AI agents that investigate incidents across services, traces, and queries — correlating signals your team would take hours to connect
From automated investigation to actionable recommendations — AI that traces through your full stack
From alert to root cause in minutes. AI investigates across all services simultaneously, correlates signals, and delivers a diagnosis — not just symptoms.
Trace slow performance through the entire service chain. Pinpoints whether the bottleneck is in code, queries, or infrastructure.
AI analyzes query patterns, identifies missing indexes, and traces slow queries back to the exact ORM call that generates them.
Automatically compares pre- and post-deploy metrics. Catch performance regressions before they impact all users.
When SLAs are breached, get a complete investigation report with root cause, timeline, and remediation steps.
Distinguishes between code issues and capacity limits. AI identifies when scaling, not re-deploying, is the right response.
Replace the patchwork of monitoring, logging, tracing, and incident management tools with a single AI-powered platform.
You open Datadog, Splunk, Jaeger, and a wiki tab, then try to line up timestamps by hand while the incident is still live.
One query kicks off a full trace across every service, log line, and metric — no tab-switching, no manual timestamp matching.
Traditional dashboards give you a symptom, not a cause. You're left guessing why memory spiked or what actually crashed the pod.
AI Investigation
Root Cause
Correlation
Queries
Tracing
Actions
Memory
Incident
Performance
Database
Deploy
SLA
Scaling
No more tab-switching
Traditional Stack
ApexData
db.go:247ApexData points to the exact line, the exact config value, and the exact moment things went wrong — no guesswork required.
Every incident turns into a scavenger hunt through logs, metrics, and traces while your team scrambles to piece together what happened.
AI correlates every signal simultaneously and hands you a diagnosis, not a pile of dashboards to stare at.
To see what your queries are actually doing, you need to bolt on another tool — or profile things by hand and hope you catch the slow one.
Every query is captured at the kernel level automatically. Slow queries, missing indexes, and connection issues surface without any setup.
Following a request across five microservices means five separate dashboards, five separate mental models, and a lot of lost time.
ApexData walks the entire call chain for you — service to service, hop to hop — so you see the whole picture in one place.
"Didn't this happen before?" Yes — but finding that old ticket, or the one person who remembers, takes half the incident.
ApexData automatically flags similar past incidents and what fixed them, so your team isn't solving the same problem twice.
Most tools tell you where to look, not what to do. You still have to figure out the fix yourself.
You get concrete next steps — add this index, change this config, look at this line of code — not vague suggestions.
Post-mortems get written days later from fuzzy memory, missing details, and Slack screenshots pieced together at the last minute.
A full report — root cause, timeline, and remediation steps — is generated automatically the moment the incident is resolved.
Not a bolt-on AI feature. The entire product is built around AI investigation — it understands your infrastructure and traces through your entire stack automatically.
eBPF-based collection. No code changes, no SDK installation, no instrumentation debt. Connect your cluster and we pull everything.
Deploy on your cluster, on your VPC. Your data never leaves your infrastructure. SOC 2 Type II compliant.
Battle-tested on production workloads from startups to enterprise — reliable observability at any scale.
Zero config
Why ApexData
