Made with AICreative power without privacy worry: why communications leaders should care about AI back-end processes
Mikko Oksanen
CEO & Co-Founder
Summary
- The communications leadership challenge: AI is expected to speed up everyday communications work, but uncertainty about privacy, data leaking to models, and EU regulation slows adoption.
Two hard expectations meet on the communications director's and CCO's desk: on one side, the organisation expects more results and speed from communications with fewer resources; on the other, responsibility for brand reputation, copyright, and privacy weighs more heavily than ever.
When teams adopt AI tools on their own, uncontrolled shadow use appears quickly. Nobody knows exactly where a draft press release, strategy summary, or crisis background memo is sent, or how that data is used.
We have renewed Lyyli's back-end architecture to remove that tension. Communicators' day-to-day work should stay smooth and inspiring, while the governance layer behind it must meet the strictest security criteria.
01Freedom to create, confidence to govern
In everyday communications work, AI is at its best when it removes routine friction: turning an expert interview into a blog post, versioning a release into channel-specific social posts, and keeping brand voice consistent regardless of who writes.
Fear of what happens to submitted information must not block that work. With our latest platform update, communications teams and security leadership can rely on these principles:
- Prompts are not retained by model providers: Enforced Zero Data Retention (ZDR) means that when a communicator drafts text, Anthropic, Google Vertex AI, and OpenAI do not retain the prompt after the request is processed.
- Customer content is not used to train models: Content your organisation produces, expert thinking, and strategic messages stay under your control.
- Lyyli stores conversations to deliver the service: Workspace drafts and conversation history remain under your organisation's control in an EU-focused environment — separate from the provider's ZDR processing.
- Clear processing region by choice: The interface shows directly where each language-model request is processed. Claude and Gemini models run in the EU; GPT models are processed in a global environment.
02Proof of value: what does this bring to the communications team's day?
Text generation alone is now a baseline benefit. Real value comes from workflow control, brand protection, and a shared view of work across the team.
- No more silos and lost ideas: When all material from idea to approval is handled in one protected environment, drafts do not disappear into email threads or separate chat channels.
- The right language model for the right task: The team does not have to guess which tool fits best. Lyyli offers nine leading language models side by side, so different model outputs can be compared at a glance.
- Audit trail and commenting: Drafts can go through approval rounds, and experts can comment via secure links without a separate login hassle.
03A secure communications platform is a strategic choice
A communications professional's job is not to worry about API routing or log structures. The team's job is to clarify the message, build trust, and turn strategy into action.
Behind the scenes, we ensure the platform meets enterprise requirements, follows a strict Zero Data Retention line, and offers full transparency into processing chains.
Lyyli is built for secure organisational use. Customer data is protected with encryption, access rights, workspace isolation, and logging. Data is processed only to deliver the service, in line with GDPR and agreed processing terms.
See detailed technical descriptions and current annexes at lyyli.ai/trust. We will publish a separate article for technical decision-makers in procurement and evaluation.
See how Lyyli supports communication directors and communications operations in practice.
Want to see the governance model in your own team?
Book a demo. We will walk through how your communications team can use AI safely without shadow tools.
- •ZDR and model-specific regions in practice
- •Nine language models in one workflow
- •Approvals, audit trail, and brand voice




