What is the Agentic Reliability Center (ARC)?

The governed center of agentic operations.

One context for people and machines alike.

Production environments have outgrown human scale, and smart models require smarter context. The Agentic Reliability Center (ARC) is the enterprise substrate running underneath your operations. It unifies live access to your existing telemetry and models in place, compounds institutional memory across every incident, and enforces deterministic safety gates before any agent touches production.

Book a Demo →Platform Overview

Telemetry

Metrics, logs, traces, alerts, tickets, changes, runbooks, code, CMDB

LLMs, your choice

Claude, GPT, Gemini, Bedrock, Azure OpenAI, or models on your own infra

NeuBird

The governed center of agentic operations

Secure one perimeter

Audited every action

Cost-efficient tokens spent once

Policy-gated Suggest to Act

Central memory · remembers everything

Every investigation, by human or agent, recorded, versioned, and cited
Institutional knowledge compounds inside your perimeter
Nothing gets re-derived; every consumer starts from what is known

One audit trail across all agentic activity, human-run or autonomous

Smart Models Need Smarter Context

AI is becoming the reasoning fabric of infrastructure. In isolation, it fails.

AI is no longer just a feature plugged into legacy dashboards; it is becoming the coordination and reasoning fabric of modern infrastructure. Yet standalone LLMs and hand-rolled scripts fail inside production because they operate in isolation.

Token waste

Budget burned on noise

Dumping uncurated, gigabyte-scale log streams into model context windows burns budget on noise.

Amnesia

The same failure, solved again

Disjointed tools fail to retain operational history, paying to solve the exact same recurring failures again and again.

Ungoverned access

Scattered keys, hidden risk

Brittle scripts with scattered API keys create operational blind spots and introduce unpredictable risk.

ARC provides the missing operational layer. Deployed inside your private cloud or VPC, ARC sits between your existing telemetry and your chosen models, transforming raw intelligence into dependable, accountable production operations.

One Center, Three Foundations

Access. Remember. Serve.

ARC decouples the operational foundation from the agents and engineers running on top of it, providing one shared source of truth across your entire estate.

Access

Queries in place with zero telemetry copying.

ARC connects directly to your existing infrastructure, observability tools, and cloud providers. Instead of forcing you to duplicate petabytes of data into a proprietary second data lake, ARC reasons over metrics, logs, traces, and code where they live. Context is curated and computed once before reaching any model, slashing token waste and eliminating redundant inference costs.

Zero-copy architecture across 50+ integrations
Centralized model metering and prompt curation
Native security using the API keys you already hold

Remember

Institutional operations memory that compounds inside your perimeter.

Every investigation conducted by engineers or AI agents is captured, structured, and retained. ARC preserves conclusions, causal graphs, and approved remediation playbooks, never raw telemetry dumps. The next time a failure pattern begins to emerge, the system starts from verified organizational history rather than a blank slate.

Append-only, versioned operational memory
Causal chains and verified remediations cited on every finding
Audited single-click rollback for any system memory

Serve

Governed safety guardrails and cross-platform workflows.

ARC serves real-time findings to practitioners in daily collaboration tools, while giving platform teams an open runway to power custom internal AI agents. Execution safety is enforced through a granular policy continuum, Suggest → Recommend → Act, ensuring human engineers remain firmly in control of production.

Granular autonomy continuum (Suggest, Recommend, Act)
Human-readable receipts staged in Slack, Teams, Jira, and ServiceNow
Universal Model Context Protocol (MCP) connectivity for internal agents

The Intelligence Engine Underneath

Live system state, continually evaluated.

Inside the center, ARC continually evaluates live system state to coordinate prevention, investigation, and operational workflows.

Continuous Correlation

Synthesizes telemetry across distributed systems without data movement.

Causal Reasoning

Traces dependency graphs to isolate the root cause, not just surface symptoms.

Living Architecture Model

Maintains an active topology map of services, dependencies, and deployment drift.

Cost & Risk Attribution

Identifies idle resources, forecasts failure risk, and tracks operational impact.

Approval Gates & Audit Trail

Requires named human sign-off on changes and logs an immutable audit trail.

Telemetry queried in place · models metered once · every investigation remembered · every action gated and audited

One Platform, Two Consumers

Automate the archaeology. Empower the engineer.

The Agentic Reliability Center is designed as a shared platform serving human teams and autonomous workloads alike.

Level 2

Flagship workload

The Production Ops Agent

Prevent

Detects 30 to 60 min early

Resolve

Under 5 min RCA, 94% accuracy

Operate

Tunes noisy alerts

The runway · via MCP

Your custom agents

Claude, Cursor, and homegrown agents plug in here.

Level 1

The center

NeuBird, the Agentic Reliability Center

Access

Queries in place. Zero telemetry copy.

Remember

Institutional memory, versioned and cited.

Serve

Suggest → Recommend → Act

Delivers truth to

SlackTeamsJiraServiceNow

Live Telemetry

Your existing estate · 50+ integrations

AWS

Azure

GCP

Datadog

Splunk

+ 45 more

Queried in place. API keys you already hold. Zero data migration.

1 · For Human Practitioners

Powering the Production Ops Agent

ARC acts as the engine behind NeuBird’s flagship Production Ops Agent. It handles the multi-dashboard telemetry archaeology during incidents, detects silent degradations before thresholds trip, and stages verified fixes directly inside daily engineering channels.

2 · For Internal Builders

The Runway for Custom Agents

Keep your internal AI initiatives. Platform teams building custom scripts or tools in Claude, Cursor, and homegrown frameworks can plug directly into ARC over the Model Context Protocol (MCP). Custom agents inherit live production telemetry, causal reasoning, historical incident memory, and safety guardrails on day one, skipping months of connector maintenance.

Connect, Don't Migrate

Built on what you run. Zero rip-and-replace.

ARC connects directly to your existing environment without requiring architecture overhauls or secondary storage contracts.

What it reads · 50+ integrations

AWS
Azure
GCP
Datadog
Splunk
Prometheus
PagerDuty
GitHub
+ 40 more

The center · Access · Remember · Serve

NeuBird, the Agentic Reliability Center

Access

Remember

Serve

Access once. Remember forever. Serve everyone.

Where people & agents work

NeuBird UI
Slack
Microsoft Teams
Jira
ServiceNow
IDE and terminal
Your agents · MCP

50+ Integrations Out of the Box

Connects to AWS, Azure, GCP, Datadog, Splunk, Prometheus, ServiceNow, PagerDuty, GitHub, and CMDBs in place.

Your Model of Choice

Governed access to Claude, GPT, Gemini, or hyperscaler model deployments via Bedrock, Azure OpenAI, or Vertex AI.

Deploy Your Way

SaaS, fully inside your private VPC, or air-gapped. Telemetry stays inside your security boundary with zero retention of customer operational data.

Frequently Asked Questions

Agentic Reliability Center questions, answered.

What is the Agentic Reliability Center (ARC)?

The Agentic Reliability Center (ARC) is the governed operations substrate that provides a single point of access to two critical enterprise assets: your live telemetry and your chosen LLMs. It reasons over infrastructure data in place, versions operational memory across incidents, and enforces strict policy guardrails for any agentic action touching production.

How is ARC different from the Production Ops Agent?

They represent the platform and the workload. The Production Ops Agent is the flagship workload: the front-door agent that helps on-call engineers prevent incidents, resolve the ones that get through, and operate production between them. ARC is the platform it runs on, supplying the connections, the memory, and the policy that decides what any agent may change. Your own agents can run from the same platform.

Does ARC copy or store our telemetry?

No. ARC queries metrics, logs, traces, and code where they already live, using the API keys you already hold. Memory holds conclusions, causal graphs, and approved remediations, never raw telemetry, and the center deploys as SaaS, inside your VPC, or air-gapped.

Can our own internal agents use ARC?

Yes. Agents built in Claude, Cursor, or homegrown frameworks connect over the Model Context Protocol (MCP) and inherit live production telemetry, causal reasoning, historical incident memory, and the same safety guardrails on day one, without maintaining their own connectors.

How does ARC keep agents from making unsafe changes?

Every consumer, human or agent, is gated along the same policy continuum: Suggest, Recommend, Act. Changes require named human sign-off, and every action is recorded in an immutable audit trail, so write access is earned by track record rather than granted by default.

Which models does ARC support?

ARC provides governed, centrally metered access to Claude, GPT, Gemini, or hyperscaler deployments via Bedrock, Azure OpenAI, or Vertex AI. Context is curated once before it reaches any model, so tokens are not wasted on noise.

See the Agentic Reliability Center

Access once. Remember forever. Serve everyone.

Bring your telemetry, your models, and the agents you already have. We will show you the Production Ops Agent at work and what changes when every agent runs from one governed center.

Book a Demo Platform Overview