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Agnt vs Eidentic

Agnt and Eidentic 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.

Agnt

Agnt

AGNT is a local-first agent operating system built around an AGI loop: the agent executes a step, evaluates the result, and re-plans before moving forward — without you steering each decision. Persistent memory and skill layers mean context survives across sessions, not just within a single run. The visual workflow designer handles repeatable paths; goal-mode hands the agent an objective and lets it figure out the steps. Self-hosted deployment with Docker keeps data on your own infrastructure, which matters when your legal team has opinions about where prompts and outputs live. The custom license — not OSI-standard — is the detail that stops procurement at some organizations before the first demo.

Eidentic

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.

AttributeAgntEidentic
PricingPaidFree
Price$0 or $333/year per additional user for hosted version
Free trialNoNo
Open sourceYesYes
Has APIYesYes
Self-hosted optionYesYes
PlatformsDesktop (Windows, macOS, Linux), Docker, Kubernetes, headless server, VPS, homelab, Raspberry PiNode, Bun, Deno, Edge
Pros
  • AGI loop (execute → evaluate → re-plan) means the agent adapts when a step returns an unexpected result, so you aren't rebuilding the workflow every time real data doesn't match the demo assumption.
  • Persistent memory across sessions, so an agent working a multi-step task over hours or days carries context forward — without this, every run starts from zero and you hand-manage state yourself.
  • Local-first Docker deployment with no execution-based billing, which means compliance-sensitive teams can run agents on internal data without renegotiating data processing agreements or watching a cost meter.
  • Goal-mode lets you set an objective and let the agent sequence its own steps, so you aren't manually building every branch for tasks where the path depends on intermediate results.
  • Plugin and subagent architecture allows parallel delegation, so work that can happen simultaneously doesn't queue behind a single-threaded pipeline.
  • 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.
Cons
  • The license is a custom non-OSI-standard document — not MIT, Apache, or GPL. Teams at enterprises or funded startups with formal open-source review processes cannot deploy to production until legal clears it, and that process adds weeks to any timeline. Some teams skip the review entirely and move to a competitor with a standard license.
  • Community support is thin: a few hundred stars and a handful of open issues means when you hit an edge case in the re-planning loop or a plugin integration, there is precious little in forums or Stack Overflow to guide you. You are reading source code.
  • The visual workflow designer handles linear and moderately branched paths well; deeply conditional logic — branching based on what the third or fourth agent returned — pushes against what a canvas can express cleanly. Teams building that complexity end up extending with code outside the visual layer, at which point they are maintaining two systems.
  • 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.
Bottom line

Agnt is paid while Eidentic is free. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Agnt and Eidentic?

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

Is Agnt better than Eidentic?

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.

Agnt vs Eidentic: which should I pick?

Pick Agnt if its pricing model, openness, or platform fit matches your constraints; pick Eidentic 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.