Cleric
AI SRE teammate that checks every production change and investigates incidents to root cause
By Cleric · 4.0/5 Value-Position score (estimate)
Positioning guardrails
Best for
- Platform and SRE teams running Kubernetes microservices that want every production change verified automatically.
- Engineering orgs that route alerts through Slack and want false positives dismissed before an engineer is paged.
- Teams already on Datadog, Prometheus, PagerDuty or Grafana that want AI root-cause analysis over existing telemetry.
- Companies adopting AI coding agents that need a production-side check on AI-written changes.
Ideal size: 20–500 engineers people · Scale-up with CI/CD, Kubernetes and an observability stack in place
Not for
- Teams without an observability stack, log/metrics access or a Slack-based release flow.
- Buyers expecting fully autonomous remediation; Cleric is read-only by default and proposes changes for human approval.
- Very low-change monolith teams where credit-based pricing (from $700/month) is hard to justify.
- Organizations that must self-host; Cleric is a single-tenant SaaS platform hosted on GCP.
Value metrics scorecard
Time-to-Value
Connect in an afternoon; value same day
~1 days to first production value
Total Cost of Ownership
$18,000/yr
Starts at $8,400 · Credit-based: Team $700/mo (1,400 credits), Pro $1,500/mo, Scale $3,000/mo, Enterprise custom; credits $0.50 each
Implementation Friction
2/5
Engineering + admin effort required
Value-Position score
out of 5 · model estimate
Full cost breakdown
Mandatory implementation fee
None
Seat tiers
Unlimited users on every plan; cost scales with completed work credits, not seats
Add-on costs
- Additional credits at $0.50 each, same per-credit rate as your plan
Company & support
Who is behind Cleric, and how your team gets help once it is live.
Company
- Founded
- Not recorded
- Headquarters
- Not recorded
How you get support
- PhoneNot listed
- EmailPaid plans
- Live chatNot listed
- Support portal / ticketsNot listed
- Community forumNot listed
- Help centre / docsAll plans
- Dedicated account managerEnterprise only
- In person / on-siteNot listed
- Hours
- Not recorded
- Response time
- Not stated
Team includes email support; Pro includes priority support; Scale adds a shared Slack channel with Cleric engineers; Enterprise adds a named customer success manager and DPA/security review.
“Not listed” means the vendor’s public pages don’t mention that channel, not that it is unavailable. Ask about it during evaluation.
Market position
Where Cleric sits against its closest alternatives. Pick any two of cost, speed, friction and buyer score, and up to 9 companies to compare.
Quadrant view
Typical annual cost × Time-to-value
The lines cross at the median of the solutions shown, so about half sit on each side of each line. A dashed ring marks an outlier pinned to the edge; hover for its value.
Companies on the chart 6 / 10
- Cleric
- Shortcut
- Whimsical
- Tally
- Better Stack
- Siit
Add or change companies
Up to 10 companies including Cleric. Listed closest first.
Stack fit signal
Compatibility with standard B2B ecosystems.
Ships an official MCP server. Connects to Claude Code, Claude Desktop, ChatGPT connectors and Cursor out of the box.
AI & MCP readiness
What Cleric ships in AI, and what it asks of your ecosystem.
AI features shipped
Cleric is an AI SRE agent: it follows each change for up to 14 days, flags regressions and anomalies, correlates logs, metrics and infrastructure changes, and proposes a fix pull request. It is read-only by default and does not merge pull requests or change infrastructure itself.
Your data & models
- Trains on your data
- Never trains on your data
- Runs on
- Anthropic, Google, OpenAI
- AI pricing
- Billed by usage or credits
In your ecosystem
- AI connection
- Official MCP server
- Model key
- Vendor's key
- AI usage audit
- Full audit trail
Compliance attestations
* IAPP AIGP certifies individuals, not products. It means named staff hold the credential — not that the platform does.
Bottom line
Cleric is an AI SRE agent for engineering teams. It follows each production change for up to 14 days, catches regressions, and investigates incidents from alerts or failed deploys, returning root cause, evidence and a fix pull request for human approval. It connects to existing observability, Kubernetes, code and alerting tools with read-only access by default, works in Slack or the web app, and can be driven from MCP clients. Pricing is credit-based: Team from $700/month, all plans with unlimited users.
Frequently asked questions
How is Cleric priced?
Cleric charges in credits for completed work. Team is $700/month with 1,400 credits, Pro $1,500/month with 3,000 credits, Scale $3,000/month with 6,000 credits, and Enterprise is a custom annual credit pool. Credits cost $0.50 each; a change verification costs 2 credits and an issue investigation 10 credits. All plans include unlimited users.
What access does Cleric need to our production systems?
Read-only access to logs, metrics, Kubernetes metadata, alert metadata and, optionally, source code and documentation, scoped by RBAC or the access scopes each system supports. Some integrations add write permissions only to propose changes, for example opening a pull request; Cleric is instructed not to merge pull requests or push to your default branch.
Does Cleric train on our data?
No. The pricing FAQ states Cleric does not use customer data to train Cleric or its underlying models, and the security page says data is never used to train or fine-tune models. Raw logs, metrics and code are queried at runtime and not persisted.
Which AI models does Cleric run on?
The security page names Anthropic, Google Gemini and OpenAI as LLM providers, reached through their enterprise API endpoints with contractual zero-data-training and zero-data-retention guarantees.
Can we use Cleric through MCP?
Yes. All plans include MCP access: you can connect your own MCP servers to Cleric and use Cleric from Claude Code, Cursor and other MCP clients.
How long does implementation take?
Cleric connects to your existing observability, infrastructure, code and documentation tools; the vendor says a stack can be connected in an afternoon, with read access by default and write access added when you are ready. The free trial includes 500 evaluation credits with no time limit.