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Tomosu AI
$150000/yrStarting price
0Popularity
About Tomosu AI
Tomosu AI serves as an AI governance layer designed to embed reliability intelligence across the entire software development lifecycle, from development to production. It continuously scores applications using the Production Reliability Index (PRI) and a multi-tier agentic system, identifying and closing reliability gaps before incidents occur. The platform operates across development, pre-merge, and runtime phases, enforcing policies, detecting regressions, and protecting service-level objectives (SLOs). By integrating with existing tools such as GitHub, Datadog, and Jira, Tomosu AI provides a unified reliability loop that hardens code, enforces guardrails, and turns runtime learnings into new guardrails without manual rule updates. Tomosu AI is tailored for engineering, SRE, and support teams seeking to reduce support escalations, post-deployment failures, and governance overhead. It distinguishes itself from point solutions by offering a common governance language that is built for AI-generated changes rather than retrofitted onto human-centric workflows. The platform provides a single, trendable risk ledger—the PRI—that stakeholders across engineering, finance, and leadership can use to track and budget against reliability. Designed to sit above existing stacks, Tomosu AI works with tools teams already rely on while maintaining read-only access by default and enforcement under user control.
Key features
- Continuous reliability scoring with PRI
- Multi-tier agentic incident resolution
- Pre-merge policy enforcement
- Runtime SLO protection and regression detection
- Automated escalation handling with root-cause context
- Governance policy management for AI-generated code
- Audit-ready decision logging
- Integration with IDEs, CI/CD, and observability tools
Use cases
- Preventing production incidents through proactive governance
- Reducing support escalations via automated issue resolution
- Improving software reliability for AI-powered development workflows
Pros
- Continuous reliability scoring with Production Reliability Index (PRI)
- Multi-tier agentic system for automated incident resolution
- Integration with existing development and observability tools
- Closed-loop governance that learns from production incidents
- Audit-ready governance decisions with evidence trails
Cons
- No free tier beyond read-only functionality
- Limited to teams using supported platforms (GitHub, GitLab, Bitbucket)
- Requires integration with existing tooling for full functionality
Frequently asked questions about Tomosu AI
What is Tomosu AI and what does it do?
Tomosu AI is an AI governance layer designed to continuously score applications using the Production Reliability Index (PRI) and a multi-tier agentic system. It operates across development, pre-merge, and runtime phases to prevent incidents, resolve issues automatically, and learn from escalations.
Who is Tomosu AI designed for?
The platform is designed for engineering, SRE, and support teams to reduce support escalations, post-deployment failures, and governance overhead. It is particularly suited for teams running on GitHub, GitLab, Bitbucket, and other DevOps tools.
How does Tomosu AI integrate with existing tools?
Tomosu AI integrates with existing tools like GitHub, Datadog, Jira, New Relic, Sentry, PagerDuty, ServiceNow, Zendesk, Linear, Slack, and others to enforce policies, detect regressions, and protect service-level objectives (SLOs).
What is the Production Reliability Index (PRI)?
The Production Reliability Index (PRI) is a unified, trendable number that scores applications based on their reliability across development, pre-merge, and runtime phases. It helps teams track and improve reliability over time.
Does Tomosu AI offer a free edition?
Yes, Tomosu AI offers a free edition that allows users to scan a repository for their PRI score without requiring a credit card. The free edition is read-only by default.
How does Tomosu AI learn and improve over time?
Tomosu AI uses a closed-loop system where runtime learnings are automatically converted into new guardrails without manual rule updates. This ensures the governance layer gets smarter every week.
