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Kadmo vs Nimbalyst

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

Kadmo compared with Nimbalyst
DetailKadmo logo KadmoNimbalyst logo Nimbalyst
What it doesSovereign agentic engineering platform that runs AI coding agents with roles, playbooks and gates on your infrastructure Agent wiki and visual workspace for Claude Code, Codex and other AI coding agents
StageNot given Not given
FoundedNot given Not given
Based inDE Not given
Pricing modelNot given Freemium
PricingTrial: Free for 15 days with €5 credit on Kadmo's LLM provider. Business: Flat monthly rate per workspace, unlimited seats, 100K runs per month, up to 100 agents on your cloud. Enterprise: Custom pricing with flexible terms, support for more than 100 agents by agreement. Model pricing: Claude Haiku Free: Nimbalyst app and personal wiki. Wiki Teams: $20 per user per month or $200 per user per year (currently free during beta).
Key features
  • Multiple specialized agent roles (Engineer, Product Manager, QA, Security, Documentation, Skill Discovery, Website Builder)
  • Playbook-based workflows with gates at every handoff
  • Integration with existing tools (Jira, Linear, GitHub, GitLab, Slack, Notion, Teams)
  • Code execution on customer's own cloud infrastructure (AWS, Google Cloud, Hetzner)
  • Support for multiple AI models (Claude, GPT, Gemini, Codex) with no vendor lock-in
  • GDPR-compliant with data residency enforcement
  • Full transcript and audit logs for every agent run, replayable anytime
  • Governance controls including role-based access, approval policies, and spend budgets
  • Transparent token cost reporting per ticket
  • WYSIWYG markdown editor with AI-assisted editing
  • Red/green inline diffs for AI changes approval
  • Visual editors for mockups, diagrams, and drawings
  • Parallel agent session management
  • File and session linking
  • Persistent searchable session history
  • Pull request review in Developer Mode
  • MCP server support
What makes it different
  • Agents run on your infrastructure with no code leaving your perimeter, maintaining full data sovereignty and GDPR compliance
  • No vendor lock-in with support for any AI model; switch models as better ones ship
  • Integrates seamlessly into existing tools and workflows without requiring installations or migrations
  • Live in days with transparent cost accounting per run in real tokens
  • Agents write the wiki as they work, eliminating manual documentation
  • Open source and local-first: your data stays on your machine
  • Built by Evergage founders who scaled to $250M ARR
  • One unified workspace instead of multiple disconnected tools
Community votes00
DR (Domain Rating by Ahrefs)26 +1 (up) since last check45 −5 (down) since last check
Trust Flow (Majestic)1115
Citation Flow (Majestic)2540
Referring domains (Majestic)6709

4 details filled in for both companies.

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