Autonomy as leverage, not replacement. NeuBird takes the tool-hopping correlation off your plate and hands your SREs the assembled context, the causal chain, and a proposed fix. You decide, you act, you close.
p99 latency spike · checkout-service
Auto-resolvingDetected anomaly
0:00p99 latency +340% vs. 7-day baseline
Correlated signals
0:41Traced 14 services · 3 recent deploys
Isolated root cause
2:18Connection pool exhaustion · payments-db
Applied remediation
3:52Scaled pool 20 → 60 · rolled back deploy #4821
Verified & resolved
4:12Latency nominal · MTTR 4m 12s
Root cause · confidence
Connection pool exhaustion
Trusted by the world's most innovative companies
Preset skills for the whole production loop.
NeuBird AI ships with battle-tested operating skills out of the box. Turn them on, point them at your stack, and let one agent carry the triage, the toil, and the 3am pages.
Change Intelligence
Correlates every deploy, flag flip, and config change to the risk it introduces, so regressions never ship blind.
Incident Investigator
Watches telemetry across every service and opens an investigation the moment behavior drifts, before an alert ever fires.
Root Cause Analysis
Traces causal chains across logs, metrics, traces, and deploys with explicit, verifiable reasoning at every step.
Runbook Automation
Executes remediation the way your best engineer would: scale, roll back, restart, or hand off with a full audit trail.
Alert Triage
Groups, dedupes, and ranks noisy alerts so your on-call only sees what actually matters, with up to 90% less noise.
Cost Optimizer
Between incidents, it hunts idle capacity and misconfiguration, trimming cloud spend without touching reliability.
One agent. The whole production loop.
The page mostly stops before it starts
Context Engineering 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.
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.
The time comes back to you
Roughly 40% of ops time returned, and it goes to the roadmap, not to a smaller team. Between incidents the agent trims cost, captures every fix, and rolls each incident into the leadership view.
What it actually does for you.
Your team keeps the incident. The Production Ops Agent arrives with the context assembled, the causal chain laid out, and a fix proposed. You decide, you act, you close. Nothing executes without you.
The correlation goes to the machine.
The judgment stays with you. What you stop doing is the tool-hopping, not the engineering.
The page mostly stops.
Context Engineering fixes the underlying issue upstream, so the noise never reaches you.
One investigation, one answer.
Root cause in under five minutes, causal chain shown. No war room, no five tools, no copying trace IDs at 3am.
It sees it coming.
Degradation caught 30 to 60 minutes before a threshold trips, and blind spots surfaced before they page anyone.
Your tools stay yours.
Claude, Cursor, and the agents your team already built keep working over MCP. They just stop pointing at a raw alert queue.
It runs where your data already is.
Your VPC or on-prem, zero storage, SOC 2 Type II, human approval on every action, full audit trail.
Incidents don't live inside tools. They live in the spaces between them.
The same alert, two very different nights. NeuBird AI takes on the mechanical correlation work, so your engineers move from tool-hopping data detective to strategic verifier.
- Opens 12+ browser tabs: Datadog, Splunk, AWS Console, GitHub
- Copies and pastes trace IDs and timestamps under pressure
- Convenes an 8-person war room to find which silo holds the answer
- Queries 15+ observability backends in parallel, in place
- Reconstructs the complete causal chain from telemetry to the git PR
- Delivers an evidenced brief and recommended fix to Slack for approval
One agent, every surfaceThe same investigation shows up wherever your team already works, from a native desktop co-pilot to the Slack channel where the incident gets reported.
Why Context Engineering wins.
Trustworthy production autonomy is not a generic LLM wired to your alert queue. It takes an intelligence layer integrated natively with your telemetry and infrastructure, built on four practitioner-focused patterns.
Upstream context engineering
While standard agents react to whatever noisy queue they inherit, NeuBird AI works upstream. It instruments and enriches live telemetry so alerts only fire on real, SLO-impacting degradation. Fix the issue, don't patch the alert.
Zero-copy virtualization
No compulsory consolidation. Queries run in parallel directly against Datadog, Prometheus, Splunk, and New Relic through governed API access. Your logs, metrics, and traces stay exactly where they live.
Context curation
Data-side pre-filtering isolates the exact metrics, configs, and dependencies for the active incident. That precision delivers 94% root-cause accuracy at roughly 10% of the cost of generic architectures.
Persistent memory
A living layer maps your topology, tracks incident patterns, catalogs runbooks, and remembers root causes. When an engineer resolves a novel incident, the team keeps what it learns, inside your environment.
Autonomy you turn up, one gear at a time.
SREs keep ultimate sovereignty over production. NeuBird AI earns trust through a controllable, auditable blast radius: it can see everything and change nothing until you say so.
Suggest
Background triage. NeuBird AI continuously monitors events, maps topologies, and scores hypothetical failure modes. No state changes, and nobody is paged.
Recommend
Evidenced causal chains. When an alert fires, NeuBird AI investigates in parallel and presents a root cause analysis with cited evidence and step-by-step remediation. Still no state changes.
Act
Gated execution. NeuBird AI restarts services, rolls back, or redirects traffic through Ansible, Kubernetes, and Terraform. Every write is gated behind human approval in Slack, Teams, or the CLI.
No action occurs without explicit human authorization. The approval gate is the control, not a restriction on what the agent can see. These three gears sit on our full Earned Write Access spectrum, from read-only recommendations to policy-bounded autonomy.
Explore the Earned Write Access frameworkData residency and VPC
Deploys fully on-prem, in-VPC, or air-gapped, so production metadata never leaves your perimeter.
Zero storage
Real-time stream processing. We never copy or store your raw logs, databases, or metrics. We cannot leak what we do not store.
Human approval on writes
Suggest, Recommend, Act. Every write is gated behind a configurable approval block in the tools you already use.
Complete audit trail
Every query, trace, and authorized remediation is recorded in a SOC 2 Type II compliant, immutable log.
Leading teams stop incidents before they happen with NeuBird AI
Our team was able to get up and running with NeuBird AI 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.
Works with your existing stack.
No rip-and-replace. The Production Operations Agent connects to the tools you already use.
See how NeuBird AI customers have saved $2M+ in engineering costs and returned 40% of ops FTE time back to their engineers.