NeuBird
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The AI SRE and Beyond

NeuBird is the AI SRE that investigates every alert across your stack, then keeps going: preventing the next incident and operating production in between.

  • Triage incidents in minutesRoot cause in under 5 minutes at 94% accuracy.
  • Eliminate ticket fatigueNoisy and duplicate tickets handled before anyone is paged.
  • Lower MTTR, raise reliabilityA verified fix is ready when on-call opens the page.
  • Make production autonomousRoutine operations run themselves, with your approval.
One center · three consumersZero telemetry stored
Acme · ProdChannelsincident-checkoutpayments3deploysplatform-oncallAppsNeuBird
Today
V
Vinod09:11checkout p99 is climbing again.
NeuBirdApp09:14
Root causeConnection pool exhaustion · payments-dbEvidence14 services · 3 deploys · citedBlast radiuscheckout, cart, orders · 3 of 14 servicesProposed fixRoll back #4821 · awaiting approval
Approve rollbackReview evidenceRequires · Andrew LeePolicy · Act
RVP3 repliesLast reply 2m ago
Andrew Lee is typing…
Message #incident-checkout
inv-2291 · seen before · 2 prior fixes
Central memoryServing · slack

inv-2291 · versioned · cited · conclusions, never telemetry

RCA accuracy94%
Time to root cause<5 min
Writing · conclusions and institutional knowledge
GitHubinv-2301cart p99 regression · N+1 in coupon-service · fix merged
Google Cloudkb-0133egress spikes track the weekly export job, not traffic
GitLabinv-2282ci image pull timeouts · registry mirror added · resolved
OpenTelemetrykb-0136trace sampling hides the slow path below the p99 alert
AWSinv-2285eu-west-1 nat gateway saturation · scaled out · resolved
MongoDBkb-0139orders replica lag spikes during the nightly index build
Redisinv-2288checkout cache stampede · ttl jitter added · resolved
Datadogkb-0142checkout p99 trails every payments-db failover by ~40s
audit
09:14:02 · alee approved rollback #4821 · consumer: slack · policy: Act · 09:16:40 · agent read payments-db dashboards · policy: Recommend · 09:21:07 · cursor session queried inv-2291 · consumer: mcp · read only · 09:24:55 · scheduled brief generated · consumer: leadership · no writes · 09:31:12 · write to search-api held for approval · owner: platform
models
one metered connection · claude, gpt, bedrock · spend by team, agent, and service · per-agent budgets · caps enforced before the call · no key sprawl · one place to rotate and revoke · model choice per task · not per team, per agent

Trusted by teams that run production at scale

  • Agero
  • Commonwealth Bank
  • DeepHealth
  • EverPure
  • KAi
  • RH
  • SAP
  • Greenlight
The on-call reality

The alert you learned to ignore is the one that pages you at 2 AM.

Every team that runs production knows this week. It is not a talent problem or a tooling problem. It is what Day 2 operations costs when every step is done by hand.

Alert fatigue

83% of organizations say their teams ignore alerts.

Alert fatigue is what happens when most alerts are not actionable: the signal-to-noise ratio collapses and the critical page gets the same glance as the hundredth false positive. Thousands of alerts a week, correlated by nobody, until one of them is real.

Manual toil

Every investigation starts from zero.

Toil is the manual, repetitive work that scales with your services instead of with your headcount: open six tabs, pull the deploy history, rebuild the timeline, correlate by hand. The same hunt, every incident, by whoever happens to be on call.

The war room

One P1, eight engineers, three hours.

A war room is what an incident becomes when nobody can see the causal chain: the whole team on a bridge, narrating dashboards to each other, while the root cause sits in a commit someone approved yesterday. MTTR is measured in meetings.

An AI SRE investigates every alert, so the 2 AM page arrives with the root cause already attached. Your on-call reviews and approves instead of hunting.

See the AI SRE
Our team was able to get up and running with NeuBird rapidly. It is like having an always-on AI SRE that delivers real-time incident diagnosis and actionable fixes 24/7, saving our engineers hours of troubleshooting and improving service quality for our customers.
Madhu Jahagirdar
Madhu Jahagirdar
VP of Cloud, Technology & Product, DeepHealth
Beyond the AI SRE

One agent. The whole production loop. None of the hunting.

The Production Ops Agent runs on the Agentic Reliability Center: one governed platform that queries your telemetry in place, remembers every investigation, and stages every action for your engineers to approve. Here is what each part of your week becomes.

01 / Prevent · ends alert fatigue
30-60minutes of early detection

The pages mostly stop before they start

The Agentic Reliability Center filters alert storms and fixes the underlying signal upstream, so the noise never reaches you. It also surfaces the blind spots: services with no owner, no alert, no runbook. The alerts that remain are the ones worth waking up for.

02 / Resolve · ends the manual hunt
94%RCA accuracy, root cause in under 5 minutes

One investigation, one answer

The agent does the digging a war room would take hours to finish, then hands your team the root cause, the offending commit, and a proposed fix in under five minutes. Your engineers review and approve, instead of hunting. Nobody rebuilds the timeline by hand.

03 / Operate · ends the war room
60%+lower incident management costs

The time comes back to you

Between incidents the agent trims cost, captures every fix into memory, and rolls each incident into the leadership view. The next time the symptoms appear, the answer is already there, so the bridge never opens.

See the platform
In production

What NeuBird does, live on your stack.

Watch what the Production Ops Agent does when production breaks: it detects early, resolves fast, and keeps operating between incidents.

80% fewer P1 war rooms

Detect earlyBefore the war room

NeuBird catches silent service drift and missing SLOs before the alert storm, so the page never turns into an all-hands incident.

RCA in under 5 min at 94% accuracy

Resolve fastRoot cause, staged fix

NeuBird investigates across 15+ sources in parallel, isolates the causal chain, and stages the exact fix for your on-call to approve.

~10% of alternative cost

Operate continuouslyBetween incidents

NeuBird prunes noisy telemetry, tracks recurring cross-service patterns, and attributes model spend back to the team that drove it.

Why an agent, not an API key

Reliable ops automation needs more than a model call.

Teams across engineering are adopting frontier models and IDE assistants like Claude and Cursor to move faster. But when production is on fire, the bottleneck is never querying a model. It is the operational harness required to reason across infrastructure safely.

Curated context over token waste

Raw dumps burn budgets. NeuBird curates the operational state before it calls a model, so context is passed cleanly without multi-agent token sprawl.

Self-updating memory

When triage happens in one-off terminal sessions or disjointed chats, institutional memory vanishes the moment the incident closes. Without a centralized memory layer, teams burn cycles, and model budgets, re-diagnosing the same failures month after month. When your on-call approves a resolution, NeuBird commits the causal chain to memory. The next time related symptoms emerge, that institutional knowledge is surfaced automatically.

Earned autonomy and safety

Moving from passive suggestions to automated remediation requires audited guardrails. NeuBird establishes clear policy gates, Suggest, Recommend, Act, so your team retains incident ownership while internal tools safely interact with production.

The model was never the problem. Production needs a governed harness around it, and that is exactly what NeuBird runs as a service.

What a Production Ops Agent is
One agent, every surface

The same investigation, wherever your team already works.

From a native desktop co-pilot to the Slack channel where the incident gets reported, NeuBird brings the full investigation to the surface your team is already in.

SURFACE / 01Live operational context
Desktop co-pilot

A native workspace that runs local tools and investigates alongside you.

SURFACE / 02Live operational context
In your Slack channels

Finds root cause in minutes, creates a PR, and reports back for approval.

Explore every interface
Trust by architecture

Nothing executes without an approval the audit trail can show.

Suggest

Policy 1

Observes and proposes. Blind spots, drift, and risk surface in the memory. No state changes.

Recommend

Policy 2

Investigates in parallel and presents a root cause with cited evidence and a staged fix. Still no state changes.

Act

Policy 3

Gated execution through your own tooling. Every action waits for a human approval, and the audit trail shows who gave it.

  • Runs in your environment
  • No bulk telemetry retention
  • Human approval on every action
  • One SOC 2 Type II audit trail
Customer proof

Teams that run production on NeuBird.

The time it takes to root cause and solve an issue is about the most important concern for anyone leading IT operations. GenAI technologies like NeuBird AI are an absolute necessity as we prepare ourselves for the next decade.
JF
Justin Fitzhugh
Vice President of Engineering
Enterprise IT
80%
fewer P1 war rooms, down from hours of manual coordination
The question the CIO cannot answer today

And who approved what they did last week? NeuBird is the one governed center that can answer, for every agent, including its own.