Conversational Agents
Guide users through multi-step workflows, answer questions using live business information, and provide contextual recommendations.
Agentic Workflow Designer
Design, orchestrate, and govern AI-powered business workflows visually.
Connect users, AI models, business data, tools, knowledge, and other agents. Define how an agent receives a request, gathers context, reasons, invokes actions, validates output, and presents the result.
Design the reasoning. Connect the knowledge. Select the actions. Govern the outcome.
Explore the CapabilityBuild Agentic Workflows Visually
Use connected task nodes on a visual canvas to make the sequence of activities and hand-offs visible before deployment.
Compose the process
Combine user input, business-data retrieval, LLM reasoning, tool execution, Skills, conditional routing, agent invocation, output validation, and rendering.
Configure each AI task
Set model selection, reasoning effort, and prompt instructions at task level.
Make orchestration visible
Connect task nodes to define how information and control pass through a multi-step AI experience.
Conversational and Background Experiences
Choose the interaction pattern that fits the business task, from progressive conversations to AI processing behind an application action.
Interactive conversations
Let users ask questions, provide information progressively, and work with an AI assistant through multiple steps.
Embedded background agents
Trigger agents from a Protrak application experience or API and return results within the application.
Survey generation
Connect a background agent to a Protrak widget through APIs so survey generation runs as part of the user's application experience.
Structured and Validated AI Outputs
Associate expected output formats with AI tasks when the application requires more than free-form text.
Defined output structures
Use a configured JSON structure to generate required fields, titles, and question information consistently for a survey workflow.
Task-specific formats
Configure multiple output formats and associate them with the appropriate agent or LLM task.
Validation before delivery
Check responses against the required schema and correct them before returning the result to the application.
Reuse Business Knowledge Through Agent Skills
Define instructions, context, reference information, and the expected approach once for a repeatable task.
A repeatable approach
Capture the objective, business instructions, required checks, reference content, expected result, and steps the agent should follow.
Skills for the right experience
Make a defined Skill available to the appropriate AI experience so users do not need to repeat the complete procedure in every prompt.
Asset maintenance history
Use a defined sequence to retrieve and organize current and historical maintenance requests for an asset.
Control Actions Through Agent Tools
Skills describe how work should be performed; tools determine which actions an agent can take. Review descriptions and input and output schemas before making tools available.
Protrak-native tools
Perform supported operations such as creating, updating, connecting, promoting, or deleting records.
External tools
Use capabilities exposed by connected systems through MCP Servers.
Utility tools
Support common processing needs, including date- and time-related operations.
Custom tools
Extend the library with organization-specific functions where existing tools do not cover the required action.
Agent Patterns You Can Design
Data Intelligence Agents
Interpret natural-language questions, retrieve business data, and return summaries, tables, or visual results.
Process Automation Agents
Execute scheduled, application-triggered, or event-driven validation, change analysis, compliance checks, and reporting.
Decision Support Agents
Analyze information and evaluate options against business context or defined rules to provide structured recommendations.
Guided Task Agents
Collect information, invoke tools, and prepare a confirmed business outcome for reviews, approvals, and service processes.
Multi-Agent Orchestrators
Coordinate specialized agents, delegate parts of a complex request, and consolidate results into one outcome.
Enterprise Use Cases
- AI-generated surveys and forms
- Guided service request resolution
- AI-assisted configuration
- Cross-system workflows combining Protrak actions with MCP-connected tools
Business Value
- Reduce custom orchestration development.
- Reuse workflows, Skills, and Tools across scenarios.
- Embed AI directly into business applications.
- Produce structured rather than unpredictable AI outputs.
- Combine AI reasoning with deterministic business actions.
- Connect internal and external systems within one agent experience.
- Standardize recurring AI-supported work.
Design AI Workflows Around Business Outcomes
Design the reasoning. Connect the knowledge. Select the actions. Govern the outcome.