A defined role for each agent
Separate responsibilities and information access so the system’s behavior is easier to reason about.
Agentic AI System
Agentic systems coordinate model-driven steps, tools, and context to work through a defined objective. We design the orchestration and controls around your use case, including when an agent should stop, ask, or hand work to a person.
Outcomes to plan for
We shape this work with your team around real workflows, the systems already in place, and the outcomes the project needs to support.
Separate responsibilities and information access so the system’s behavior is easier to reason about.
Limit the actions agents can take and plan for authorization, validation, and human approval.
Create scenarios to review task completion, error handling, handoffs, and behavior outside expected inputs.
Agent coordination
Agent roles, shared context, tool permissions, evaluation, and handoffs all need clear boundaries. Begin with a system that can be observed, reviewed, and stopped safely when work falls outside its limits.
Illustrative orchestration model
Routes work and applies shared limits
A bounded role
A bounded role
A bounded role
Concept diagram · a project may use fewer roles or a different orchestration pattern.
Scope and delivery
The final scope depends on your users, systems, constraints, and the first useful release. Typical work can include:
Defined to fit the agreed project scope
Delivery path
The sequence is shaped around the requirements and review points agreed for this service.
Break down the objective and specify agent roles, allowed tools, and shared context.
Plan coordination, state, validation, escalation, and recovery behavior.
Review multi-step scenarios, tool use, handoffs, and unwanted actions.
Technology and architecture
These are relevant options rather than a fixed bundle. Final choices depend on your existing environment, requirements, integrations, and operating needs.
Orchestration service option
Agent orchestration option
Model provider option
Model provider option
Local model option
Model ecosystem option
Before the build
Every service has different constraints. These prompts make the decisions behind scope visible before implementation begins.
Can the objective be decomposed into clear, reviewable steps?
What data and actions should each agent be allowed to access?
How will completion, failure, and human handoff be assessed?
Direct answers
Every project is different. These answers cover common starting questions; the details can be scoped to your systems and requirements.
An agentic system may coordinate multiple model-driven steps, tools, and decisions to pursue a defined goal. The appropriate design depends on the workflow and its required human controls.
We can design tool permissions, input and output checks, action limits, approval points, and fallback behavior. These controls reduce risk but do not make model behavior infallible.
Connected capabilities
Make approved business knowledge searchable through retrieval-augmented generation systems grounded in your data.
Explore serviceAutomate defined, multi-step business workflows with AI agents that work across your connected tools.
Explore serviceAdd AI capabilities to existing and legacy technology stacks while building on the systems your teams already use.
Explore serviceStart with the challenge
Share what you know so far. We can help identify the key questions and a practical next step.