agentic sqa
An evidence-first software verification platform that turns code-change and quality signals into prioritized, reviewable risk assessments and developer-ready actions.
Private beta begins with a focused kernel regression risk advisor workflow and expands through fast capability releases - while building toward a broader systems verification platform.
What is Agentic SQA
Agentic SQA is IR Labs’ primary active build program and the first productized workflow in a broader systems verification platform direction.
It is designed to improve software verification workflows by transforming noisy signals into evidence-backed risk assessments and actionable outputs that engineers can review, challenge and use.
The goal is not more alerts. The goal is better decisions: stronger rationale, clearer evidence and faster movement from signal to action.
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Prioritize findings with traceable rationale
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Interpret signals in code and workflow context
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Produce reviewable actions, not opaque model responses
The Problem
Software teams generate more verification signal than humans can reliably process at review speed. PRs, regressions, static findings, test failures and runtime indicators all compete for attention.
The bottleneck is not only signal volume. It’s signal usability: incomplete context, weak rationale and too little evidence packaged in a way that supports confident engineering decisions.
That gap appears in everyday software workflows today - and becomes more severe as verification moves deeper into firmware, binaries, toolchains and hardware-software interfaces.
The challenge is not just detection. It is evidence-backed verification at machine speed with human reviewability.
Why evidence matters
Agentic SQA is built around evidence-backed outputs. A flagged risk should come with rationale and supporting signals - not just a model-generated conclusion.
That evidence layer is what moves verification workflows from opaque automation toward reviewable, controllable decision support. It also creates a stronger path for trust, adoption and iterative improvement.
Analogs and precedent — previous similar patterns or comparable signals
Context links / locations — where the signal maps into relevant code or workflow context
Signal traces — supporting traces or signal history used in the assessment
Risk rationale — explicit explanation for why something was surfaced
Reviewable artifacts — outputs engineers can inspect, challenge and act on
how it works
Ingest Signals
Collect and normalize relevant verification signals from target workflows so they can be evaluated consistently.
Build Context
Interpret signals in the relevant code and workflow context to improve prioritization and reduce low-value noise.
Generate Evidence-Backed Risk Assessments
Produce prioritized risk outputs with supporting rationale and evidence artifacts that can be reviewed.
Deliver Developer-Ready Actions
Package outputs into forms that support engineering workflows so teams can move from signal to action faster.
beta
Kernel Regression Risk Advisor Workflow
The private beta launches with a focused kernel regression risk advisor workflow designed to validate output usefulness, evidence quality and workflow fit in a production-oriented setting.
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A reviewable risk-advisor workflow for kernel regression signals, with evidence-backed outputs intended to support faster and more confident triage decisions.
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Signal usability, evidence quality, reviewer confidence and operational fit inside real engineering workflows.
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We are intentionally starting with a narrow workflow so we can improve quickly from real usage and release new capabilities at a high cadence.
who is beta for
We’re looking for teams with real verification and triage workflow pain, clear evaluation paths and a willingness to provide structured feedback during beta.
Primary beta participants
Engineers and reviewers responsible for PR quality and regression decisions
QA / validation / reliability workflows with triage bottlenecks
Platform or systems teams evaluating verification signal quality and reviewability
Secondary stakeholders
Engineering managers responsible for release confidence and verification throughput
Reliability or security leaders evaluating evidence quality and control requirements
Tooling / developer productivity teams exploring workflow fit
fast release cadence
Expanded verification coverage
Broaden the range of supported verification scenarios and categories as beta feedback confirms utility and reliability.
Richer evidence and controls
Increase evidence depth, reviewability, and control layers to support safer adoption and stronger reviewer confidence.
Workflow integration improvements
Tighten fit with engineering workflows so outputs are easier to consume, review and act on in practice.
Where We’re Headed
Agentic SQA is the first productized workflow in a broader systems verification platform direction. The same evidence-first model can extend beyond software code into deeper layers of the engineering stack.
We view software verification, firmware and binary analysis, toolchain handoffs and systems engineering verification as connected symptoms of one larger problem: human-speed verification is breaking under system complexity.
The platform expands by proving utility in narrow workflows first, then extending the same evidence-backed approach into deeper handoffs over time.
From software verification to systems verification
Interested in the agentic sqa private beta?
We’re always on the lookout for feedback. We’re speaking with teams that have real verification and triage workflow pain and want to evaluate an evidence-first, reviewable approach.