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.


Trusted by industry experts from


Case study
“91% of AI-generated responses showed significant improvement, leading to faster resolutions and better customer experiences.”

Thiru B
VP & Principal Architect


Case study

"Significant differences in cost appear based on the model chosen and the smaller and/or more specialised models (Veritas and Veritas Nano) are an order of magnitude or more cheaper than the general purpose large language models.”

Julian Wiffen
Chief of AI and Data Science

Case study
"Collinear AI’s expertise enabled us to measure our AI Sales Agent’s ability to sell by developing a model based on our conversational data between human agents and customers in just a few weeks. From ideation to execution, they always felt like a part of our team!”

Tomas Uribe
Co-Founder

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."
A huge thank you to my incredible team for making this possible and to our partners Collinear AI for the amazing collaboration."


Solution
Introducing Collinear Environments
Multi-user RL worlds with authentic tools, stateful workflows, and
complete high-fidelity agent trajectories.
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 Gyms
Coding
380 Tasks
Sprint planning across linked issues, bug triage with dependency tracking, and spec documentation that maintains integrity across Jira and Confluence.

Tools:
- Github
- Bash
- Python
- Poetry
Sample Tasks:
- Resolve open Github issues
- Implement a new API endpoint
- Write unit tests
Sample NPCs:
- Product Manager
- Staff SWE
- Engineering Manager
Software & Product Development
220 tasks
Sprint planning across linked issues, bug triage with dependency tracking, and spec documentation that maintains integrity across Jira and Confluence.

Tools:
- Jira
- Confluence
- Slack
Sample Tasks:
- Write user stories with clear acceptance criteria
- Calculate sprint story points
- Link Jira Epic to the right Confluence PRD
Sample NPCs:
- Product Manager
- Staff SWE
- Engineering Manager
ITSM / Enterprise Operations
140 tasks
Sprint planning across linked issues, bug triage with dependency tracking, and spec documentation that maintains integrity across Jira and Confluence.

Tools:
- ServiceNow
- Jira
Sample Tasks:
- Classify a new incident by severity and category
- Locate relevant knowledge base articles
- Determine likely root cause and orchestrate remediation next steps
Sample NPCs:
- Service Desk Agent
- Affected user
- Service Owner
Human Resources
150 Tasks
Sprint planning across linked issues, bug triage with dependency tracking, and spec documentation that maintains integrity across Jira and Confluence.

Tools:
- Workday
- SAP SuccessFactors
- Slack
Sample Tasks:
- Review new applicants for an open role
- Evaluate employee PTO requests
- Resolve employee benefits questions
Sample NPCs:
- Employee
- Hiring Manager
- HR Business Partner
Sales & Procurement
110 Tasks
Sprint planning across linked issues, bug triage with dependency tracking, and spec documentation that maintains integrity across Jira and Confluence.

Tools:
- Salesforce CRM
- SAP Ariba
Sample Tasks:
- Classify an inbound lead into the correct segment
- Build a quote with the correct SKUs and pricing allowed by policy
- Assemble a vendor scorecard using provided KPIs
Sample NPCs:
- Account Executive
- Solution Engineer
- Procurement Manager
Customer Support
220 tasks
Sprint planning across linked issues, bug triage with dependency tracking, and spec documentation that maintains integrity across Jira and Confluence.

Tools:
- Zendesk
- Salesforce CRM
Sample Tasks:
- Classify and route new support tickets
- Approve or deny refunds within policy
- Prevent potential customer churn through retention offers
Sample NPCs:
- Customer
- Tier 2 Support Specialist
- Escalations Manager
Healthcare
170 tasks
Sprint planning across linked issues, bug triage with dependency tracking, and spec documentation that maintains integrity across Jira and Confluence.

Tools:
- OpenEMR
Sample Tasks:
- Retrieve authorized patient data
- Verify insurance eligibility for a scheduled appointment
- Resolve discrepancies between patient-reported systems and existing problem list
Sample NPCs:
- Patient
- Scheduler
- Care Coordinator
Finance
120 tasks
Sprint planning across linked issues, bug triage with dependency tracking, and spec documentation that maintains integrity across Jira and Confluence.

Tools:
- SAP 4/HANA
- SAP Concur
Sample Tasks:
- Classify an incoming invoice into the correct expense category
- Produce a department spend report
- Create financial projections based on incoming receivables
Sample NPCs:
- Budget owner
- Procurement partner
- RevOps manager

Don’t fall behind in the AI race.
Get ahead with Collinear for better AI from development to production.


