AI agents that auto-triage, diagnose, and resolve L2/L3 support tickets.

Root cause analysis in minutes, not days — with built-in QA to prevent repeat issues.

Triage

RCA

Fix

Test

Joe Acme (via Support) 30s ago

Inbound

“”

auto‑triages every customer issue 4x faster. generates technical RCAs for every issue within minutes of ticket creation.

Auto-triage every escalation

Contract renewal failed with FX rounding error on checkout.

Complete context in seconds
Pulls in customer data, recent deployments, telemetry, and related tickets automatically.
Classify and route intelligently
Determines if it’s a bug, config issue, or known problem — and routes accordingly.
Eliminate the diagnostic loop
No more back-and-forth between support and engineering to gather basic context.
24/7 coverage
Every ticket gets immediate triage, regardless of timezone or on-call schedule.

Trace issues to code
Pinpoints the exact code path, configuration, or dependency causing the issue.
Code simulations
Tests hypotheses against your actual codebase without running production infrastructure.
Reproducible diagnoses
Every RCA includes steps to reproduce, affected customers, and blast radius.
Developer-ready handoffs
When human review is needed, engineers get a complete investigation — not a ticket with a screenshot.

Every resolved ticket teaches PlayerZero something new about your system. The same class of issue is never investigated from scratch twice.

Everything you need to run L2/L3 support with AI — from ticket intake to root cause to resolution.

Ticket system integration

Jira, Zendesk, ServiceNow, Salesforce, and 50+ ticketing systems.

Deep code understanding

Semantic codebase graph across monorepos and microservices.

Runtime signals

Ingests logs, traces, errors, and metrics for real production context.

Governance & approvals

Configurable approval flows, audit trails, and compliance controls.

Multi‑repo at scale

Supports monorepos and polyrepos — scales to billions of lines of code.

Grows into QA & SRE

The same production model powers code simulations and incident response.

Recent highlights

Our smartest models capable of simulating how code runs

A new category of models built to understand and predict how large codebases behave in complex, real-world scenarios

Evaluating how well AI models can anticipate customer-facing issues before they surface in production.

How AI can diagnose issues in complex systems where full observability is impossible.