Lightrun

What Lightrun does

Lightrun is an AI-native reliability engineering platform that enables engineering teams and AI agents to autonomously prevent and remediate software issues across the SDLC, from code to production. It closes the gap between AI-generated code velocity and reliable production systems by generating live runtime context at the moment of failure. Lightrun proves root cause and validates fixes without code changes, redeployments, or restarts. The platform provides a single runtime sensor that grounds coding agents and AI SRE, allowing for verification of every change with live context, resolution of production issues surgically, and strengthening of resilience. It also enables runtime-aware development, evidence-based issue resolution, and secured autonomous workflows by providing direct, read-only access to production at every stage of the development cycle. Lightrun aims to enable self-healing software by grounding AI-driven investigation, remediation, and prevention in live runtime behavior, moving away from predefined telemetry or post-incident guesswork.

Products

• Lightrun AI SREAn AI-native reliability engineering platform for support, SRE, and platform engineering teams. It offers core triage, root cause analysis workflows, remediation suggestions, and integrates with various tools. Available in Free, Pro, and Enterprise plans with increasing features like automatic alert investigations, knowledge memory engine, RBAC, and full audit logs.
• Lightrun Runtime ContextEnables AI agents and engineers to investigate live systems without redeploying. It supports multi-instance debugging (K8s, Serverless etc.) and integrates with AI coding assistants and AI agents. Available in Pro and Enterprise plans with enterprise-grade security, compliance, and deployment options.
• Lightrun SandboxA secure, read-only sandbox environment for testing and validating code in production without risking users or affecting running state. It allows for dynamic telemetry and is part of the Lightrun Runtime Context offering.
• Runtime Aware PR VerifierA new feature that simulates how each change affects the live system and validates if it solves the ticket before merging, using live runtime context.
• Lightrun MCP (Management Control Plane)The interface for supplying AI assistants with live runtime context, enabling real-time validation and tracing against running systems without redeployments or pre-instrumentation.
• LogOptimizerA tool to reduce logging costs by identifying redundant events and suppressing low-value data while preserving high-signal data.

Key capabilities

• AI-native reliability engineering platform
• Live runtime context generation
• Autonomous prevention and remediation of software issues
• Root cause analysis and fix validation without code changes, redeployments, or restarts
• Inline runtime sensor for agentic workflows
• Runtime-aware development
• Evidence-based issue resolution
• Secured autonomous workflows
• Query live production efficiently and accurately
• Simulate PR behavior against live systems
• Debug production issues without redeploying
• Automate error remediation end-to-end
• Enterprise-grade security and compliance (ISO 27001, SOC 2 Type II, GDPR, HIPAA alignment)
• Full RBAC, SSO
• Dynamic Logs
• Real-time Snapshots
• Performance Metrics
• Counters
• Custom Metrics
• Conditions & TTL
• Multi-Instance Debugging (K8s, Serverless)
• PII redaction during investigations
• Full audit logs and reports
• On-prem deployment options
• Dynamic telemetry
• IDE plugins (IntelliJ, PyCharm, WebStorm, VS Code, Visual Studio)
• CLI Support
• Web Editor
• Logging Tool Integrations
• Reporting
• Runtime Reachability Assessment
• Dynamic SBOMs
• Webhooks

Use cases

• Validate code with live production context
• Investigate systems with live production context
• Solve issues with precision using live production context
• Debug live production environments
• Validate code before release
• Performance analysis
• Autonomous remediation of software issues
• Runtime-verified root cause analysis (RCA)
• Triage and route alerts
• Fix recommendations and postmortems
• Code deep research
• Verify every change with live context
• Resolve production issues surgically
• Inspect live execution
• Triage incidents
• Propose fixes
• Capture runtime evidence
• Generate postmortems
• Scope issues
• Validate every PR with live runtime context
• Query how code is actually executing in production
• Simulate how a PR will behave before it ships
• Automate error remediation
• Accelerate time to market
• Improve developer productivity
• Reduce logging costs
• Feature validation in production environments
• Safely test code on live production traffic
• Developer observability for production debugging
• Design new code in full context
• Diagnose issues with runtime evidence
• Validate fixes in live runtime
• Eliminate the validation bottleneck for AI-generated code
• Break out of local reproduction loops for debugging
• Troubleshooting by runtime

AI approach

Lightrun is an AI-native reliability engineering platform that enables engineering teams and AI agents to autonomously prevent and remediate software issues across the SDLC. It provides live runtime context to AI agents, allowing them to validate code, investigate systems, and solve issues with precision. The platform grounds AI reasoning in live execution evidence to prevent 'hallucinated root causes' and enables autonomous remediation by validating fixes in a secure, read-only sandbox. It integrates with various AI coding assistants and AI SRE tools.

Tech named: Gemini, Amazon Q, Codex, Windsurf, Claude Code, Cursor, Antigravity, GitHub Copilot, Kiro, Junie, JetBrains AI Assistant, Google Antigravity

What it says sets it apart

• AI-native reliability engineering platform
• Generates live runtime context at the moment of failure
• Proves root cause and validates fixes without code changes, redeployments, or restarts
• Closes the gap between AI-generated code velocity and reliable production systems
• Provides direct, read-only access to production for AI agents and engineers
• Enables self-healing software by grounding AI-driven investigation, remediation, and prevention in live runtime behavior
• Replaces 'log everything' model with precise, on-demand runtime context
• Secure by design, enterprise grade with PII redaction and RBAC
• 763% ROI and $5.62M NPV over a three-year period (according to deep research)
• Reduces MTTR significantly (e.g., 90% reduction from 5 hours to 30 minutes)
• Increases developer productivity (e.g., 30% increase)
• Allows dynamic instrumentation without stopping the application or reproducing issues locally
• Validates behavior under real traffic in a secure, read-only sandbox
• Reduces logging costs with dynamic telemetry and log optimization