Real-world environments for frontier agents
Collinear Environments provide configurable RL worlds with dense rewards, domain-specific tools, and verifiable outcomes, enabling models to act, reason, and adapt like professionals.
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.
Static datasets capture text, not decision traces.
Agents fail under enterprise constraints.
Synthetic sandboxes lack authentic tools and hierarchies.
Models can’t learn nuanced behavior.
Sparse rewards hide incremental progress.
No alignment to
real outcomes.
Isolated benchmarks ignore policy & safety dynamics.
"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
Environments
Simulated organization with multiple roles (Engineer, Support, Analyst, QA) collaborating on shared projects (releases, patient intake, order fulfillment), mirroring real workflows, permissions, and policies.
Tools
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
Why Contact Centers Choose Collinear's Solution
Software & Product Development
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
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
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
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
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
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
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
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
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
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
Stop launch-and-pray AI.
Simulations catch failures before your customers do.