Agent task and tool design
Define goals, tools, constraints, stopping rules, permissions and approved sources.
AI Agent Development · Menteso
Agents that take useful actions—within defined boundaries.
Create tool-using AI agents that interpret tasks, invoke approved services and coordinate multi-step workflows with logged actions and human approval where needed.
Scope-first approachHuman-led reviewMeasurable acceptance criteria
Service overviewWhat this service means
What this service means
for your business.
Create tool-using AI agents that interpret tasks, invoke approved services and coordinate multi-step workflows with logged actions and human approval where needed.
When to choose it: Best when the task requires multiple decisions or tool calls and cannot be solved by a single response or a simple fixed automation.
Where it starts and stops: An agent can choose among permitted actions based on context; predictable repetitive sequences are usually better placed under AI Workflow Automation.
What we can buildCore ai agent development
Core ai agent development
capabilities.
Scope is tailored to the systems and data your business already uses. The following capabilities describe the principal work involved—not a fixed one-size-fits-all package.
Multi-step orchestration
Coordinate retrieval, reasoning, tool invocation and exception handling without uncontrolled loops.
Human-in-the-loop approvals
Require explicit review for sensitive changes, external communication or consequential actions.
Evaluation and monitoring
Test task completion, tool misuse, loops, prompt injection, cost limits and recovery from failed steps.
Business use casesWhere it creates
Where it creates
practical value.
Each use case is a representative scenario, not a claim that Menteso has delivered that exact project. Project feasibility is confirmed during discovery.
- A sales research assistant preparing a reviewable lead brief from allowed sources.
- An operations agent that gathers information from multiple authorized systems.
- A case-intake agent producing a structured draft for a staff member.
- A support agent proposing next actions before a human approves them.
Typical project outputsDefine the handoff
Define the handoff
before development.
Deliverables and acceptance criteria should be agreed in the statement of work so your team knows exactly what it will review and operate.
- Agent specification and tool permissions
- Workflow graph and error handling
- Functional connectors and audit trail
- Agent evaluation and security tests
- Deployment and support playbook
Engineering & qualityMeasure what matters
Measure what matters
before you launch.
Deployment quality requires more than a working demo. Define representative test cases, edge cases, data rights, operational measures and the people responsible for reviewing results.
What we should evaluate
- Task completion and exception rate
- Tool-call correctness and permission safety
- Time and cost per completed task
- Human intervention and recovery needs
Technology & implementation
Depending on the use case, implementation may use model tool-calling, orchestration frameworks, API integrations, structured output schemas and tracing platforms.
Architecture decisions should be evaluated against security, vendor terms, reliability, team skills and expected operating cost—not chosen only because a tool is popular.
Our delivery process01 / STAGE 02 / STAGE 03 / STAGE 04 / STAGE 05 / STAGE 06 / STAGE
From discovery to operation.
Discover
Clarify success, users, current workflow and constraints.
Assess
Review access, data quality, alternatives and risk.
Design
Define interfaces, model choices and acceptance tests.
Build
Implement and integrate the agreed scope.
Validate
Test quality, edge cases, privacy, cost and response.
Operate
Roll out safely, review monitoring and hand over.
Frequently asked questions
Questions about ai agent development.
Can the agent act without approval?
Only for specifically authorized low-risk actions. Sensitive or irreversible actions should have explicit approval controls.
How do we prevent agent loops?
Define step limits, timeouts, budget caps, tool permissions and escalation routes, and test failure scenarios.
Is every chatbot an AI agent?
No. A chatbot answers conversational requests; an agent is designed to execute bounded actions across tools and workflows.
How are pricing and timelines determined?
Data readiness, integration complexity, security obligations, model evaluation and application scope affect the effort. A discovery discussion establishes a practical estimate and delivery milestones.
What should we include in our first enquiry?
Share a non-confidential description of the intended users, current workflow, available systems, expected volume and desired results. Sensitive records can be reviewed after appropriate access and confidentiality arrangements.
Related AI capabilities
Explore complementary services.
AI Consulting & Strategy
Find realistic AI opportunities, prioritize them by business impact and plan adoption with clear technical, financial and governance cr…
Explore service →Enterprise AI Solutions
Design coordinated AI capabilities for organizations where multiple departments, legacy applications and risk controls must work togeth…
Explore service →Custom AI Application Development
Engineer AI capabilities into SaaS products, mobile and web applications, internal portals and business platforms with usable interface…
Explore service →
