Open-Kritt vs Patina

Open-Kritt and Patina are both agent frameworks tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Open-Kritt

The tool runs parallel AI agents across a codebase, so vulnerability discovery that would serialize into hours on a single-context scan distributes across concurrent analysis threads. It targets security researchers and bug bounty teams who need to sweep repositories at scale, not review a function at a time. Self-hosting is supported under AGPL-3.0, which means your code and findings never leave your infrastructure — a requirement for any org with compliance constraints. The open-source core is inspectable and forkable, but managed scans are a paid-only feature, so teams that want the hosted workflow face a significant spend threshold. The page describes GitHub integration as a first-class path, making it a practical fit for teams already running security workflows inside existing CI infrastructure.

Patina

Orbit wraps each agent task in a bounded loop: the agent works, validation runs (tests, lint, type checks), and the task only closes when the checks pass. Every loop leaves structured JSON artifacts — what the agent returned, how it scored against a rubric, and a human-readable recommendation to accept, retry, or stop. This makes agent runs auditable after the fact, not just observable in the moment. The ceiling appears when your project needs multi-agent coordination or a hosted execution layer — Orbit is deliberately narrow, self-hosted only, and ships no managed runtime.

Attribute	Open-Kritt	Patina
Pricing	Paid	Free
Free trial	No	No
Open source	Yes	Yes
Has API	No	No
Self-hosted option	Yes	Yes
Platforms	Local, GitHub, self-hosted	Python (via pip install), local execution, CLI
Released	2026-07	—
Pros	Parallel agent analysis across large codebases, so security researchers are not bottlenecked by single-context limits that cause coverage gaps on repositories too large for one model pass. AGPL-3.0 open-source license with self-hosting support, which means organizations with compliance requirements can audit the tool's behavior and keep all code and findings on their own infrastructure rather than routing through a third-party service. Direct GitHub repository integration, so teams can point the tool at existing repos without building a separate code ingestion or preprocessing step. Support for Codex and Claude Code model backends, so teams can align the analysis engine with the model their organization already has access to or trusts for security-sensitive tasks. Inspectable agent orchestration code under an open license, which means a security team can verify exactly what the agents are executing — a requirement that opaque SaaS tools cannot satisfy.	Validation gates block task closure until tests, lint, and type checks pass, so agents cannot self-report success on work that would fail your CI pipeline. Four structured artifacts per run (agent output, rubric evaluation, review recommendation, and progress log), which means audit trails exist by default instead of requiring you to reconstruct what happened from logs. Dependency-ordered backlog selection keeps each loop focused on one task at a time, so agents do not skip prerequisites or work on tasks whose dependencies are not yet verified. Agent-neutral adapter contract lets you swap Claude, Codex, Cursor, or any JSON-speaking CLI behind the same harness, so you compare agents on identical tasks with structured artifacts instead of anecdotes. MIT licensed and fully self-hosted, so teams with on-premise requirements or external platform restrictions can run the full harness without a managed dependency.
Cons	Managed scans are a paid-only feature with a spend threshold the validator context confirms is substantial; independent researchers and small bug bounty teams operating on limited budgets hit this wall immediately and are forced to self-host, which shifts the burden of infrastructure provisioning, scaling, and maintenance entirely onto the team. Self-hosting the agent infrastructure requires operational capacity that security research teams — typically focused on findings, not DevOps — often lack; teams without a dedicated infrastructure engineer end up spending sprint time on setup and uptime instead of auditing, and those teams frequently abandon self-hosted options for managed security tooling that absorbs that operational cost. No API is available per the tool's current documentation, which means teams that want to embed Kritt.ai's analysis into an existing CI/CD pipeline or trigger scans programmatically from another system face a hard integration ceiling; teams requiring API-driven automation switch to tools with exposed endpoints.	Orbit handles one task per loop; there is no mechanism for running agents in parallel or coordinating handoffs between agents. Teams whose workflows require concurrent agent execution build a separate scheduling layer on top — at which point they are maintaining two systems. The harness ships no hosted runtime, no API, and no managed execution environment. Teams that want cloud-hosted agent scheduling or need to trigger runs from external CI systems without standing up their own infrastructure will move to a platform that provides those primitives. The adapter and demo ecosystem is early-stage and contribution-dependent. Teams integrating a coding agent that lacks an existing adapter write and maintain the adapter themselves, which adds setup cost before the first validated loop runs.

Bottom line

Open-Kritt is paid while Patina is free. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Open-Kritt and Patina?

Open-Kritt is Paid and open source, while Patina is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Open-Kritt better than Patina?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.