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Dify vs AT0M

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Dify compared with AT0M
DetailDifyAT0M
What it doesThe Platform for Production-Ready Agentic Workflows A private System One Decision AI that runs locally
StageEstablished Beta
FoundedNot given Not given
Based inUS Not given
Pricing modelfreemium Not given
PricingSandbox (free), Professional ($590/year per workspace), Team ($1,590/year per workspace), and custom Enterprise pricing. Message credits included monthly. Not given
Key features
  • Workflow Studio - Visual builder for agentic workflows
  • Agent builder - Create agents with skills, tools, and knowledge
  • Knowledge Pipeline - Prepare searchable knowledge bases
  • Marketplace - Explore tools, models, and integrations
  • Multi-deployment options - Cloud, VPC, or self-hosted
  • Publish and monitor - Ship as app, API, or tool
  • Visual execution path - Turn prompt logic into visible workflows
  • Unified workspace - Bring AI stack into one platform
  • Enterprise features - SSO, SAML, RBAC, audit logs
  • Non-autoregressive with no free text generation
  • Multi-question call support in a single forward pass
  • Bounded output within supplied candidate set
  • Calibrated probabilities without temperature fitting
  • Local inference as a Rust binary executable
  • Deterministic inference with reproducible results
  • Support for choice, score, and yes-no decision types
  • CPU, Apple Metal, and CUDA hardware support
  • Trainable on your own decisions locally
What makes it different
  • No-code platform that democratizes AI agent development for beginners
  • Deploy from prototype to production without rebuilding the stack
  • Unified workspace for agents, workflows, and knowledge pipelines
  • Enterprise-ready with SSO, RBAC, audit logs, and compliance certifications
  • Bounded output structurally prevents off-list answers, unlike generative models
  • Calibration by construction without temperature fitting enables direct threshold-based automation
  • Local executable keeps inference in your perimeter with no per-decision API dependency
  • Cost structure based on electricity, not output tokens
  • Deterministic inference with identical results across repeated requests
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)78 no change since last check22 no change since last check
Trust Flow (Majestic)330
Citation Flow (Majestic)523
Referring domains (Majestic)63381

4 details filled in for both companies.

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