Comparison | AI SRE
OnePane vs Cleric: Investigation, or Investigation Plus Action?
Both OnePane and Cleric are AI SREs. Cleric focuses on investigation: finding answers fast and learning from engineers. OnePane covers investigation plus remediation, with tenant deployment as a first-class option. Here's the honest comparison.
At a glance
Side-by-side comparison
| Dimension | OnePane | Cleric |
|---|---|---|
| Deployment model | Tenant-deployed (AWS, Azure, GCP) or SaaS | SaaS |
| Data residency | Your cloud boundary | Cleric's cloud |
| RCA approach | Change-correlation (correlates recent changes to incidents) | Self-learning investigation across telemetry, learns from engineers over time |
| Scope | Investigation, ticket execution, runbook ChatOps (read + write) | Investigation-first AI SRE, surfaces findings to engineers (read-heavy) |
| Target customers | ITOps teams, SREs, MSPs, regulated enterprise | SRE and infrastructure teams at SaaS-native companies |
| MSP / channel pricing | Designed for multi-tenant channel economics | Direct enterprise SaaS |
| Agentless | Yes, reads from existing observability and ticketing | Yes, connects to existing observability and incident tools |
Comparison reflects publicly stated positioning at time of writing. Cleric's product details may change; verify on their site for current claims.
Strengths
Where OnePane wins
Tenant deployment as a first-class option
OnePane runs inside your own AWS, Azure, or GCP tenant. Cleric is delivered as SaaS, which means your telemetry and incident data flow to Cleric's environment. For regulated buyers and any company whose security review rejects production telemetry leaving the boundary, tenant deployment is structural, not a feature flag.
Investigation plus remediation, not just diagnosis
Cleric is read-heavy: it investigates, surfaces findings, and helps engineers debug. OnePane is read plus write: the same agent investigates and then executes approved runbooks and ticket workflows. If you want the agent to actually close the loop on routine incidents, not hand a report to a human, that scope difference matters.
Change correlation as the first hypothesis
Cleric's self-learning model gets stronger over time as it accumulates investigation history. OnePane starts with change correlation: deployments, config changes, and infrastructure edits get correlated to incident signals from day one. When the incident is change-driven, OnePane finds the cause in seconds without needing a learning runway.
ITOps scope, not only SRE
Cleric is positioned for engineering and SRE teams. OnePane covers the broader IT Operations scope: service desk ticket execution from ServiceNow, runbook ChatOps from Slack, and incident response. One agent across the surfaces an ITOps team actually uses, not just the SRE on-call rotation.
Honest take
Where Cleric wins
A comparison page is only useful if it is honest. Here is where Cleric has real strengths.
Focused investigation experience
Cleric is purpose-built around the investigation moment: alert lands, agent goes to work, engineer gets an actionable finding. That tight focus produces a refined experience for SRE and platform teams whose primary need is faster, higher-quality root-cause investigation. Cleric was named a 2025 Gartner Cool Vendor for AI in SRE and Observability.
Self-learning improves with use
Cleric explicitly learns from engineers and prior investigations, so the system gets sharper as your team uses it. If your environment generates a steady stream of similar incidents, that institutional learning compounds into faster answers over time.
Faster start for SaaS-comfortable buyers
If tenant deployment is not a requirement and you want an AI investigator running this week, SaaS onboarding is faster than provisioning into your own cloud account. Cleric can be in production without involving your cloud team.
Pick OnePane if
Who should choose OnePane
- You need the agent to take action, not just investigate (runbook execution, ticket workflows)
- You need tenant deployment in your own AWS, Azure, or GCP account
- Your scope is broader than SRE: service desk, network ops, incident response
- You are an MSP or channel partner and need multi-tenant economics
- Your security or procurement team will not approve SaaS for production telemetry
Pick Cleric if
Who should choose Cleric
- Your primary need is faster, higher-quality root-cause investigation for an SRE team
- Your engineers are comfortable taking action themselves once the answer is surfaced
- Your security posture allows SaaS observability and incident tools
- You want a system that learns from your team and compounds value over time
Try OnePane alongside Cleric
The best way to evaluate is to pilot both. OnePane deploys into your tenant in under 30 minutes. Book a 30-minute scoping call and we'll walk through your stack and show change correlation plus runbook execution working on your actual systems.
More comparisons
See how we compare to other AI SREs
Evaluating multiple AI SRE tools? Here are the other honest comparisons.
OnePane vs Cleric FAQ
Is OnePane a Cleric AI alternative?
Yes, particularly for buyers who need tenant deployment, want remediation actions in addition to investigation, or have an ITOps scope wider than SRE. Cleric is a strong investigation-first AI SRE; OnePane covers investigation plus runbook execution and ticket workflows inside your own cloud tenant.
Does Cleric only investigate, or does it also fix incidents?
Cleric's public positioning emphasizes investigation: finding, investigating, and surfacing answers to engineers, with some remediation capability. OnePane is built read + write from day one: it investigates and then executes approved runbooks and ticket workflows directly. If your team wants the agent to take action and not just produce a report, that difference matters.
Can Cleric run inside my cloud tenant?
Cleric is offered as a SaaS product based on their public materials. OnePane offers tenant deployment in your own AWS, Azure, or GCP account in addition to SaaS. If your security review will not approve a SaaS AI touching production telemetry, tenant deployment is the structural difference.
How does change correlation compare to Cleric's self-learning approach?
Cleric learns patterns from your engineers and prior investigations and applies that knowledge to future alerts. OnePane's first hypothesis is always: did a recent change cause this? Change correlation is fast and explainable when the incident traces to a deployment, config push, or infra edit. Self-learning investigation is stronger over time as the system accumulates institutional knowledge. Different strengths; pick based on which failure mode is more common in your environment.