Terms shift between teams
The same customer, risk or approval term can mean different things across systems. Agents need controlled business meaning before they can apply rules consistently.
Emerging corporate service
Put AI agents to work with controls you can inspect.
Define the terms an agent uses, the actions it may take, the evidence it must show and the decisions that still require a person.
- One consequential workflow
- Named owners and approval points
- Evidence before wider autonomy
A specialist service from Tesseract Advisory & Consulting.
⚡ Interactive Agent Guardrail Simulator
GOVERNED
Meaning
:PaymentOrder schema • Currency, EUR limit, ISO 20022
Authority
Bounded Workflow
Autonomous Execution Engine
Operates strictly within verified semantic envelope.
Evidence
0 SHACL violations; GLEIF identifier verified
Review
Head of Treasury cryptographic sign-off
PermissionsExplicit • Gated
EvidenceInspectable • 100%
ApprovalNamed Human Gate
The control gap
Your agent can act. Can your organisation explain why?
As agents move from answering questions to requesting actions, vague rules become operational risk. Governance has to live in the workflow, not in a policy document nobody checks.
Permissions blur at the edges
A helpful assistant can become an unsafe operator when data access, tools and action rights are implicit. Each role needs a visible operating envelope.
Evidence disappears at review
A polished answer is not enough for a consequential decision. Owners need to inspect the source, rule and evaluation trail behind an output or action request.
Who owns the decision
Built for the leaders who will be asked to account for the agent.
This is for organisations moving beyond experimentation into workflows where permissions, evidence and escalation must be explicit.
CIOs and CTOs
Set operational controls, integration boundaries and clear technical ownership.
Chief Data and AI Officers
Create consistent agent standards and evidence that teams can evaluate.
Risk and compliance leaders
Make permissions, approval gates and review trails visible without pretending software replaces legal judgement.
Operations and product owners
Match agent rules and escalation paths to the way the real workflow operates.
A practical control model
Four layers turn policy into something people can inspect.
Ontology is one part of the answer, not the whole answer. Meaning, permissions, provenance, evaluation and human review work together.
In plain English: an ontology is a controlled map of the terms, entities and relationships your organisation relies on. It gives important words defined meanings before an agent applies rules to them.
Meaning
Give the agent a controlled map of business terms, entities and relationships, so key words have defined meanings.
Result: less ambiguity across teams and systems.Authority
Specify the data, tools and actions available to each role. Name the owner, approval point and escalation route.
Result: permissions people can see and challenge.Evidence
Require important outputs and action requests to carry their source, rule or evaluation trail.
Result: a review starts with evidence, not guesswork.Review
Keep consequential decisions with named people. Expand autonomy only for specific actions after evidence meets an agreed bar.
Result: autonomy grows by action, not by assumption.
The business value
Move one agent from interesting demo to accountable workflow.
The goal is not a bigger governance document. It is a smaller, clearer operating envelope that teams can test, inspect and improve.
Shared agreement on boundaries
Business, technology and risk leaders work from the same map of terms, permissions and ownership.
Clearer evidence for each decision
Reviewers can see which source, rule or evaluation supports an important output or action request.
Controlled expansion of autonomy
Teams widen one defined action only when agreed evidence supports it, while consequential decisions keep named owners.
Discovery to pilot
Start narrow enough to learn something real.
We begin with one consequential workflow and make the controls explicit. Discovery creates a clear blueprint for the decision. If the evidence supports proceeding, the next engagement builds and evaluates a controlled pilot.
Choose one consequential workflow
Select a decision or action where ambiguity, permissions and evidence genuinely matter.
Map meaning and authority
Define the business vocabulary, available data, permitted tools, named owners and escalation points.
Build a controlled pilot
Allow the agent only to read approved sources or prepare drafts, then evaluate its outputs against agreed cases.
Review the evidence and decide
With accountable owners, choose whether to stop, revise or widen one specific action.
Discovery is the first engagement. A controlled pilot is scoped separately only when the evidence supports proceeding. Timing depends on the workflow, systems and approval requirements.
Relevant foundations
Built on work across meaning, validation and staged autonomy.
Evidence boundary: the work below demonstrates components we can build on: ontology engineering, machine readable validation, agent evaluation and staged autonomy. These are adjacent projects, not client outcomes from this emerging service.
National Digital Twin Programme
An open source AI ontology extension tool delivered for the National Digital Twin Programme, with a separate national skills ontology demonstration showing machine readable validation at scale.
See the ontology foundation →Open Ontologies
Open source tooling led by our partner Fabio Rovai for building, validating, querying and reasoning over RDF and OWL ontologies.
See the open tooling foundation →Production AI support agent
A separate production agent project using human review, structured evaluation, guardrails and staged autonomy, with write actions kept behind feature flags during the pilot.
See the agent foundation →
Clear boundaries
Governance starts with honest limits.
Tesseract Academy does not provide legal advice or compliance certification.
No AI system can be guaranteed safe.
Consequential actions remain behind named human approval gates.
Any increase in autonomy is limited to specific actions after agreed evaluation evidence.
Discovery separates written control design from technical enforcement. Permissions and approval gates depend on your approved identity, access and workflow systems.
This is an emerging corporate service. The right controls depend on your workflow, data, systems, obligations and accountable owners. Discovery is designed to surface those constraints before a pilot is scoped.
One workflow. Clear boundaries.
Choose the first agent your organisation needs to trust.
Bring us the workflow, the people accountable for it and the action that matters most. We will help you decide whether a bounded governance pilot is the right next move.
No standard package is assumed. We start by understanding the decision, the systems and the people responsible for it.