Pricing

1/100th The
Cost Of Manual Work

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RunWhen costs ~$5 per AI Investigation, 1/100th the cost of doing the same work by hand
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Pay-per-investigation to get started quickly
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Enterprise outcome-based contracts at scale
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* Noisy alerts? No problem. RunWhen does alert de-duplication before starting a session.

Our Pricing Plan

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How many alerts and chats is your team chasing down every day?

image showing the impact of driving down kubernetes costs
AI Investigations
Price
Description
5,000
sessions
$25k
5,000 AI investigations is the equivalent of an engineer who investigates 12-15 alerts per day for a year
10,000
sessions
$45k
10,000 AI investigations is the equivalent of a small team investigating 20-30 alerts per day for a year
25,000
sessions
$100k
25,000 AI investigations is the equivalent of a team investigating 65-75 alerts per day for a year
Unlimited
sessions
We will work with your team to create an outcome-based contract after the PoC, e.g.:
‍
- Number of incidents resolved autonomously
- Percent of cost savings capture from other contracts
- MTTR impact

Note this pricing is only available with Bring-Your-Own-LLM configurations.

A Typical Engagement Timeline

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A typical engagement starts with an hour long installation session using either a read-only kubeconfig or a read-only cloud credential. There are two checkpoints after that for go/no-go decisions, after which the system should be well integrated with your apps, data and workflows and ready for production use.

1
hour

Install Defaults

Default read-only tools, default Assistants

1-2
weeks

Vibe Test Defaults

Let your team vibe test with the defaults (infrastructure and basic app troubleshooting)

2-4
hours

Workshop

Prioritize app, data and workflow integrations

30
days

30 New Tools

Our FDEs work with your team to build 30 new tools in 30 days for the integrations you need

1-2
days

PoC Wrap-Up

Business case and proposal based on usage to date

Pre-Installation Analysis

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Prior to an installation, our team can help with tools to that analyze your existing alerts or chats, measuring which would turn in to automated sessions with Tasks currently in our library.

Before
After
900
Engineering hours
per thousand tickets
80%
of tickets with
>4 hours MTTR
156
Engineering hours per thousand tickets
56%
of tickets with
<1 minute MTTR

Automation can cut observability costs

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Some of our most popular automation libraries copy logs directly from pods and VMs into Jira/Github tickets. Connecting this to VSCode, alerts and CI/CD webhooks removes the need to ingest and store 90%+ of non-prod logs.

Talk to an Expert

Operate at lower cost with AI Engineering Assistants

Kubernetes stands as a cost-effective cloud platform choice. Integrating AI tools for non-experts, like app developers or junior SREs, brings a 60% reduction in KTLO engineering costs.

image showing the impact of driving down kubernetes costs

Test your assumptions quickly with Enterprise PoC

RunWhen offers a troubleshooting library for all environments, streamlining knowledge and consolidating tools.

Get started quickly with the PoC/PoV guide

This document provides reference materials for architecture, security reviews, sample discussion guides, and outlined directions for quantitative business case development. Additionally, PoCs include weekly check-ins with the RunWhen engineering team and support via email, Slack, and video conferencing during US Eastern business hours.

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