Agentic Data. Built for Action.
Train Agents That Act, Not Just Answer
From tool-use traces to multi-step task demonstrations, deliver structured agentic data that teaches models to plan, execute, and recover at scale.
Start Building Agent Data
The Agentic Data Gap
Conversation Data Won’t Train Agents
Instruction-following and task-completion are fundamentally different capabilities.
Agents require sequential decision-making, tool invocation, and error recovery — none of which standard dialogue datasets are designed to capture.
The Solution? Structured task trajectories and annotated execution traces that give models the behavioral signal needed for reliable agentic performance.
Missing Tool-Use Signal
Models trained without tool-invocation data lack the grounding needed to select, sequence, and recover from API and function calls reliably.
No Recovery Patterns
Without annotated failure and correction sequences, agents cannot generalize error handling to unseen tasks in production environments.
Shallow Task Depth
Single-turn demonstrations fail to capture the planning horizon and intermediate reasoning required for multi-step agentic workflows.
Agentic Data Infrastructure
Designed for Agent Behavior
Building agent training data requires structured task design, execution tracing, and behavioral annotation — not repurposed chat datasets.
01
Task Trajectory Design
Structured end-to-end task sequences with defined goals, tool environments, and measurable completion criteria.
- Goal-Oriented Sequences Each workflow is structured around defined objectives with measurable completion criteria
- Tool-Aware Environments Tasks are scoped within specific tool environments to reflect real agent deployment conditions
02
Tool-Use Annotation
Every function call, API invocation, and parameter decision labeled and validated against expected execution paths.
- Execution Path Validation Every API call and parameter decision is labeled and checked against expected execution paths
- Function-Level Precision Individual tool invocations are annotated to support accurate agent decision-making at runtime
03
Failure & Recovery Traces
Annotated error states paired with correction sequences to support generalizable agent behavior across production environments.
- Error State Annotation Edge cases and failure points are documented with structured correction sequences
- Production Generalization Recovery traces are designed to improve agent resilience across diverse real-world environments
Data Types
Full-Spectrum Agentic Data Coverage
Type
Description
Use Case
Task Demonstrations
End-to-end annotated trajectories covering goal decomposition, step sequencing, and task completion.
Training enterprise AI agents for automated workflow execution and multi-step business process automation.
Tool-Use Traces
Labeled API calls, function invocations, and parameter selections across single and multi-tool environments.
Building reliable AI copilots for developer tooling, CRM automation, and enterprise API orchestration.
Failure & Recovery Sequences
Annotated error states paired with correction paths for robust agent behavior under real-world conditions.
Improving agent resilience in production deployments for customer support, logistics, and financial operations.
Reasoning & Planning Traces
Chain-of-thought and scratchpad annotations surfacing intermediate decision-making for complex agentic tasks.
Developing advanced reasoning models for legal research, strategic decision support, and autonomous planning systems.
Agent Data Workflow
From Task Design to Training-Ready Trajectories
01
Task Environment Scoping
Define agent objectives, available tools, success criteria, and failure boundaries aligned to your target deployment context.
02
Trajectory Collection & Annotation
Capture full task executions with step-level labels, tool-use annotations, and decision rationale across diverse task instances.
03
Behavioral QA & Validation
Review trajectories for logical coherence, tool correctness, and goal alignment before training set inclusion.
04
Delivery
Export structured datasets in JSON, JSONL, or custom schema with full trajectory provenance documentation.
Ready to Align?
Define your agentic data requirements and receive a structured proposal within 48 hours.
Request a Data Scoping Call