Sweden ships the games. AI search decides who gets played.

Frequently asked

• We ship English-first. Do we still need AI tools for non-native English game text?

  Yes — but for the secondary languages, not the master. Helpshift's Language AI FAQ Translation tool covers 74 languages with published 40-70% automation rates on tier-1 gaming tickets. The pattern that works for Swedish studios: English master copy stays human-written, AI handles the 10-15 language localisation pass on patch notes, support macros, and Steam page descriptions. Quality control is one bilingual reviewer per market, not a full translation desk.

• How does AI fit into F2P live-ops without breaking margins after ATT?

  Three places. Creative testing: AppsFlyer's 2024 report documents ~839 monthly creative variations per app at USD 100k+ spend, with playable ads converting 29x higher than static. AI-assisted variant generation is the only way to staff that volume below AAA budgets. LTV modelling: Unity Analytics and deltaDNA cite 200% retention lift and 40% revenue lift on real-time CRM personalisation. Support deflection: Helpshift's 40-70% automation range frees the human team for high-value escalations. None of these touch monetisation design directly, which is the right place to keep human judgement.

• How does community moderation work under the EU AI Act?

  Voice and text moderation tools (Modulate ToxMod, Microsoft Community Sift) sit inside the AI Act's general-purpose AI rules — they were already operating with audit logs and human-in-the-loop appeal paths before the Act. From 2 August 2026, Article 50 transparency adds an explicit obligation: when AI is making moderation decisions visible to players (mute, kick, chat filter), the system must be machine-readably identifiable as AI. Practically, this is a one-line change in the moderation message and a public policy page documenting the AI system. Areza writes both as part of the Voice Agent + Workflow Ops engagement.

• What about copyright on AI-generated assets?

  Two layers. Training-data provenance — Scenario.gg, Layer AI, and similar style-consistent tools train on team-uploaded reference sets, which keeps the IP chain inside the studio. Open-web models (Midjourney, Stable Diffusion base) have unresolved training-data exposure that publisher legal teams flag immediately. Output disclosure — EU AI Act Article 50 requires AI-generated content used in-game to be machine-readably marked. The practical answer for AA studios is: use in-house-trained models for production assets, keep open-web models for moodboards only, and document the asset provenance in the build-pipeline metadata from day one.

• We have a publisher relationship. Does Areza work inside that?

  Yes — alongside, not against. Publishers own platform marketing (Steam page, console-storefront placement, paid UA at scale) and contract terms protect that lane. Areza ships the studio-owned layer the publisher does not staff: studio website, AI-search citation infrastructure, employer-brand content, community ops automation, and post-launch support deflection. The typical AA engagement reviews publisher contract clauses for content-rights ownership before scoping; we have not yet hit a clause that blocks the work.

• How is Areza different from a Stockholm gaming agency or BPO like Keywords?

  Keywords Studios (which acquired Helpshift in 2024) is enterprise BPO — full-service localisation, QA, and player support priced for AAA. Stockholm gaming agencies cover events, press, and influencer ops. Areza is purpose-built for the AI-search and agentic-automation layer that sits below both: the parts of studio growth that are remote-first, English-language-first, and systems-engineering-shaped. The honest split — bring Keywords in for full BPO if you are AAA, hire a Stockholm gaming agency for events and press, bring Areza in for AI search, Foundation, Voice Agent, and Knowledge Bot work where the systems-first approach pays compounding returns at AA budgets.