Orygo AI

The interesting claim on OrygoAI's site is not the model, it is the division of labour. Most AI support tools sell you a builder and wish you luck; OrygoAI sells Agent OS (knowledge base, natural-language instructions, integrations, A/B testing, analytics, error monitoring, cost logs) plus deep training it performs itself and then optimises weekly against revenue per visitor. That second half is the product. A wrong recommendation on a product page is a lost sale, and the vendor's own framing — self-service chatbots fail as volumes grow because they are not properly trained — is the argument for paying someone else to own that work. Strengths. Breadth of the selling surface: conversational search, product Q&A, recommendations, comparisons, bundles and cross-sell, one-to-one coupons, proactive on-site messages, cart and order creation, booking and subscription management, then post-chat automations and CRM updates. A/B testing between agent versions is unusual at this layer and is how you keep the better performer instead of guessing. Cost transparency is genuinely better than most: request-level logs, credits per reply disclosed as 0.5–1.5 depending on model, and unused Starter credits refundable within 30 days on a first purchase. The human-handoff path is specified — smart escalations, human takeover, hot-lead tagging — rather than hand-waved. Weaknesses and open questions. Pricing is usage-based, so your bill is a function of traffic and how chatty your visitors are; a 4–6 exchange conversation is cheap, a long pre-sales discovery session is not, and the site does not publish a hard monthly ceiling. Credits per reply vary by LLM, which means the same conversation can cost three times as much depending on routing decisions you do not control. Implementation is one-to-one with the vendor — that is the source of quality and also the lock-in; your agent's competence lives partly in their team, not your dashboard. And the performance figures (+10–15%, +3–5%) are vendor-reported averages across 20+ brands, not a controlled study you can audit. Where it fits. Online sellers with enough traffic that a 10–15% conversion lift on the same visitors outperforms the €2,500/year floor plus credit spend, on a commerce stack the vendor supports, with a structured catalog and someone internally who can own the KPI. Travel and consumer-services businesses look well served by the booking and subscription features. Where it does not: low-traffic stores, catalogs that exist only as PDFs or in a founder's head, and teams who want to tune prompts themselves on a Tuesday afternoon. The seed framing of this as a support-deflection tool undersells what the current site sells — this is positioned first as a sales agent, with the helpdesk and escalation layer as the safety net.