Choose Alhena AI when
Ecommerce brands wanting a shopping assistant trained on the product catalogue, with revenue and merchandising features alongside support.
RAUM AI vs Alhena AI
Alhena or a general-purpose website chatbot on your own AI account?
Alhena is built specifically for ecommerce and trains on your product catalogue. RAUM Chat is not commerce-specialised; it answers from your written procedures and the systems you connect, on the AI provider account you already pay.
Last reviewed: September 2, 2026
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Decision guide
Which approach fits best?
Choose RAUM AI when
Teams whose website questions are answered from documented policy and connected systems rather than from a product catalogue.
Neutral considerations
What to validate before choosing
Commerce specialisation
Alhena describes training on your product catalogue, reviews, help centre and past chats. If product discovery and merchandising are the job, that specialisation is the point and RAUM does not replicate it.
Included volumes
Both publish per-conversation tiers, but the included volumes differ by roughly an order of magnitude. Compare at your own expected volume rather than at the entry tier.
Model ownership
Alhena does not document customer-supplied model keys. RAUM requires you to bring your own provider account, which is more setup and keeps the model contract yours.
Side by side
RAUM AI vs Alhena AI
Competitor cells use the official sources listed below. “Not publicly documented” means we did not find a current official statement; it is not a claim that the capability is absent.
| Decision area | Alhena AI | RAUM AI |
|---|---|---|
| Metering unit | Per credit, consumed when the AI resolves or assists an interaction[1] | Per conversation, charged once per conversation id |
| Published monthly rate | $239 for 200, $599 for 550 and $1,199 for 1,200 conversations, with lower annual rates[1] | $49 for 500, $149 for 2,000 and $399 for 6,000 conversations |
| Free tier | Free plan listed at 25 conversations a month[1] | No free tier on the chat product |
| Knowledge grounding | Trained on product catalogue, reviews, help centre and past customer chats[2] | Written procedures and approved help content, plus connected read-only systems |
| AI-provider credentials | Not publicly documented as customer-supplied keys | You connect your own OpenAI, Anthropic or Google account |
| Commerce features | Positioned around shopping assistance and revenue, not support alone[2] | Support answering only; no merchandising or recommendation features |
| Live web knowledge | Confirm crawling, exact live-page access, and freshness behavior in the cited product documentation | Website crawling, exact live-page lookups, dynamic URL variants, and durable last-good snapshots |
| Workflow review controls | Confirm current builder, approval, review, and simulation controls in the cited documentation | Guided connected workflows, per-finding AI Review, ticket directives, and Simulation Mode |
| Zendesk onboarding | Product-specific installation and setup | Guided Marketplace installation with automatic webhook and trigger setup |
In depth
What the choice actually turns on
Two different products wearing the same widget
A shopping assistant and a support chatbot look identical on the page and are judged by different things. A shopping assistant is measured by whether it helped someone buy; a support chatbot is measured by whether it answered correctly and knew when to stop. RAUM is built for the second and has no merchandising features at all, so if the bulk of your website conversations are product discovery, a commerce-specialised product is the better tool and this comparison should end there.
Compare at your volume, not at the entry tier
Per-conversation tiers are the easiest pricing model to misread, because the headline number is set by whatever volume the vendor chose to anchor on. The only comparison that means anything is your own expected monthly conversations priced against every relevant tier, including the overage rate once you exceed one. Add the model spend on any bring-your-own-key product — it is genuinely at cost, but at cost is not zero, and a comparison that omits it is not honest.
Setup and migration
A practical evaluation sequence
- 1
Separate the two jobs: helping someone choose a product, and answering a question about an order or a policy. RAUM is built for the second.
- 2
Take your expected monthly conversation volume and price both at that number, not at the advertised entry tier.
- 3
Connect the order or account system you want the bot to read as an approved read-only source before comparing answer quality.
FAQ
Questions teams ask
Can RAUM recommend products?
No, and it is not trying to. There are no merchandising, recommendation or catalogue features. It answers support questions from your documented procedures and the systems you let it read. If product discovery is the job, buy something built for it.
Can it look up an order?
Yes, if you connect the system that holds them. Read-only sources run automatically; anything that would change an order — a cancellation, a return — is a separate class of action that requires explicit approval before it executes.
How do the included volumes compare?
They differ by roughly an order of magnitude at similar price points, so the entry tiers are not comparable. Price both at your own expected monthly volume, and include the overage rate for the month you go over.
Do I pay RAUM for model usage?
No. You connect your own provider account and they bill you directly at your rate. Budget for it as a separate line — it is at cost, not free.
Evidence
Official sources
- [1] Alhena AI pricing
Plan names, monthly and annual rates, conversation allowances and the credit definition; verify at purchase.
- [2] Hallucination-Free AI Powered Shopping Assistant | Alhena AI
Product positioning, channel list and the knowledge sources it trains on.
Product packaging and availability can change. Recheck these official pages and obtain a vendor quote before making a purchase decision.
Keep exploring
Related resources
Evaluate RAUM AI with your real Zendesk workflows
Install from the Marketplace, connect a supported provider, and verify representative tickets without sending customer replies.
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