Real-world RL gyms
for frontier AI agents

Train agents that learn from experience, not just examples. We deliver configurable RL worlds with dense rewards, domain-specific tools, and verifiable outcomes.
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90%
AI responses improved
8x
Faster time to production
70ms
Latency
Problem

Models need real-world experiences, not just examples.

Agents miss
reasoning context.

Examples teach agents “what”. Experiences teach them “why” and “when”.

Agents fail under enterprise constraints.

Sandboxes don’t mirror production. Real systems have approval chains, compliance gates, and stateful context that accumulates over time.

Models can’t learn nuanced behavior.

Sparse rewards hide incremental progress.

No alignment to
real outcomes.

Single-task tests ignore multi-step reality. Real workflows require maintaining context across sessions, balancing competing goals, and respecting safety guardrails.
"Launch of Apriel-1.5-15B-Thinker - ServiceNow's SLM that thinks big. Multimodal reasoner delivering results on par with much larger models like DeepSeek R1m Mistral-medium and Gemini Flash 2.5 - at just one-tenth the size.

A huge thank you to my incredible team for making this possible and to our partners Collinear AI for the amazing collaboration."
Srinivas Sunkara
VP - Applied Research
ServiceNow

Red-team

Employ adversarial testing to proactively catch and mitigate AI hallucinations and unsafe content before your customers do with the widest risk taxonomy on the market

Automated red-teaming and vulnerability assessments for real-world scenarios, scaling up to handle extensive model evaluations tailored to your safety needs.

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Highlights

How you can benefit from Collinear Red-team

Collinear Red-team simulates compliance, prompt injection, data leakage, and edge case scenarios
at scale to uncover and remediate vulnerabilities before they reach your users.

Accelerate Deployment

  • Reduce compliance incidents by 3x
  • Cut Quality Assessment and Red-Teaming time by 90%
  • Go to market 3x faster.

Turn every breach into a stronger defense

Stay one step ahead of vulnerabilities by using Collinear Red Team to:
  • Automatically generate targeted synthetic data from failed attacks
  • Strengthen your AI through focused retraining
Solution

Introducing Collinear Environments

Multi-user RL worlds with authentic tools, stateful workflows, and
complete high-fidelity agent trajectories.

Environments

Multi-user virtual organization with realistic roles (Engineer, Support, Analyst) collaborating on shared projects (releases, patient intake, order fulfillment), mirroring real workflows, multi-turn interactions, permissions, and policies to produce stateful context over time.

Tools

Production-grade tool ecosystems, with APIs and MCP-compatible interfaces for Jira, Confluence, ServiceNow, EMR, Shopify, and airline/hotel systems, enabling realistic tool use and data access.

Tasks

Multi-step objectives mirroring real operational goals, including sprint planning, triaging incidents, updating documentation, processing patient data, or managing bookings and returns.

Verifiers

Automated evaluators that check the environment’s final state, confirming if tasks were completed, data linked, policies followed, and progress achieved. Dense rewards provide interpretable, domain-specific feedback.
Outcomes

Learn faster.
Generalize further. Reason better.

5× faster convergence in complex tool-use environments
3× higher generalization across unseen domains
Lower compute cost per training cycle via dense rewards
Policy-safe exploration across real business workflows

Domain-specific RL worlds

Software & Product Development

Sprint planning across linked issues, bug triage with dependency tracking, and spec documentation that maintains integrity across Jira and Confluence.
Env: Weaver Labs (Jira + Confluence org)
Tools: get_issue, update_status, create_page, link_issue_page
Tasks: Plan sprints, triage bugs, draft specs, write retrospectives
Verifiers: Check Jira–Confluence link integrity, completion ratio, and documentation accuracy

ITSM / Enterprise Operations

Incident classification, intelligent escalation routing, and resolution documentation that prevent recurrence and customer churn.
Env: ServiceNow Simulation
Tools: query_incidents, assign_ticket, resolve_task, check_SLA
Tasks: Classify tickets, escalate incidents, validate resolution notes
Verifiers: Validate SLA compliance, escalation logic, and closure accuracy

Healthcare

Patient data retrieval under HIPAA constraints, multi-specialty routing decisions, and clinical handoffs where incomplete information meets compliance requirements.
Env: EMR Workflow Simulation
Tools: fetch_record, summarize_visit, route_to_specialist, update_followup
Tasks: Retrieve patient info, prepare handoff notes, verify compliance
Verifiers: Check HIPAA-safe reasoning, correct routing, and chart completeness

Retail / E-Commerce

Refund processing with complex policy exceptions, inventory updates across multiple systems, and customer service workflows where errors cascade into retention issues.
Env: Shopify Fulfillment RL Env
Tools: lookup_order, process_refund, update_inventory, create_ticket
Tasks: Handle refunds, verify shipments, manage inventory discrepancies
Verifiers: Confirm refund accuracy, update propagation, and policy alignment

Hospitality / Travel

Reservation modifications with fare rule enforcement, overbooking service recovery, and itinerary changes where single edits affect multiple connected bookings.
Env: Airline & Hotel Ops RL Env
Tools: find_booking, change_itinerary, apply_credit, update_room_status
Tasks: Modify reservations, issue vouchers, resolve overbookings
Verifiers: Check itinerary correctness, fare rules, and service recovery outcomes

Ship smarter models, not bigger ones.

Collinear generates high signal post-training datasets and RL environments that make every release stronger.

Generate Data

Stop launch-and-pray AI.

Simulations catch failures before your customers do.

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