The best Cleric alternatives are Sherlocks AI, Resolve AI, Metoro, Datadog Bits Investigation, and NeuBird. Sherlocks AI is the best overall Cleric replacement for cross-stack AI SRE and production incident investigation; Resolve AI leads on controlled remediation, Metoro on Kubernetes, Bits in Datadog environments, and NeuBird on zero-copy governance.
These Cleric AI competitors serve teams comparing tools, products, and software like Cleric, but differ substantially in production context, RCA depth, change detection, remediation, learning, integration coverage, and autonomy.
Best Cleric alternatives and competitors at a glance
| Alternative | Best for | Production investigation | Telemetry model | Remediation |
|---|---|---|---|---|
| Sherlocks AI | Best overall for complete, cross-stack AI SRE | 16+ specialist agents, competing hypotheses, evidence-backed RCA, change correlation, and incident memory | Queries the existing stack through a read-only data agent and Awareness Graph | Plans, commands, and draft PRs; engineers execute changes |
| Resolve AI | Closed-loop investigation and remediation | Parallel Agent Teams with a dedicated verifier | Connects to observability, infrastructure, code, and incident tools | Approved reverts, workflows, alert silencing, and operational actions |
| Metoro | Kubernetes-native detection and verification | Autonomous detection, RCA, and deployment verification | Native eBPF Kubernetes observability with OTel and Prometheus support | Reviewable fix and rollback PRs |
| Datadog Bits Investigation | Existing Datadog customers | Automatic alert investigation and hypothesis testing | Native Datadog telemetry, topology, infrastructure, and change data | Datadog workflows and Bits Code handoff |
| NeuBird | Governed, zero-copy investigation | Cross-tool RCA with shared operational memory | Queries telemetry in place without retaining raw data | Policy-gated, human-approved production actions |
1. Sherlocks AI — best overall Cleric alternative
Sherlocks AI is a Cleric alternative that investigates production incidents using telemetry, infrastructure, code, and deployment context. It detects regressions, produces evidence-backed RCA, plans remediation, learns from incidents, and supports daily incident review.
When an alert fires, Sherlocks uses its Awareness Graph and more than 16 domain-specialized agents to investigate different parts of the production stack in parallel.
- Production context: Maps services, dependencies, infrastructure, behavioral baselines, deployments, prior incidents, runbooks, and operational conversations.
- Investigation and RCA: Tests competing hypotheses and returns the root cause, confidence, timeline, affected services, blast radius, ruled-out causes, and supporting evidence.
- Change detection: Connects production behavior to commits, pull requests, builds, deployments, configuration changes, scaling events, and infrastructure changes.
- Remediation: Provides short- and long-term mitigations, exact commands, step-by-step plans, and draft pull requests for engineers to review.
- Learning: Reuses previous investigations, approved resolutions, responder corrections, known failure patterns, and team instructions.
- Integration depth: Works across observability, cloud, Kubernetes, databases, queues, code, CI/CD, incident systems, Slack, and Microsoft Teams.
- Enterprise fit: Supports managed, hybrid, in-VPC, self-hosted, air-gapped, and private-model deployments with read-only access, SSO/SAML, RBAC, and audit logs.
- Economics: A free plan includes 30 monthly investigations; Enterprise provides unlimited investigations with custom pricing.
Limitation: Sherlocks can recommend changes and draft fixes but does not execute production changes. Its public materials also do not describe a general automated post-fix verification loop or a complete phone/SMS on-call suite.
2. Resolve AI — best Cleric alternative for closed-loop remediation
Resolve AI extends autonomous production investigation into controlled mitigation and operational action. Its Agent Teams investigate separate hypotheses in parallel while a verifier checks conclusions against production evidence.
- Verified investigation: Produces the root cause, causal chain, impact, affected services, evidence, and suggested fix.
- Controlled remediation: Supports approved commit reverts, GitHub Actions workflows, alert silencing, and other operational actions.
- On-call automation: Triages and investigates alerts before escalating them to a human responder.
- Human steering: Engineers can redirect agents, challenge findings, add evidence, or pursue parallel investigation threads.
- Broad connectivity: Integrates with observability, infrastructure, code, incident-management, and collaboration systems.
Limitation: Resolve is an enterprise-oriented platform with custom, credit-based pricing. Its write-capable workflows require more implementation and governance than a read-only investigation product.
3. Metoro — best Cleric alternative for Kubernetes
Metoro combines a Kubernetes observability platform with an AI SRE agent. Its eBPF collector captures runtime and deployment context before an investigation begins.
- Native Kubernetes context: Collects logs, metrics, traces, profiles, events, and resource changes without application SDKs or sidecars.
- Autonomous detection: Finds service regressions, dependency failures, workload errors, and cluster anomalies without requiring an alert for every condition.
- Code-to-runtime RCA: Connects incidents to deployments, commits, pull requests, configuration changes, and affected workloads.
- Deployment verification: Compares new rollouts with production baselines and flags regressions.
- Fix generation: Creates review-ready fix or rollback PRs with RCA evidence and telemetry links.
Limitation: Metoro is designed for Kubernetes and requires a compatible Linux environment for eBPF. It may duplicate an existing observability layer, and paid pricing scales by node and excess ingestion.
4. Datadog Bits Investigation — best Cleric alternative for Datadog
Datadog Bits Investigation is the strongest Cleric alternative for teams whose telemetry, topology, monitors, and incident workflows already live in Datadog.
- Native context: Investigates Datadog metrics, logs, traces, infrastructure state, Kubernetes events, topology, recent changes, and user impact.
- Hypothesis testing: Generates possible causes, runs targeted queries, and marks hypotheses as validated, invalidated, or inconclusive.
- Evidence-backed output: Returns a supported root cause or explicitly reports when the available evidence is insufficient.
- Operational memory: Uses previous investigations, runbooks, and responder feedback.
- Integrated response: Can create incidents or tickets, start workflows, and send code-related findings to Bits Code.
Limitation: Bits is most effective when the required data already resides in Datadog. AI Credits add usage-based costs to the underlying Datadog products; an autonomous investigation uses approximately 6.5 credits on average, with actual consumption varying.
5. NeuBird — best Cleric alternative for governed, zero-copy investigation
NeuBird is designed for enterprises that want AI SRE investigation without copying production telemetry into another data platform. It queries connected systems in place and retains investigation conclusions rather than raw logs, metrics, or traces.
- Zero-copy investigation: Reads telemetry from existing systems without creating another observability data store.
- Cross-stack context: Correlates observability, cloud, incident, code, ticket, runbook, and configuration evidence.
- Operational memory: Preserves tested hypotheses, root causes, actions, outcomes, service relationships, and human corrections.
- Governed autonomy: Uses Suggest, Recommend, and Act policies with approval gates and audit trails.
- Private deployment: Supports customer VPC or VNET deployment and policy-controlled access to production systems.
Limitation: NeuBird is a broader governance and operational-intelligence platform, not only an incident-investigation agent. Pricing is custom and credit-based, and production writes require human approval.
Best Cleric alternative by use case
Best Cleric alternative for AI SRE
Sherlocks AI is the best overall choice for cross-stack AI SRE because it combines production context, parallel investigation, change correlation, RCA, remediation planning, and memory. Choose Resolve AI for controlled execution or Metoro for a Kubernetes-native detection-to-fix workflow.
Best Cleric alternative for incident investigation
Sherlocks AI provides the broadest investigation coverage across telemetry, infrastructure, code, deployments, databases, queues, CI/CD, and operational knowledge. Resolve AI is strongest for parallel, human-steerable investigations, while Datadog Bits is the best fit when the relevant evidence already lives in Datadog.
Best Cleric alternative for production incident investigation
Sherlocks AI is the strongest overall option for mixed production environments requiring read-only safety and deep change correlation. Resolve AI is better when findings must lead directly to controlled production actions, while Metoro is strongest for detecting and verifying Kubernetes deployment regressions.