Tessera’s broader approach to scoped access and data handling.
If the workflow matters, make it operational.
Bring one messy workflow. Tessera will map the risk, define the operator boundary, and show the smallest useful system worth deploying.