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imho.run vs Kognitos

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

imho.run compared with Kognitos
Detailimho.run logo imho.runKognitos logo Kognitos
What it doesFree Steam game recommender that ranks games against your library and what players are saying in reviews Not given
StageStartup Established
Founded2025 2020
Based inNot given US
Pricing modelFree Freemium
PricingNot given Free tier available to automate first process with no credit card required. Enterprise pricing is consumption-based, scaling with volume of automated transactions and complexity of agents rather than per-bot or per-user licensing.
Key features
  • Collaborative filtering recommendation algorithms
  • Review-mined vibe graph with 129,000+ edges
  • Steam Deck compatibility filtering
  • Hidden gem discovery
  • No login required for anchor mode
  • Daily catalogue refresh from Steam APIs
  • Transparency with reasons behind each recommendation
  • Analyzes 18 million+ player libraries
  • Hallucination-free AI automation through deterministic execution
  • English as Code for plain English programming of workflows
  • Patented Time Machine runtime with pause-patch-resume capability
  • 200+ pre-built enterprise integrations
  • Builder Agent for no-code workflow creation
  • Symbolic Executor for deterministic execution
  • Resolution Agent for automatic exception handling
  • Context Graph for auditable business decisions
  • Role-based access control and audit governance
What makes it different
  • Recommendation rankings based on what you actually play, not popularity
  • No ads, sponsors, or revenue-based ranking
  • Built by a single independent developer with no investors
  • Gameplay vibes extracted from actual player reviews
  • Private data handling with no personal data sales
  • Deterministic execution with zero hallucinations, unlike probabilistic AI systems
  • English as Code lets business users build automation without developers
  • 12x lower maintenance cost compared to traditional RPA
  • Consumption-based pricing that scales with transaction volume, not per-bot licensing
  • Production deployment in 14-30 days for single workflows
Community votes00
DR (Domain Rating by Ahrefs)1 +1 (up) since last check56 −1 (down) since last check
Trust Flow (Majestic)011
Citation Flow (Majestic)2040
Referring domains (Majestic)9692

5 details filled in for both companies.

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