Your AI on-call engineer, always awake
VeloOps connects to your logs, metrics and alerts, then uses AI to catch incidents before they page you — and explain the likely root cause in plain English before you have even opened a dashboard.
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Illustration of a VeloOps incident timeline: a deploy triggers an error spike, VeloOps identifies the root cause in eleven seconds and posts it to Slack, and the team resolves the incident by rolling back — nine minutes and fifty-nine seconds end to end.
MTTR this incident
9m 59s
Alerts grouped
1 of 7
Built for engineering & DevOps teams at growing companies
Everything you need to catch incidents before your customers do
One platform, watching every service you connect, correlating the signals a human would chase down by hand.
Real-time log & metrics monitoring
VeloOps streams your logs and metrics continuously and flags anomalies the moment they deviate from a service’s normal baseline — not five minutes later in a batch job.
Learn moreAI root-cause analysis
When something breaks, VeloOps correlates the error spike with recent deploys, config changes and upstream infra events, and explains the likely cause in plain English.
Learn moreSmart alerting that cuts the noise
Related signals get grouped into one incident instead of paging your team twenty times for the same underlying failure.
Learn moreAuto-generated incident timelines
Every incident gets a timestamped timeline of what happened and when — and a first-draft postmortem you edit instead of write from scratch.
Learn moreWorks inside your existing workflow
Slack, Microsoft Teams and PagerDuty integrations mean your team responds where it already works, with no new tool to check.
Learn moreOne-click connect to your stack
Point VeloOps at CloudWatch, Datadog, or your existing log pipeline and it starts building baselines immediately — no agents to deploy on day one.
Learn moreConnect your stack → AI monitors 24/7 → Get root cause in seconds
No agents to deploy on day one, and no dashboard to babysit. Most teams see their first anomaly detected within the hour.
STEP 01
Connect your stack
One-click connect CloudWatch, Datadog, or your existing log pipeline. Nothing to migrate, and baselines start building within minutes.
STEP 02
AI monitors 24/7
VeloOps watches logs, metrics and deploys continuously, building a baseline for every service and flagging anomalies the moment they appear.
STEP 03
Get root cause in seconds
When something breaks, VeloOps correlates the signals and hands you a plain-English root-cause summary — before you have opened a dashboard.
Less firefighting. Faster answers. Less burnout.
Alert fatigue is a design problem, not a discipline problem. VeloOps absorbs the correlation work that used to eat the first twenty minutes of every incident.
Cut mean-time-to-resolution dramatically
Root-cause correlation that used to take twenty minutes of manual dashboard-hopping happens automatically, in seconds.
Give your engineers their nights back
Smart grouping means one incident, one page — not nine near-identical alerts for the same underlying failure at 3am.
Scale coverage without scaling on-call headcount
Monitor more services with the same team, because the correlation work lands on VeloOps first, not on whoever is on call.
70%
reduction in MTTR
measured across pilot deployments
<30s
to anomaly detection
from first signal to alert
90%
fewer noisy alerts
after smart grouping and dedup
24/7
always-on monitoring
every service, every timezone
Figures reflect target performance measured across early pilot deployments. Actual results depend on your service mix and alerting maturity.
What engineering teams tell us
Illustrative feedback from early pilot deployments, shared without company names at their request.
“We used to lose twenty minutes just figuring out which deploy broke things. VeloOps had the correlation done before the second page went out.”
“The alert grouping alone paid for itself. One bad deploy used to mean nine pages to nine different people — now it is one incident, one page, one owner.”
“The postmortem draft is the part nobody asked for and everybody now expects. It turns a two-hour writeup into a fifteen-minute review.”
Works with the tools you already run
VeloOps sits alongside your existing stack rather than replacing it, so your team keeps its current workflow.
Need something else? Ask us about the API and webhooks.
Watching your infrastructure is only useful if it’s safe
VeloOps handles your logs, metrics and deploy history, so the controls around that data matter as much as the anomalies it catches. Here is how it is protected — and what we will put in writing for a security review.
Enterprise agreements include a data processing addendum, configurable data residency, and support through your security review.
Encrypted in transit and at rest
Telemetry is protected with TLS in transit, and stored logs and metrics are encrypted at rest with managed keys. Each workspace is logically isolated from every other.
Your telemetry is not training data
Your logs, metrics and incident data are used only to monitor and analyse your own workspace. We do not use customer telemetry to train models shared across accounts, and neither do our model providers.
Access you can audit
Role-based access control and an audit log on Business and Enterprise plans, so you can see who changed what and when — the questions a platform team asks first.
Built to stay up
Redundant infrastructure across multiple availability zones, continuous monitoring, automated encrypted backups, and a documented recovery process.
Stop finding out about incidents from your customers
Connect your stack, let VeloOps build a baseline, and get your first AI root-cause summary this week. The Free plan needs no credit card.
No credit card required · Cancel anytime · Live in minutes