Copilot and Cursor write the code. Static analyzers grade the syntax. APMs watch what already broke. Tomosu sits above all of them. It’s the layer that decides what reaches production, scores the risk, finds the change that caused the page, and writes the audit trail.
This is agentic reliability in practice: purpose-built AI agents for policy, risk, context, and evidence work collaboratively in real time. No single model decides alone. Each agent owns a domain, challenges the others, and together they produce a reliability verdict no monolithic tool can match.
Every PR clears a streaming evaluation lane: context resolved, policy aligned, risk composed, evidence written. Before merge, not after the page.
Explore the lane ScoreEight calibrated indexes roll up into a single Production Reliability Index. Trendable across quarters. Readable by the CTO, CFO, CIO, and CCO without translation.
See the indexes ResolveThe moment something fails in production, the responsible change is on the table. Engineers stop firefighting. The same failure pattern doesn’t ship twice.
How it works ProveSOC 2, ISO, internal AI-use policy: every reliability decision is logged with a defensible audit trail, ready to file the day the auditor asks.
Talk to usStatic analyzers give you pass/fail. APMs give you mean-time-to-detect. Tomosu gives you eight trendable, executive-readable signals, calibrated to your stack, plus Agent Reliability for codebases that run agents of their own.
A single trendable master score that rolls up the seven sub-indices, plus Agent Reliability on codebases that run their own agents, calibrated per organization to reflect your architecture, maturity, and risk tolerance. The one number the board tracks.
How likely this code is to break, based on structural signals and real production behavior.
The gap between what dev expected and what production delivered. “Test like you fly.”
Severity-weighted adherence to your organization’s coding, security, and observability standards.
Live production health: error rate, latency, and resource anomalies aggregated per service.
Churn and hotspot density, mapped onto technical debt quadrants. Penalizes files that keep re-triggering the same issues.
Frequency and safety of releases. Rewards small, confident batches.
The interrupt tax on engineering: repeat ticket rate, tier-level MTTR, senior on-call load.
How the agents in your own codebase behave: tool-protocol and tool-result errors, execution tracing, context management, authorization, safety governance and execution budgets. Added to the roll-up only for codebases that run AI agents.
One weighted score. One trendline. Calibrated to your org, not a generic template.
Want to see the indexes in motion? Walk the interactive PRI Impact Ledger to model how each index moves the roll-up score, or place your org on the reliability maturity model to see what the next stage requires. Background reading: why a signal is not a gate and the two halves of a merge gate.
VisionBoard is where humans read the score. The Git Agent is where the score acts on your pipeline. Both are included from the free plan, what grows with your plan is scope, not access.
Every index, every trendline, every repository in one place, readable without a translation layer between engineering and the board.
It branches, commits and opens the pull request, and holds the merge behind a PRI gate, so a change that would move the score the wrong way never lands quietly.
Full plan detail lives on the pricing page.
