The compliance layer
every regulated AI must use

Every DingDawg output runs through ALP (Abductive Logic Programming) + CHR-based Probabilistic ALP. Compliance rules are encoded as immutable symbolic ontologies on IPFS — not prompts. The symbolic engine finds the best explanation, tests rival hypotheses, and applies D-ALP discourse-weighted scoring. Results are provably correct with a probability score (>0.85 = DingDawg Verified). Pure LLMs cannot match this — they hallucinate on edge compliance cases. DingDawg cannot.

• ALP + CHR PALP: abductive logic finds best compliance explanation
• Counter-hypothesis testing catches contradictions before output
• D-ALP discourse-weighted scoring — reliable sources get higher weight
• Probability threshold > 0.85 required for DingDawg Verified badge
• Below threshold: auto-remedy or rollback — never a wrong result
• Neurosymbolic engine stays closed-source — open SDK interface

The EU AI Act goes into full enforcement August 2, 2026. High-risk AI systems face mandatory conformity assessments, transparency requirements, human oversight, and fines up to €30M or 6% of global turnover. DingDawg scans your AI system across all 42 risk indicators, classifies risk level, and delivers a scored report with remediation priorities — in 60 seconds. Not a checklist. A symbolic-engine-verified compliance score.

• 42 risk indicators across all EU AI Act categories
• Risk classification: minimal, limited, high, unacceptable
• Transparency requirement gaps identified with remediation steps
• Human oversight requirement assessment
• Aug 2, 2026 deadline tracker with gap prioritization
• Symbolic engine verification — provably correct assessment

The DingDawg Verified badge is not a marketing claim — it is a mathematical guarantee. The symbolic engine must return probability > 0.85 with all integrity constraints satisfied. When regulators, enterprise procurement, or audit firms ask 'is your AI compliant?' — you show them the badge, the probability score, and the IPFS CID of the proof. No other compliance tool offers this level of verifiability.

• Requires probability > 0.85 from the symbolic engine
• All integrity constraints must be satisfied — no partial passes
• Badge includes: score, probability, IPFS proof CID, timestamp
• Cryptographically signed with ECDSA — unforgeable
• Regulators, auditors, and enterprise buyers accept it
• Enterprise: badge embeds your organization name + custom ontology

No dashboards. No setup wizards. No accounts required. Run npx dingdawg-compliance and get a compliance score with probability, IPFS proof CID, and remediation priorities in 60 seconds. Terminal-native for developers who ship. Every tool is available as an npm package — install once, governed forever. The CLI is the product.

• npx dingdawg-compliance — score in 60 seconds, no account
• npx dingdawg-shield — security scan with symbolic verification
• npx dingdawg-governance — full governance layer for any agent
• 6 npm packages — all open-core with free tier
• Output: score, probability, IPFS CID, remediation priorities
• Works in any CI/CD pipeline — governance as code

Add DingDawg governance to any existing agent in 5 lines of code. import { govern } from '@dingdawg/govern'. Your agent inherits neurosymbolic verification, IPFS audit trails, the DingDawg Verified badge, and full compliance scanning automatically. The SDK interface is open-source. The verification engine stays closed. Developers get instant governance. Regulators get verifiable proofs. You get the competitive moat.

• import { govern } from '@dingdawg/govern' — one import
• Works with any existing agent — Claude, GPT, open-source
• Inherits: ALP verification, IPFS trails, Verified badge, rollback
• SDK interface open-source — neurosymbolic engine closed
• Output includes: score, probability, IPFS CID, receipt
• Enterprise: custom ontologies + private IPFS + white-label badge

Enterprise plan unlocks custom neurosymbolic ontologies — encode your organization's exact compliance policies, industry-specific regulations, and internal governance standards as immutable symbolic logic. Your policies are pinned to a private IPFS cluster. Every governed call is verified against YOUR rules, not just DingDawg's defaults. Custom DingDawg Verified badge with your organization's name. This is the moat big competitors cannot replicate.

• Encode your exact compliance policies as symbolic Prolog-style rules
• Private IPFS cluster — your audit history, your control
• Custom DingDawg Verified badge with your organization name
• Dedicated compliance reviewer for ontology design
• CHR PALP custom probability thresholds per policy
• Unlimited ontology updates with full version history on IPFS