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Onyx vs Raghim AI

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan
Onyx has one; Raghim AI prices on request
Public API
Both have one
Higher Trust score
Onyx — 91 vs 68 for Raghim AI
Best fit
Onyx: IT teams that must keep documents and embeddings inside their own network · Raghim AI: Regulated organizations such as finance, healthcare or government-adjacent teams that need enterprise chatbots on infrastructure they control
Platforms
Onyx: Web, Chrome extension, Slack app · Raghim AI: Web

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

Side by side

FactOnyxRaghim AI
CategoryEnterprise SearchEnterprise Search
Pricing modelFreemiumContact
Starts at$20/seat/mo—
Public APIYesYes
Trust score91 / 10068 / 100
PlatformsWeb, Chrome extension, Slack app, APIWeb, API
CompanyZoomRaghim AI
Launched2023—
Last verifiedOct 2, 2026Sep 1, 2026

What our research says

Onyx

Onyx fits teams that want a ChatGPT-style workspace over their own documents without sending the index to a vendor cloud. The free community edition covers chat, connectors and agents; SSO and role-based access sit behind the paid tiers. The Zoom deal is new, so check how the self-hosted and open-source promises are written into your contract.

Pros

  • Permission-aware retrieval inherits access rules from each connected source
  • Runs self-hosted, including air-gapped, with a free MIT-licensed community edition
  • Works with many LLM providers, including local models
  • Connects to 40+ apps and exposes agents, MCP tools and developer APIs

Cons

  • SSO, role-based access and white-labeling require a paid or enterprise licence; the repository carries a separate enterprise licence for those directories
  • Self-hosting a search index and connectors needs real infrastructure and upkeep
  • Product roadmap now depends on a new parent company, and pricing for larger deployments is not published

Raghim AI

Raghim's whole pitch is control over data location: everything from document RAG to natural-language database queries can run self-hosted via Docker rather than only in someone else's cloud, which matters for regulated industries that can't send data off premises. That flexibility comes at the cost of a heavier setup than a plug-and-play SaaS chatbot, and there is no visible pricing to gauge cost until you talk to the vendor.

Pros

  • Genuine self-hosted deployment option via Docker, not just a hosted-only product with a compliance label
  • Combines document RAG, SQL and database natural-language queries, and voice AI in one platform instead of three separate tools
  • Enterprise controls such as RBAC, audit logging, retention policies and IP allowlisting are built in rather than bolted on

Cons

  • No published pricing, so budgeting requires a sales conversation
  • Self-hosted deployment requires real infrastructure and Docker operations work
  • Independent, non-vendor reviews of real-world deployments are hard to find

Which one fits

Choose Onyx if you need

  • IT teams that must keep documents and embeddings inside their own network
  • Companies that want one chat and search interface across Slack, Drive, Confluence and GitHub
  • Teams that want to swap LLM providers without changing the interface

Choose Raghim AI if you need

  • Regulated organizations such as finance, healthcare or government-adjacent teams that need enterprise chatbots on infrastructure they control
  • Teams wanting natural-language access to production databases alongside document Q&A in one platform

Onyx vs Raghim AI: the questions people ask

Is Onyx cheaper than Raghim AI?

Onyx starts at $20/seat/mo; Raghim AI prices on request, so a quote is the only way to compare.

Does Onyx or Raghim AI have a free tier?

Onyx has a free tier; Raghim AI prices on request.

Which has a public API, Onyx or Raghim AI?

Both ship a public API, so either can be built on; the fact table above shows the platforms each one runs on.

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