Resolve AI Alternatives in 2026

Resolve AI is a well-funded product with large enterprise customers. Teams look elsewhere for a few common reasons:

• No way to try it first. Getting Resolve means booking a demo. There is no self-serve sign-up or free plan.
• No public price. Usage is metered in credits set by contract, so the cost is hard to know before you buy.
• Setup before value. Engineers who trialled AI SREs often say they needed a lot of runbooks and company knowledge before the answers were useful.
• Trust. Engineers want to see exactly what an AI queried and what came back, before they act on its answer.

1. RubixKube

RubixKube runs read-only observers in your Kubernetes clusters, AWS, Google Cloud and Azure accounts and Linux machines, and takes alerts from Datadog, PagerDuty, Grafana, Sentry and other tools by webhook. It groups related alerts into one incident, and its agent, Rubix, writes a root cause analysis for each one, citing the tool output behind every step. Quotes are checked in code against what the tools returned, so you can see exactly what Rubix read.

Every RCA proposes a Fix and Follow-ups. Rubix opens the change as a pull request or through any tool you connect, and you choose how much it may do: Observe only reads, Assist asks before every change, Auto asks before anything destructive. It remembers past incidents and fixes, and works in the console, Slack, the CLI and your own AI tools over MCP.

• How you get it: sign up and start today. No demo, no approval.
• Pricing: Individual is free (1 environment, 10 investigations a month). Business is $999 a month. Enterprise is custom. See pricing.
• Best for: teams that run on more than one platform and want an AI SRE they can try on their own systems this afternoon.

2. Cleric

Cleric checks production changes and investigates alerts, then proposes fixes. It works with Kubernetes, AWS and Google Cloud and a wide set of observability, code and paging tools. It is read-only by default. With write access it opens a fix pull request for your approval. You use it in Slack, Microsoft Teams, its web app or over MCP.

• How you get it: a free trial of 1,000 credits, after Cleric approves it, or a demo.
• Pricing: public. Team is $700 a month, Pro $1,500 and Scale $3,000, each with a monthly credit allowance. An investigation uses 10 credits, $5. Enterprise is custom.
• Best for: teams that want change checks and investigations with credit-based pricing.

3. Traversal

Traversal is an AI SRE for large, complex production environments. It runs read-only on top of the observability tools you already have, without installing agents in your systems, and offers automated remediation and long-running agents that start when something looks wrong. You use it on the web, in Slack, in Microsoft Teams or over MCP.

• How you get it: book a demo, and Traversal scopes a deployment for your stack.
• Pricing: not public.
• Best for: very large enterprises with big observability estates.

4. Datadog Bits AI SRE

Bits AI SRE is Datadog's agent. It investigates monitors using the telemetry, runbooks and context already in Datadog.

• How you get it: as part of Datadog.
• Pricing: a paid add-on to Datadog.
• Best for: teams whose data all lives in Datadog. See RubixKube vs Datadog.

5. PagerDuty

PagerDuty's SRE agent, Paige, works inside the PagerDuty platform. It brings in the right people and agents for an incident and runs fixes through approved automation, waiting for your approval unless you let it act. It takes events from PagerDuty's many integrations rather than watching your infrastructure itself.

• How you get it: self-serve, with a free incident management plan for up to 5 users.
• Pricing: Paige is an add-on to Professional and included in the platform plans, from $2,800 a year.
• Best for: teams standardised on PagerDuty. See RubixKube vs PagerDuty.

6. incident.io and Rootly

incident.io and Rootly add AI investigation to their incident management and on-call products.

• How you get it: as part of those products.
• Best for: teams already running incidents in incident.io or Rootly.

7. Komodor

Komodor started as a Kubernetes troubleshooting tool and now sells an agentic operations platform, with AI SRE, cost and software operations modules and more than 50 built-in agents. It runs in your cloud, on-prem or in Komodor Cloud, with approval rules you set per action.

• How you get it: a trial on the Starter plan, or sales for Enterprise.
• Pricing: custom, a platform fee plus AI tokens.
• Best for: Kubernetes-heavy teams that also want cost and CI/CD modules. See RubixKube vs Komodor.

8. HolmesGPT

HolmesGPT is a free, open source investigation agent and a CNCF sandbox project. You run it yourself, as a CLI, Helm chart or server, with your own model, and connect it to Kubernetes, clouds and observability tools. It is read-only by design.

• How you get it: free and self-hosted. Slack and Teams come through Robusta's commercial product.
• Best for: teams that want open source and will run and tune it. See RubixKube vs HolmesGPT and K8sGPT.

9. AWS DevOps Agent

AWS DevOps Agent investigates incidents in AWS environments using AWS telemetry and services.

• How you get it: through AWS.
• Best for: teams that run only on AWS.

10. Azure SRE Agent

Azure SRE Agent monitors, diagnoses and helps resolve issues in applications hosted on Azure.

• How you get it: through Azure.
• Best for: teams that run only on Azure.

11. NeuBird

NeuBird is an AI SRE agent that analyses telemetry across enterprise IT tools to investigate incidents.

• How you get it: through sales.
• Best for: enterprise IT teams.

12. Causely

Causely builds a causal model of your services to work out which failure caused the others.

• How you get it: through sales.
• Best for: teams that want a causal analysis engine in their own stack.

13. K8sGPT

K8sGPT is a free, open source CLI and CNCF sandbox project that scans Kubernetes clusters with built-in analyzers and explains problems in plain English, using the AI model you choose.

• How you get it: free and self-hosted, as a CLI, an operator or an MCP server.
• Best for: a free first look at one Kubernetes cluster.

What Resolve AI does

Resolve AI describes itself as AI for production, working across code, infrastructure, telemetry and team knowledge. It connects to AWS, Azure and Google Cloud and a long list of observability tools, and runs a read-only agent called Resolve Satellite inside Kubernetes. Its actions are proposals that need a person's approval in its app or Slack, such as silencing an alert or a code fix as a pull request. You use it in its web app, Slack, Microsoft Teams or over MCP.

• How you get it: book a demo. There is no self-serve sign-up.
• Pricing: not public. Usage is metered in credits set by your contract.
• Best for: large enterprises ready for a sales-led rollout.

RubixKube answers yes to all five. Start free, or see the best AI SRE tools in 2026.