What are the best alternatives to SRE.ai?

Based on documented capability coverage across the Agentic Index 14 point taxonomy, the closest alternatives to SRE.ai among SRE and DevOps agents are incident.io, Ciroos AI, Harness, Wild Moose. Each is graded on the same public evidence, and no vendor pays for placement.

Does SRE.ai give you tracing and observability into agent runs?

Full under the Agentic Index verification standard. SRE.ai publishes public evidence of tracing, observability and audit logging into agent runs, so a team can see what an agent did and why. Evidence basis: Agents 'surface every action they take', with their reasoning, structured plans and step by step progress with timestamps and artifacts. Each action is tied to Changes, which tracks each change from design through deployment. Automations ke. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

Does SRE.ai require human approval before an agent acts?

Full under the Agentic Index verification standard. SRE.ai publishes public evidence of human approval steps and guardrails, so an agent action can be held for review before it executes. Evidence basis: Agents pause at key decision points for user input. Design documents need approval before building begins, generated code is presented for review before it is committed, and a deployment shows what will change before it runs. Member roles a. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

Does SRE.ai have SOC 2, SSO and role based access control?

Partial under the Agentic Index verification standard. SRE.ai publishes some public evidence of security and identity controls, but narrower than the full set of SOC 2, single sign on (SSO) and role based access control (RBAC). Evidence basis: Customers get Owner, Admin and Member roles. Members are read only and Admins cannot delete. GitHub access runs through a GitHub App. A Security Portal sits at trust.sre.ai, and security and compliance documents are offered as files, but no. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

Back to vendors

SRE.ai

Q: Who is SRE.ai for?

enterprise, Salesforce development teams, MSPs and integrators, DevOps teams

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SRE / DevOps agentindependentVerified 2026-09-29

Entry priceContact sales / book a demo (enterprise)Full pricing detail

AI DevOps platform for Salesforce delivery, with Design, Build and Deploy agents that pause for approval, plus event driven automations across Salesforce orgs, GitHub, GitLab and Jira.

SRE.ai builds natural language AI agents for enterprise DevOps, starting with Salesforce delivery. From a chat, requests are routed to a Design Agent that writes design documents, a Build Agent that writes code and test classes, and a Deploy Agent that deploys to connected Salesforce orgs. Agents pause for approval of designs, review of code before commit and a preview of what a deployment will change, and they show every action with plans, timestamps and artifacts, tied to Changes that track each change from design to deployment.

Automations built from triggers and steps run when a deployment completes or on demand, and the GitHub App, GitLab, Jira, Microsoft Teams and Supabase integrations let the platform manage branches and pull requests and update tickets. Workspaces carry Owner, Admin and Member roles, and a security portal sits at trust.sre.ai. Founded in 2024 by former Google Research and DeepMind engineers, SRE.ai is a Y Combinator company that raised a 7.2 million dollar seed round led by Salesforce Ventures and Crane Venture Partners.

Vendor details

Canonical URL

https://www.sre.ai

Company status

independent

Use cases & customers

Primary use cases

low-code DevOps automationCI/CD and deployment orchestrationmerge conflict resolutionrelease testing and rollback

Target customers

enterpriseSalesforce development teamsMSPs and integratorsDevOps teams

Deployment options

SaaS (agents integrate into your stack)

Integrations

Salesforce orgs, GitHub (GitHub App), GitLab, Jira, Microsoft Teams and Supabase.

In practice

Your Salesforce team wants changes designed, built and deployed from one request. SRE.ai routes a chat request to its Design, Build and Deploy agents, which pause for approval of the design, review of the code before commit and a preview of what the deployment will change.

Your release manager spends time updating Jira after every deployment. SRE.ai links each deployment to its Jira tickets and updates their status automatically, and an Automation can run its next steps when a deployment completes.

Your team needs regression tests for every Salesforce change. The Build Agent writes regression test classes alongside the code, and Changes tracks each change from design through deployment.

Sources & related URLs

Research sources

https://www.sre.ai https://github.com/agamm/awesome-ai-sre

Agentic Index coverage score

7.5 / 14 capabilities · 54%

Integrations & Tool Calling	Full
Agents act in the customer's systems. The GitHub App lets SRE.ai track branches, trigger automations and manage pull requests. Jira links deployments to tickets and automates status updates, and the Deploy Agent deploys to connected Salesforce orgs. GitLab, Microsoft Teams and Supabase integrations sit alongside them. SourceSRE.ai docs, Integrations and Agents; docs.sre.ai/setting-up-sre.ai/integrationsread 2026-09-29
Workflow Orchestration	Full
Customers build Automations in a builder. Each starts with a trigger followed by Steps that 'define the sequence of instances and dependencies', with conditions and criteria for each step. Chat requests are routed to Design, Build and Deploy agents that hand work along the lifecycle. SourceSRE.ai docs, Automations and Agents; docs.sre.ai/using-sre.ai/automationsread 2026-09-29
Knowledge Grounding & RAG	Partial
Agents draw on the connected Salesforce orgs, repositories and tickets, read at task time. Each agent is 'powered by a specialized LLM trained on Salesforce development patterns', so its Salesforce knowledge lives in the model's weights. SRE.ai names no maintained index or graph over the customer's knowledge. SourceSRE.ai docs, Agents; docs.sre.ai/using-sre.ai/agentsread 2026-09-29
Human Oversight & Guardrails	Full
Agents pause at key decision points for user input. Design documents need approval before building begins, generated code is presented for review before it is committed, and a deployment shows what will change before it runs. Member roles are read only. SourceSRE.ai docs, Agents and Roles and permissions; docs.sre.ai/using-sre.ai/agentsread 2026-09-29
Security, Identity & Governance	Partial
Customers get Owner, Admin and Member roles. Members are read only and Admins cannot delete. GitHub access runs through a GitHub App. A Security Portal sits at trust.sre.ai, and security and compliance documents are offered as files, but no readable attestation is published in either place. SourceSRE.ai docs, Roles and permissions and Security and compliance documents, and trust.sre.ai; docs.sre.ai/setting-up-sre.ai/roles-and-permissionsread 2026-09-29
Observability & Auditability	Full
Agents 'surface every action they take', with their reasoning, structured plans and step by step progress with timestamps and artifacts. Each action is tied to Changes, which tracks each change from design through deployment. Automations keep a run history in the Activity tab. SourceSRE.ai docs, Agents and Automations; docs.sre.ai/using-sre.ai/agentsread 2026-09-29
Memory & State Persistence	Not documented
No state carries over from previous runs, which SRE.ai says keeps agent results reproducible and prevents unintended side effects between tasks. SourceSRE.ai docs, Agents; docs.sre.ai/using-sre.ai/agentsread 2026-09-29
Deployment & Data Residency	Not documented
The hosted service connects to the customer's orgs and repositories. No hosting region or customer environment option is published. SourceSRE.ai docs and trust.sre.airead 2026-09-29
Prebuilt Agents, Templates & Packs	Full
Three named prebuilt agents each do their own job. The Design Agent writes design documents, the Build Agent writes code and test classes, and the Deploy Agent handles deployments. A prompt library and an automations cookbook sit beside them. SourceSRE.ai docs, Agents and the docs index; docs.sre.ai/using-sre.ai/agentsread 2026-09-29
Triggers & Channel Coverage	Full
An Automation is 'a sequence that runs automatically when a specific event happens'. The Deployment trigger fires 'when a deployment completes', and the automation then runs without anyone starting it. The other trigger is manual, and agents also answer chat requests. SourceSRE.ai docs, Automations and Triggers; docs.sre.ai/using-sre.ai/automations/triggersread 2026-09-29
Model Flexibility & Routing	Not documented
Each agent is 'powered by a specialized LLM trained on Salesforce development patterns', and SRE.ai picks the model. It names no provider and no way for customers to choose a model. SourceSRE.ai docs, Agents; docs.sre.ai/using-sre.ai/agentsread 2026-09-29
APIs, SDKs & MCP Extensibility	Not documented
No API, SDK, CLI or MCP server for driving SRE.ai is published. Its documentation covers setup, chat, agents, changes, automations, use cases, troubleshooting and security. SourceSRE.ai docs index; docs.sre.airead 2026-09-29
Testing, Debugging & Optimization	Partial
Testing is aimed at the customer's Salesforce changes. The Build Agent writes regression test classes, QA and code review are among the published use cases, and generated code is reviewed before commit. SRE.ai names no evaluation of the agents' own output. SourceSRE.ai docs, Agents and the docs index; docs.sre.ai/using-sre.ai/agentsread 2026-09-29
Browser & Computer Use	Not documented
Agents work through the Salesforce, GitHub, GitLab and Jira integrations and chat. SRE.ai names no browser, desktop or computer control. SourceSRE.ai docs; docs.sre.airead 2026-09-29

The Agentic Index coverage score grades every vendor Full, Partial or Not documented against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded

Pricing

Contact sales / book a demo (enterprise)

What is public

No public pricing; enterprise DevOps automation, book a demo.

Variable cost rationale

No public pricing; enterprise and sales quoted.

Sales call required

Yes, required for paid access

Free / trial

Demo

Agentic Index verified 2026-07-22

Related vendors

Alternatives to SRE.ai

The closest documented capability profiles to SRE.ai among SRE and DevOps agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.

incident.io10.0 / 14Adds documented Memory & State Persistence and Model Flexibility & Routing, among others
Ciroos AI7.5 / 14Adds documented APIs, SDKs & MCP Extensibility
Harness7.5 / 14Adds documented APIs, SDKs & MCP ExtensibilitySRE.ai vs Harness →
Wild Moose7.5 / 14Adds documented Deployment & Data Residency
Cased8.0 / 14Adds documented Deployment & Data Residency and APIs, SDKs & MCP Extensibility
Resolve AI11.0 / 14Adds documented Memory & State Persistence and Deployment & Data Residency, among others

Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded

Compare SRE.ai with other vendors →Compare all SRE and DevOps agents →See where SRE.ai ranks →

Data confidence: medium

Head to head

SRE.ai vs Harness