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OGAC vs Open-Kritt

OGAC and Open-Kritt 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.

OGAC

OGAC

The Console gives banks, insurers, and other regulated enterprises one place to connect data sources, route traffic through observed model gateways, build apps in plain language without code, and produce signed, cited audit trails — all governed by rules set once and inherited everywhere. Prompt-injection screening, PII filtering, and policy checks run in the pipe before a call leaves the system. Live scoring watches for drift against a golden set and traces every result to its source. A run can pause for human sign-off, then continue on its own. The self-hosted, AGPL-3.0 path means your data and models stay on your servers — but operating that infrastructure is on your team, not the vendor.

Open-Kritt

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.

AttributeOGACOpen-Kritt
PricingPaidPaid
Free trialNoNo
Open sourceNoYes
Has APIYesNo
Self-hosted optionYesYes
PlatformsCloud, on-prem, self-hostedLocal, GitHub, self-hosted
Released2026-07
Pros
  • Rules set once and inherited by every app and agent built on the platform, so compliance teams stop chasing developers to re-implement guardrails each time a new use case ships.
  • Prompt-injection, PII, and policy screening run inside the pipeline before a call exits the system, which means a blocked request never reaches an external model or a downstream user.
  • Live drift scoring and source tracing on every run, so when a regulator asks what the model said and why, the answer is already signed and cited rather than reconstructed from scattered logs.
  • AGPL-3.0 open-source with full self-host support, so your model traffic and data stay on your servers and swapping a gateway or model provider is a config change rather than a renegotiated contract.
  • Human oversight pauses built into agent runs, so a workflow that touches a sensitive decision stops for sign-off before continuing — without requiring a custom integration to wire that step in.
  • 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.
Cons
  • The plain-language app builder targets business teams describing clear, bounded use cases — workflows that require conditional branching across multiple decision points force developer involvement, at which point teams are maintaining both the no-code layer and custom logic sitting outside it.
  • Self-hosting under AGPL-3.0 puts infrastructure operation, scaling, and security patching on your team; organizations without dedicated platform engineering capacity report that the operational overhead shifts cost from licensing to headcount, and some move to a managed alternative when internal bandwidth runs out.
  • The vendor's public pricing page does not list usage tiers or per-seat costs, so teams cannot estimate total cost of ownership without booking a demo — a blocking issue for procurement processes that require a written quote before evaluation can proceed.
  • 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.
Bottom line

Open-Kritt is open source; only OGAC exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between OGAC and Open-Kritt?

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

Is OGAC better than Open-Kritt?

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.

OGAC vs Open-Kritt: which should I pick?

Pick OGAC if its pricing model, openness, or platform fit matches your constraints; pick Open-Kritt otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.