This is for how code is written today
Joplin lives in the AI context window. Your compliance rules are already there — no plugins, no wrappers, no extra work.
The audit trail is written directly into the code. Developers don't do anything extra.
Checks every diff against Anthropic, Google, OpenAI, and Mistral usage policies before evaluation. Blocks policy violations at the gate.
Tier 1 Constitution, Tier 2 Rules, Tier 3 Guidelines — each with its own authority level, approval workflow, and escalation path.
Generate SOC 2 Type II and EU AI Act conformity packages on demand. Evidence automatically gathered from your audit trail.
REST API endpoint accepts any git diff and returns a structured JSON verdict. Drop it into GitHub Actions, GitLab CI, or Jenkins in minutes.
Joplin lives in the context window — no extension needed. Your rules are already there when Copilot, Claude, or any AI assistant generates code.
Hash-chained audit trail. Every evaluation is cryptographically linked to the previous one — deletion or modification is detectable.
Scribe tickets route rule change requests to the right approver — CIO, Lead, or Developer — with email notifications and one-click approval.
Every other governance platform was designed for a world where humans write code and AI is a model you deploy. Joplin was designed for where we actually are.
OneTrust and Credo AI require a GRC team to run them. Joplin is a git hook — it runs whether or not anyone is paying attention to the governance program that week. There is no dashboard to check, no quarterly review to schedule. Every commit is governed automatically.
Every other platform requires someone to go generate a report. Joplin's hash-chained audit record exists automatically at every commit. By the time an auditor asks the question, the evidence is already there — cryptographically linked, tamper-evident, and timestamped to the second.
No other platform controls what rules the AI sees before it generates code. They are all downstream of that moment — evaluating outputs, monitoring runtime, classifying models. Joplin is upstream: it governs what enters the context window on every evaluation call. The AI cannot violate a rule it has been given.
An enterprise with OneTrust, IBM watsonx, and IndyKite still has a gap at the git commit. Joplin closes it without replacing anything they already paid for. That is a much easier conversation than "rip and replace" — and it means Joplin can sell into shops that already have a governance stack.
Most teams run Joplin against Claude or Gemini and never think about it. But if you're in defense, healthcare, or a jurisdiction with strict data residency requirements, flip one environment variable and the entire evaluation pipeline runs locally on Ollama — your code, your rules, your audit trail, all behind your firewall. IBM watsonx, OneTrust, and IndyKite are cloud-only by architecture. Joplin gives you the choice.
Every other governance tool was designed for a world where humans write code and AI is a model you deploy.
Joplin was designed for the world we're actually in — where AI writes the code and humans review the commit.
"Show me every AI-assisted code change, the exact rules it was evaluated against, and the tamper-evident record that it was reviewed before it was committed."
EU AI Act Article 13. GDPR Article 22. SOC 2 CC6.1. This is what auditors will ask. Every governance platform on the market operates at the model or runtime layer — none of them see the git commit. That gap is Joplin's entire reason for existing.
| Capability | Credo AI | IBM watsonx | IndyKite | OneTrust | Joplin COS |
|---|---|---|---|---|---|
| Model bias & fairness assessment | ✓ | ✓ | — | ✓ | — |
| AI system inventory & risk classification | ✓ | ✓ | — | ✓ | — |
| Runtime agent & data access control | — | — | ✓ | ✓ | — |
| Executive dashboards & GRC reporting | ✓ | ✓ | — | ✓ | — |
| Git commit interception | ✗ | ✗ | ✗ | ✗ | ✓ |
| Diff evaluated against your rules | ✗ | ✗ | ✗ | ✗ | ✓ |
| Per-commit tamper-evident audit chain | ✗ | ✗ | ✗ | ✗ | ✓ |
| Context window governance | ✗ | ✗ | ✗ | ✗ | ✓ |
| Regulator-ready evidence packages | ✗ | ✗ | ✗ | ✗ | ✓ |
| Air-gapped capable | ✗ | ✗ | ✗ | ✗ | ✓ |
| Typical entry price | $30K–$150K+/yr | $38K+/yr | Enterprise only | $1.6K–$42K+/yr | $199/mo |
These platforms are your existing governance stack. Joplin is the missing layer.
Credo AI assesses your models. IBM watsonx monitors their runtime. IndyKite controls what agents access. OneTrust catalogs your AI systems. None of them see what Copilot, Cursor, or Claude Code writes into your codebase at the commit. Joplin does. Run them together — zero overlap.
Joplin loads your compliance rules into the AI context window. The AI already knows what's allowed.
No additional work needed.
Evaluated by Claude against real governance rules — live on AWS
Self-hosted on your own infrastructure. You bring your own Anthropic API key — AI evaluation costs go directly to Anthropic, no markup.
One HIPAA violation costs $50,000–$1.9M in fines. Joplin pays for itself on the first near-miss.
Joplin uses your Anthropic (or Google Gemini) API key for evaluations. AI costs go directly to the provider at their published rates — typically $0.01–0.03 per evaluation with Claude Sonnet. No usage markup, no surprise bills from us.
Joplin COS is available for enterprise teams. Get in touch to discuss your compliance requirements.
Request access