When an AI coding agent works autonomously for a while, it's easy to lose track of exactly what it changed, which commands it ran, or whether it reached out to some external service it shouldn't have. Spotlight reads the session afterward and turns that black box into a readable report: which files were touched, which commands ran, what external tools were contacted, and anything that looks worth a second look before it ships. Spotlight by Backplanes reads Claude Code and Codex sessions and generates post-session reports covering files touched, commands run, external domains/MCP servers contacted, scope drift, and security-risk findings with severity triage and PII/credential redaction, organized into Security, Engineering, and Spend views for teams. It's built by a team with backgrounds from Google, Twilio, Valimail, ngrok, and Algolia, backed by investors including Slow Ventures, Bloomberg Beta, and Fenwick. It's free for individual developers and their teams (no seat counting, no trial clock), with a separate paid tier for organizational rollouts whose exact pricing isn't published.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Équipes de développement voulant une observabilité automatisée sans setup lourd ni dépendance à un vendeur propriétaire | — | |
| 2 | SRE, DevOps and IT ops teams who want AI-assisted incident triage instead of manual paging | — | |
| 3 | Developers and small teams running AI agents in production who want on-prem observability without vendor lock-in | — | |
| 4 | Engineering teams running AI agents in production who need evals, tracing and automated regression detection | — | |
| 5 | Engineering and SRE teams from startups to large enterprises | — | |
| 6 | Mid-market and enterprise engineering teams (100+ engineers) | — | |
| 7 | Teams operating long-running, autonomous AI agentic systems in production | — | |
| 8 | Teams building and scaling conversational AI agents (chat or voice) | — | |
| 9 | Équipes construisant des agents IA multi-étapes (pas de simples appels LLM ponctuels) | — | |
| 10 | Fast-moving engineering teams, especially those already using AI coding agents | — | |
| 11 | Platform engineers | DevOps teams | SRE teams | — | |
| 12 | Software engineers | SRE and platform teams | — |
A self-installing mechanic for your app's bugs — instead of you wiring up monitoring tools and then manually digging through logs when something breaks, Superlog instruments your code itself, groups the mess into one clear incident, and shows up with a re
An AI pager that tries to investigate and fix the problem itself before waking up an on-call engineer at 3am.
A free, self-hosted dashboard that shows you exactly what your AI agents did, why they cost what they cost, and where they broke.
An open-source platform that watches your AI agents in production and can automatically catch and fix regressions before users notice them.
AI-native incident management platform that coordinates the whole outage response in Slack, has an AI assistant that helps find the root cause, and writes the post-incident report for you.
Incident management platform built entirely around Slack, with an AI layer that helps draft fixes, and status pages that keep customers informed automatically during an outage.
Monitoring layer for long-running AI agents that notices when an agent quietly drifts off its instructions or starts failing silently, and suggests a fix before it causes real damage.
Analytics tool that reads real conversations your AI chatbot or voice agent had with users and automatically writes a code fix when it spots a recurring failure pattern.
A dashboard that shows you exactly what your AI agent did, step by step, when it fails — every tool call, every sub-agent, every LLM response — instead of leaving you to guess from a wall of logs.
AI-native observability platform that lets engineers debug production issues by asking questions in plain language instead of digging through logs.
Open-source observability platform that unifies traces, metrics and logs in one OpenTelemetry-native tool, self-hosted or cloud.
Observability platform for debugging production systems with distributed tracing, BubbleUp anomaly analysis, and AI-assisted querying.
