Eidentic vs Open-Kritt

Eidentic 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.

Eidentic

The SDK centers on a temporal knowledge graph that tracks when facts were true, resolves contradictions, and consolidates between sessions — so the agent sharpens over time rather than accumulating noise. Durable runs, enforced cost ceilings, and CI-gated evals ship as part of the core, not as paid add-ons. The vendor benchmarks report 55.2% on LongMemEval versus 41.0% for full-context stuffing, and claims up to 39× fewer tokens per query. The gap shows up in support and long-running assistant workflows where session history compounds. At v0.1, the ecosystem is early — teams building anything outside the TypeScript path face a hard stop.

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.

Attribute	Eidentic	Open-Kritt
Pricing	Free	Paid
Free trial	No	No
Open source	Yes	Yes
Has API	Yes	No
Self-hosted option	Yes	Yes
Platforms	Node, Bun, Deno, Edge	Local, GitHub, self-hosted
Released	—	2026-07
Pros	Temporal knowledge graph tracks fact validity over time and resolves contradictions automatically, which means agents reasoning over months of sessions return accurate historical context instead of hallucinating stale or overwritten facts. Sleep-time consolidation reorganizes memory between sessions without prompt growth, so token costs stay flat as conversation history accumulates — the vendor cites up to 39× fewer tokens per query versus full-context retrieval. Enforced cost ceilings and CI-gated evals ship as core runtime features, which means you catch regressions and runaway spend in the build pipeline instead of discovering them in production billing. Provider-agnostic model and store configuration — OpenAI, Anthropic, Google, Mistral on the model side; SQLite, libSQL, Turso, Postgres, pgvector, Qdrant, LanceDB, Pinecone on the store side — so swapping backends is a constructor argument, not an architectural rewrite. Apache-2.0 license with no paid tier and a self-hosted path, which means the full feature set is available without a commercial dependency or a pricing conversation when you scale.	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 SDK is TypeScript-only. A Python, Go, or Java team hits a dead end at the npm install step — there is no polyglot client, no REST-only path that abstracts the language requirement, and no migration story. Those teams look at LangChain, LlamaIndex, or a framework with a language-agnostic API. At v0.1 with a thin community footprint and docs that the vendor describes as early, debugging non-obvious memory consolidation behavior — why a fact was superseded, why recall missed a session — produces limited guidance. Teams operating at scale with on-call SLA expectations will find the lack of managed support or a commercial support tier a blocking constraint. There is no visual workflow editor or low-code interface. Teams whose agent logic is owned by non-engineers, or whose approval process requires non-technical stakeholders to inspect and modify agent behavior, have no path forward without writing TypeScript — at which point they evaluate tools like Dify or Flowise instead.	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

Eidentic is free while Open-Kritt is paid; only Eidentic exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Eidentic and Open-Kritt?

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

Is Eidentic 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.