Where is the process losing time, quality or control?
The context advantage
Build the agent. Skip the stitching.
The application already defines the business. An agent can be grounded in the same records, process state, validation, roles, evidence and access model instead of rebuilding that context through a separate data and integration programme.
External agent projectcontext rebuilt at every edge
Data connectorPermissions copyWorkflow APIPolicy promptChannel botSeparate logs
Agent
Amoga native contextone inherited application graph
Application graphRecords & relationshipsWorkflow stateRules & validationsRoles & permissionsDocuments & evidenceOperational measures
inherits
Governed agentsame context · explicit authority
Agent Builder
From job description to governed deployment.
Agent Builder treats an agent as an enterprise actor, not a prompt. Its job, skills, tools, context, refusal boundaries, model, budget, evaluation and owner travel together.
- 01Describe
Define the job, the person or process it serves, what good looks like and what it must never do.
→ - 02Compose
Select skills and tools; declare instructions, boundaries, model and operating budget.
→ - 03Ground
Bind the records, workflows, documents, policies, roles and measures the job requires.
→ - 04Evaluate
Run scenarios, inspect evidence, test refusals and verify the human hand-off before release.
→ - 05Launch
Assign the mode, channel, scope and owner; observe every run against the same controls.
Describe the job
Build an agent that watches priority orders, gathers the cause of risk, prepares a recovery action and routes any promise change to the regional owner.
Propose onlyOrder operationsRegional approval
Agent definition · draftReady to evaluate
- Job
- Priority Order Agent
- Context
- Orders · inventory · workflow · policy
- Tools
- Read records · prepare recovery · notify owner
- Authority
- Propose; cannot commit customer promise
- Owner
- Regional Operations Lead
Five ways to work
Different jobs. One governed foundation.
The mode changes where and how an agent participates. The underlying job, context, tools, policy and evidence model remain governed as one definition.
Assistant agent
Helps an employee perform work in context.
“Explain the risk, gather the evidence and prepare the next action.”
Context attached
Record on screenavailable
Workflow stageavailable
Applicable policyavailable
User roleavailable
AuthorityPrepare · user decides
Every run retains inputs, tools, outputs, policy and human decisions.
Engagement agent
Continues governed conversations with people outside the enterprise.
“Respond through an enabled channel and preserve the thread for human hand-off.”
Context attached
Customer contextavailable
Conversationavailable
Consentavailable
Channel policyavailable
AuthorityBounded by assigned job
Every run retains inputs, tools, outputs, policy and human decisions.
Trigger agent
Responds when an event, threshold or schedule requires work.
“Gather the affected records, evaluate the rule and route the proposed action.”
Context attached
Trigger eventavailable
Conditionavailable
Action scopeavailable
Approval pathavailable
AuthorityBounded by assigned job
Every run retains inputs, tools, outputs, policy and human decisions.
Employee agent
Receives a named role, a queue and explicitly assigned work.
“Own a bounded queue, collaborate with colleagues and escalate exceptions.”
Context attached
Agent identityavailable
Job titleavailable
Assigned queueavailable
Escalation owneravailable
AuthorityBounded by assigned job
Every run retains inputs, tools, outputs, policy and human decisions.
GRID agent
Prepares process intelligence for people and other agents.
“Find the shared bottleneck behind several at-risk outcomes and show the evidence.”
Context attached
Process graphavailable
Measuresavailable
Patternsavailable
Evidence trailavailable
AuthorityAnalyse · explain · alert
Every run retains inputs, tools, outputs, policy and human decisions.
Enterprise control
The agent is accountable because its authority is explicit.
A confident answer is not a control. Amoga makes the actor, data scope, action scope, model, budget, policy, evidence and human checkpoint part of the agent definition and run history.
Decision and evidence logRUN-4817
Priority Order Agent
Opened assigned case
Scoped GRID
Attached bottleneck pattern and measures
Evidence Priority Order Agent
Prepared recovery action
Proposed Regional Operations Lead
Reviewed evidence and approved
Human gateEvery action: actor · role scope · model · tools · evidence · owner
GRID
Intelligence prepared once. Available wherever work needs it.
Graph Reasoning and Intelligence Discovery connects process structure, measures and observed patterns into a shared layer of meaning. People and governed agents can use that intelligence to ask better questions, surface changes and decide where attention belongs.
GRIDProcess intelligencegraph · measures · patterns · evidence
Processesstages · cases · queues
Measureslead · lag · thresholds
Relationshipspeople · records · events
Evidencesource · time · confidence
Which targets are moving, and which leading indicators explain it?
What changes after volume, mix and difficulty are considered?
Where should attention or investment move next, and why?
Give one agent a real job.
Start with a bounded piece of work, the application context it needs and the person who owns the outcome. We will show how the job becomes an agent definition that can be evaluated and governed.