Governed AI coding, end to end
Govern AI-generated code before it reaches production.
ScryAgent adds policy enforcement, testing, accessibility, SEO checks, approvals, and auditability around the coding agents your team already uses.
Human approval stays in the loop — nothing merges or deploys without you.
Every task follows the same governed path
- Task
- Plan
- Approval
- Agent
- Validation
- Policy
- Review
- Draft PR
The gap coding agents leave open
Your Coding Agent Is Only Part of the Workflow
A coding agent can write a plausible diff in minutes. Before it ships, your organization still has to answer:
- Was it actually tested?
- Does it meet accessibility requirements?
- Did it hurt SEO or break metadata?
- Did it touch a protected file or system?
- Did it violate an organizational policy?
- Who reviewed it, and who approved it?
- What exactly changed — line by line?
- What did it cost to produce?
ScryAgent turns those questions into a governed workflow, not a post-incident investigation.
Evidence, not blind trust
See exactly what changed, why it's safe, and who signed off.
ScryAgent clearly separates deterministic test results, policy-engine decisions, AI interpretation, and human approvals — this is the same task-detail view your team would see in the product.
Add cookie-consent banner to marketing pages
PR CREATED3 routes changed: components/marketing/cookie-consent.tsx, app/layout.tsx, lib/analytics.ts
See this running against your own repository.
Request Early AccessHow It Works
- 1
Submit the task
Describe the change and its acceptance criteria; ScryAgent creates a tracked task.
- 2
Review the plan
The agent proposes a plan before writing any code. Nothing runs until a human reads it.
- 3
Approve execution
A human approves the plan, or sends it back with requested changes.
- 4
Let your coding agent work
Claude, Codex, or another supported agent executes inside an isolated environment.
- 5
Validate the result
Build, lint, type-check, tests, accessibility, and SEO checks run automatically.
- 6
Review the evidence
See the diff, the validation results, the policy findings, and the AI reviewer's read — kept visually distinct from one another.
- 7
Approve the Draft PR
A human makes the final call. ScryAgent opens a draft pull request; it never merges or deploys on its own.
Core capabilities
Built for website and digital experience teams
Governance that understands websites, not just diffs.
ScryAgent is purpose-built for the things that make website changes risky in ways generic code changes aren't:
Accessibility
- WCAG conformance
- Keyboard navigation
- Focus management
- Semantic markup
SEO
- Metadata correctness
- Canonical URLs
- Structured data
- Link integrity
Experience
- Responsive behavior
- Performance regressions
- Browser compatibility
- Form behavior
Governance
- Analytics & tracking
- Design-system consistency
- Content accuracy
- Public-facing risk
This is deliberately a website operations platform, not a general-purpose autonomous software factory — that's where the checks that matter live today.
AI execution with guardrails
The agent gets a sandbox, not the keys.
Coding agent
Proposes the change inside its own isolated run.
Sandbox
Executes with least-privilege access, no arbitrary shell access.
Policies
Organization-defined rules check every change automatically.
Validation
Build, test, accessibility, and SEO checks run before anyone reviews.
Human approval
Nothing merges or deploys without an explicit human decision.
Each layer narrows what the next one is allowed to do — control tightens, it never loosens.
- Isolated execution environments — every run happens in its own disposable environment.
- Least-privilege access — the agent gets only the tools and scope a task needs.
- Human approval at two checkpoints — before execution starts, and before the diff ships.
- Controlled tool access — no arbitrary shell access beyond what's explicitly allowed.
- No autonomous production deployment — ScryAgent opens a pull request; it doesn't deploy.
- No autonomous merging — a human merges, always.
- Protected credentials — secrets are never exposed to the agent in plaintext.
- Budget limits — spend ceilings stop a task before it runs away.
- Audit logs — a durable, tamper-evident record of what happened.
- Policy controls — organization-defined rules, enforced automatically.
Bring these guardrails to your own coding agent.
Request Early AccessA governance layer, not another model to adopt.
ScryAgent doesn't ask your team to switch coding agents. It sits around the ones you already use — reviewing, validating, and gating what they produce. Anthropic's Claude and OpenAI's Codex are supported today, with support for additional runtimes planned as the ecosystem grows.
What changes when you add ScryAgent.
| Capability | AloneCoding Agent Alone | ScryAgent |
|---|---|---|
| Generates code | Yes | Yes |
| Runs tests | Sometimes | Yes |
| Organization policies | No | Yes |
| Accessibility checks | No | Yes |
| SEO checks | No | Yes |
| Human plan approval | No | Yes |
| Final diff approval | No | Yes |
| Audit trail | No | Yes |
| Spend controls | No | Yes |
| Draft PR governance | No | Yes |
Ready to see the difference on your own codebase?
Request Early AccessEarly access
Join the ScryAgent pilot.
We're working with web and digital teams that want to adopt AI coding agents without giving up control. Tell us about your team and we'll reach out.
- Keep the coding agent your team already uses
- Governed plan and diff approval from day one
- Deterministic validation and policy enforcement built in
- Direct input into what we build next