Your incidents cross teams,
tools, and systems.
Enterprise AI SRE sees it all.

Prevent avoidable incidents. Resolve the rest faster.
Free your SREs from manual firefighting.

Trusted across

Financial Services

Insurance

MSPS

Retail

Manufacturing

Airlines

Nobody owns the incident. Everybody escalates it.

Incidents span infrastructure, applications, services, cloud, and third parties. So teams pass them along, one escalation at a time, until someone finally owns the problem.

Change risk is invisible until it isn’t

Teams ship changes with no reliable way to predict which one causes the next incident — risk stays invisible until something breaks.

Every repeat incident is treated like a new one

Patterns, recurring causes, and proven fixes never get captured, so nobody learns from the last time this happened.

This is the gap AI SRE exists to close.

Your best people are doing dispatcher work.

No clean owner

Incidents cut across infrastructure, apps, services, cloud, and third parties — so teams escalate in sequence until someone claims it.

Your experts do dispatcher work

Spinning up channels, paging people, tracking status, asking who changed what — all of it eats time that should go to preventing the next incident.

Root cause is scattered

The knowledge to resolve an incident lives across tools, tickets, runbooks, chat, and people’s heads — diagnosis means manual assembly under pressure.

This is how you burn out your best engineers.

Your best experts become the bottleneck

SREs and ops teams spend scarce time coordinating, reconstructing context, and investigating causes — burnout rises, on-call load grows, and leaders push to hire just to keep up.

Reactive work crowds out reliability work

Recurring incidents and preventable change failures keep pulling teams back into firefighting instead of modernization and product delivery.

Incidents last longer than they should

Manual escalation and fragmented investigation delay resolution — every extra minute adds customer impact, SLA exposure, revenue risk, and brand damage.

What changes with AI SRE for the enterprise

Before

Nobody owns the incident until someone finally claims it.
Your SREs spend the incident coordinating, not fixing.
Root cause is scattered across five tools and three people’s heads.
Risky changes ship blind. You find out when it breaks.
Every repeat incident gets investigated like it’s brand new.

After

The right owner is identified and engaged immediately.
Coordination runs itself — responders just respond.
Agents investigate in parallel and hand back the likely cause.
Risky changes get flagged, with why, before they ship.
Recurring problems get fixed at the root, not re-diagnosed every time.

How it works

This is what AI SRE looks like when it’s built for enterprise IT, not a demo environment.

Automated incident response

The team assembles itself.

Assembles the team automatically
The moment an incident opens, the right channel stands up and the right responders get paged. No one stops to figure out who’s needed.

Keeps everyone posted without a human relay
Responders get a live, current summary; execs, support, and customers get simple, audience-appropriate updates.

Writes it up after, automatically
Call transcript, root cause summary, and post-mortem generated directly from the incident record.

bigpanda-AI-SRE-for-the-enterprise-image-1

Automated incident investigation

Ask it. Don’t dig for it.

You can just ask it
Describe the problem in plain language, get an answer back. No dashboards to interpret, no query language to learn.

It investigates everywhere at once
Agents check monitoring, code, history, and topology simultaneously, testing multiple leads in parallel instead of one after another.

It knows your systems
Every answer is grounded in your actual architecture and past incidents, not a generic model guessing at “normal.”

Predict change-related incidents

Know what’s risky before it ships.

Flags risky changes early
Conflicts, collisions, and risky deployment windows caught before a change ships, not discovered after it causes an outage.

Makes CAB reviews easy
Risk shows up on the change record automatically, before the meeting starts, so reviewers focus only on what actually needs scrutiny.

Learns what’s risky over time
Risk is predicted from what’s actually happened in your environment, not a static checklist that treats every change the same.

Prevent repeat incidents

Stop solving the same incident twice.

Surfaces recurring patterns
Analyzes incident history to identify recurring themes, related incidents, and likely root causes that would be nearly impossible to track manually.

Gives you the fix, not just the finding
Recommends solutions with implementation steps, estimated effort, and expected operational impact.

Helps you prioritize
Combines frequency, severity, related-ticket volume, and business impact so teams fix what matters most first.

This is how BigPanda does it.
Most AI SRE tools were built for one service — this one was built for your reality.

1

Built for enterprise IT, not one team’s service

Most AI SRE tools assume one team owns the service and one engineer investigates one app at a time. BigPanda is built for the reality where incidents cut across teams, tools, and hundreds of applications — so the right team gets engaged faster, and reliability improves across the whole operation, not just one pocket of it.

2

Operational knowledge, not just code and telemetry

Most tools reason from metrics, logs, traces, and code. BigPanda adds what they miss: who owns what, what changed, what happened before, and what’s worked in the past — so teams start with context instead of re-learning what the organization already knows.

3

Prevention first, not just faster remediation

Most tools compete on how fast they fix something after it breaks. BigPanda predicts risky changes, prevents repeat incidents, and automates response when issues do happen, so fewer incidents reach customers and your experts get their time back.

Analyst recognition · Gartner® Market Guide

Gartner’s take: reactive tools aren’t enough.Without Doubling Your Budget

BigPanda is recognized in Gartner®’s Market Guide for AI Site Reliability Engineering Tooling, which explains how organizations must evaluate and invest in AI SRE tooling to lower the cost of SRE adoption and ensure reliability at scale.

Read the Gartner report

What your CFO actually cares about.

Lower the cost of manual incident work

Automate response and investigation, cut unnecessary escalations, stop paying to re-solve the same incident.

Engineering capacity goes up, not headcount

Automated coordination and investigation free teams to improve reliability and ship faster instead of hiring to keep pace.

Customer experience and revenue stay protected

Fewer preventable incidents reach customers, which means less SLA exposure, less brand damage, less revenue risk.

This is the return enterprise IT gets from doing AI SRE right.

See what your SREs stop doing on day one.

Bring a real incident. We’ll show you exactly what BigPanda catches, predicts, and automates — before you ever page anyone.

Get a demo

Webinar

The SRE Toil Problem: How Agentic IT Operations Changes the Equation

Watch now

Your incidents cross teams, tools, and systems. Enterprise AI SRE sees it all.