Before you scale AI agents, know where you stand
No standard yet defines what "ready for AI agents" means. PEDCO AuditPro assesses your process against a curated agentic-engineering reference model—and tells you, clearly, how ready you are and what to close first.
The challenge
Teams are adopting AI coding agents fast—but agents amplify whatever process they find. Rushing in without the right guardrails scales inconsistency and risk instead of throughput. Yet there's no ISO or ASPICE for "engineering with agents" to measure yourself against.
PEDCO AuditPro gives you a clear, evidence-based readiness verdict—before you commit.
We carry the knowledge
PEDCO AuditPro doesn't only verify the standards you bring—for agentic engineering, we bring the reference model. It's authored from proven practices and our own dogfooded engineering conventions, maintained and versioned as the field evolves. So you get an assessment even where no assessable standard exists.
Our approach
You bring your process. We bring the reference model and assess it from real evidence.
Curated agentic-engineering practices
Proven practices, curated and kept current as the field evolves—so you can be assessed even where no formal standard exists yet.
Evidence-grounded, not a questionnaire
Readiness levels, not pass/fail
Opportunities, not compliance findings
What we assess
The qualities that make your QMS and process ready to guide autonomous agents—assessed from your actual documentation, not a questionnaire.
Explicit, unambiguous processes
Your processes are documented clearly enough for an agent to follow—no reliance on tribal knowledge or reading between the lines.
Clear decision boundaries
Your process defines which decisions can be delegated and which need human judgment—so agents know where their authority ends.
Current and consistent
Documentation is up to date and free of contradictions—agents amplify whatever they find, including stale or conflicting procedures.
Explicit work-product expectations
What each step must produce—templates, required content, approvals—is defined, so agent output can be checked against a clear standard.
Defined human checkpoints
Your QMS specifies where reviews, sign-offs, and approvals are required—the points that must stay human.
AI-use policy in your QMS
An explicit, current policy governing how agents may be used within your quality system—and where they may not.
Readiness is assessed against your real QMS and process evidence—not a self-reported questionnaire.
You get readiness levels, not a pass/fail
Each practice area rolls up to a readiness level, so you know exactly where to invest.
What you walk away with
A readiness level per practice area, grounded in evidence
Prioritized opportunities—what to close first for the most impact
Readiness opportunities and recommendations, never compliance findings
A shared, defensible baseline to align leadership before you scale agents
A clear path from "assessing" to governing agents in production
Confidence that you're adopting agents deliberately, not blindly
Ready is the start, not the finish
Once you know where you stand, keep humans and agents inside the same guardrails as work happens.
Explore Agentic Engineering Governance