Architect · Detect · Remediate — 11 axes, 9 modules, one thread
The agentic compliance architect for the modern web.
ariada.ai is multi-agent orchestration that architects compliant systems from L0 Mindset, detects drift continuously across eleven scanner-axes, and remediates at source through autonomous pull-request generation. Nine integrated pipeline modules. One Ariadne thread. We test, we control.
Source-level remediation only — agentic suggestions are not autonomous deployments; pull requests require client merge. Not a legal certification body.
ARIADA is the agentic compliance architect for the modern web — multi-agent orchestration that architects compliant systems from L0 Mindset, detects drift continuously across eleven axes, and remediates at source through autonomous pull-request generation. L4 Runtime/Overlay is intentionally not built (anti-overlay strategy — conflated detection and runtime remediation is what fined accessiBe). Source-level fixes only — agentic suggestions are not autonomous deployments; PRs require client merge. We test, we control — for accredited certification, customers consult a notified body or registered auditor. Regulator-facing dossier preparation runs through our sibling partner Governancer.
01 Architect
Build right from the first stroke.
Compliance starts before code. ARIADA's L0–L2 Foundation tier transforms how client teams design, code, and ship — so the product is born with accessibility, security, and AI Act transparency as defaults, not patched in later. Multi-agent orchestration generates accessible code from scratch, not just remediates after.
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L0 Mindset
Opensource bible — 10 design rules, Cobbler's Shoes Test, Progressive Enhancement architecture. Brand-bibled LMS for client team enablement.
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L1 Design
Figma / Adobe / Sketch plugins enforce WCAG-compliant palettes, typography, and component patterns at design time. Designers can't ship inaccessible artifacts without explicit friction.
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L2 Dev Tools
IDE extensions, ESLint plugins, GitHub Action, MCP server. Proactive accessible code generation (research roadmap) — agents emit accessible-by-default code from scratch.
02 Detect
Continuous measurement across eleven axes.
Once shipped, ARIADA scans the deployed surface every cycle — accessibility, security, performance, sustainability, AI Act, and legal-risk telemetry, all woven into one Ariadne thread. Multi-tool consensus, AI-author attribution, tamper-evident evidence chain.
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Eleven scanner-axes
L3 WCAG/EAA · L5 Security · L6 SEO/GEO/AIEO · L7 Perf · L8 Sustainability · L9 AI Act · L10 Legal. One engine, one scan, one report.
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Multi-tool consensus
Normalizes axe-core / Lighthouse / Siteimprove / WAVE / Pa11y into a canonical score. Cross-tool reproducibility — customers see the same number any third party would compute.
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AI authorship attribution
Fingerprints code by author — Copilot, Cursor, Claude Code, Windsurf, Devin. Methodology cross-referenced against 6,439,303 samples.
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Regression detection
Cross-deploy diff engine clusters root causes and surfaces per-component trends. New violations get their full provenance, not just a count.
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Regulator-grade evidence
Hash-anchored evidence stream (HAES) emits EU AI Act Art. 50 transparency artifacts on a tamper-evident chain.
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Stakeholder visualisation
Dracula character visualisation turns numeric reports into narrative your VP, board, and regulators can read in one minute. Same engine as draculascan.com.
03 Remediate
Autonomous pull requests, source-level, human-in-loop.
Detection without remediation is just a complaint. ARIADA's multi-agent cascade turns each finding into a source-level pull request — the client merges, ARIADA re-scans, the loop closes. No runtime overlay. No collapse. This is the GitOps-style independence that keeps ARIADA on the right side of the FTC v. accessiBe line.
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Tiered LLM remediation cascade
Cheap-to-expensive routing emits source patches: deterministic → Cerebras / Gemini Flash → Claude Sonnet → Claude Opus. Cache and reuse, framework-aware diffs.
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Backlog optimizer
MIP + ML schedules fixes under sprint capacity, severity, dependency, and budget constraints.
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CI/CD gate
Differential AI-vs-human thresholds; blocks PR merge below budget. Source-controlled compliance via clamper.ai.
Source-level fixes only — agentic suggestions are not autonomous deployments. Pull requests require client merge; client owns the commit; ARIADA re-scans after merge. Detection on the deployed surface, remediation in the pull request: physically separated by Git itself.
Nine modules — one platform
Each module is a focused capability that snaps into the platform. Marketplace standalones (blamer.ai, clamper.ai, reverter.ai) ship one module each. ariada.ai ships all nine under one contract.
Multi-domain scan
One scan emits WCAG 2.1/2.2, EAA, EN 301 549, Section 508, ADA Title II/III, DOS-lagen evidence.
LLM remediation cascade
Cheap-to-expensive cascade emits source-code patches. Cache and reuse, framework-aware diffs.
CI/CD gate
Differential AI-vs-human thresholds. Blocks PR merge below budget.
Regression detection
Cross-deploy diff engine; clusters root causes; per-component trend.
Canonical scoring
Normalizes axe / Lighthouse / Siteimprove / WAVE / Pa11y. Emits signed per-domain measurement reports (not legal certifications).
Backlog optimizer
MIP + ML over backlog under sprint capacity, severity, dependency, and budget constraints.
AI authorship attribution
Identifies Copilot, Cursor, Claude Code, Windsurf, Devin. Methodology validated on 6.4M samples.
AI artifact audit
Registry validates AI artifacts; emits EU AI Act Art. 50 evidence package.
Scan visualization
Character-themed scanner visualization for stakeholder reports. Same engine as the draculascan.com viral demo.
"The agentic compliance architect for the modern web — multi-agent orchestration that architects compliant systems from L0 Mindset, detects drift across eleven scanner-axes, and remediates at source through autonomous PR generation. Suggests source-level fixes, gates them in CI, attributes the AI that wrote them, scores them on a canonical scale, and emits regulator-grade evidence packages. Nine integrated pipeline modules. One Ariadne thread. We test, we control."
For regulator-facing dossier preparation and submission, ARIADA partners with sibling SaaS Governancer — end-to-end EU AI Act / GDPR / MDR / FDA PCCP / NYC LL 144 paperwork. See Partner ecosystem.
Validation evidence (honest framing)
The AI authorship attribution module's multi-signal methodology was cross-referenced against 6,439,303 code samples spanning 64 distinct AI models across 13 programming languages and 9 published datasets. All seven research claims were CONFIRMED with strong-to-very-strong evidence at scale. End-to-end ariada.ai classifier accuracy on production customer code is pending Q3-Q4 2026 pilots — we do not claim "validated on N customer sites."
See the Trust page for the validation record. Investor due-diligence materials — including IP-portfolio status — are at /investors.
Pain → Solution → Savings
Per medium customer (50 devs). Sources: CodeRabbit (470 PRs), GitClear (211M lines), UsableNet H1-2025, EU AI Act Art. 50.
| # | Validated pain | Annual cost without ariada.ai | Savings with ariada.ai |
|---|---|---|---|
| 1 | Tool sprawl: 3-5 a11y tools, no integration | $300K-$1.2M direct + 1-2 FTE integration | $150-600K saved — canonical scoring and multi-domain scan collapse the stack into one contract |
| 2 | EAA (European Accessibility Act) enforcement risk (active since June 2025) | DE €100K + FR €250K + SE €200K + IE criminal (18 mo) | De-risk via signed per-domain measurement reports, multi-domain scan, and tamper-evident evidence chain |
| 3 | EU AI Act Art. 50 non-compliance (mandatory Aug 2026) | up to €35M or 7% global turnover | Evidence package via the AI artifact audit (HAES) — Art. 50 transparency record per AI artifact |
| 4 | AI code 1.7× bugs → backlog explosion | $500K AI-induced bugs + $1.5M rework | $250-625K saved — differential CI gate, AI attribution, LLM remediation, and backlog optimizer working together |
| 5 | ADA litigation (4,605 lawsuits 2024, 69% e-commerce) | $20K-$200K settlement amortized + $50-200K legal | Signed measurement reports for due-diligence + insurance underwriting (carrier-dependent) |
Two ways forward
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Book a demo
30-minute scoping call, no slide deck. Bring one property URL and one regulator deadline. We scope a pilot off it.
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Talk to engineering
A 30-minute deep-dive on the platform with our engineering lead. For technical buyers who want to see the platform internals before a pilot scopes.