For on-call teams
Cut your mean time to diagnose
When an alert fires, ingren investigates your telemetry and replies in Slack with a likely cause, a first check, and the evidence behind both.
Built with a small group of design partners. Live alerts are flowing through ingren today.
ALARM: checkout-api-p99-latency
p99 > 2s for 5 min · us-east-1
Likely cause: payment gateway latency backing up the connection pool.
gateway_p95 to the payment partner moved first — 6× normal from 11:34. pool_wait on checkout-db followed at 11:36, then p99.
First check: partner-side gateway response times for the last 30 min, and the pool saturation graph.
9 figures checked against your telemetry
How it works
It investigates like your best engineer
Ingren doesn't summarize the alert. It investigates your telemetry and lays out the reasoning and evidence for the engineer who picks it up.
- 01
An alert fires
Alerts stream in from CloudWatch, Grafana, New Relic, Sentry, and GCP. Anomaly detection against learned baselines decides which ones deserve an investigation.
- 02
Ingren investigates
It forms hypotheses and runs checks against your metrics and logs to test them. Every query is logged with its purpose, so the whole investigation is replayable.
- 03
The diagnosis lands in Slack
A likely cause and a suggested first check, in the incident channel where your team already is. Evidence that contradicts the leading theory lowers its confidence visibly — it never gets quietly dropped.
- 04
It learns your system
Your corrections and resolved incidents become priors. When a similar signal shape appears, ingren recalls what your team said the cause was last time — so the second incident on your stack is cheaper than the first.
What lands in Slack
A diagnosis packet, not another alert
Ingren turns the noisy part of incident response into a compact handoff: what probably changed, which evidence supports it, and what the engineer should check first.
Likely cause
Named explicitly
Evidence
Ordered by time
First check
Actionable next
checkout-api
Incident packet - 11:47
Likely cause
Payment gateway latency is backing up the checkout connection pool.
Gateway p95
Moved first at 11:34
Pool wait
Followed at 11:36
Checkout p99
Pager fired at 11:42
First check
Open partner gateway latency and checkout pool saturation.
Time saved
The investigation path is ready before the owner arrives.
Signal quality
Reduce noise before diagnosis
The investigation is only useful if it starts from alerts worth chasing. Ingren learns the normal shape of your system, groups related signals, and lets your team correct the model from Slack.
Learned baselines
A baseline for every metric, recalculated daily with seasonality included — an anomaly is a deviation from your system's normal, not a static threshold someone set two years ago.
Anomaly detection
Warning- and critical-level anomalies arrive with expected vs. actual values and a link to the dashboard. Clear enough to act on from the notification alone.
Cluster-window grouping
When several alert types go anomalous in the same window, you get one "something systemic" message instead of five separate pages.
One-click feedback
Every notification has Real / False positive buttons. Two seconds of your time, and ingren tunes itself to your environment.
Integrations
Works with your stack
Ingren ingests alerts and telemetry from the tools you already run, so there is no agent to install and nothing to migrate.
Running something else? Tell us what you run — design partners get their stack prioritized.
Design partnership
Become a design partner
We're building ingren with a small number of teams. Your incidents shape the triage logic, and your corrections become the ground truth it learns from — the second incident on your stack is cheaper than the first.
You'll talk to the founder, not a sales team.