Yanerva develops AI communication frameworks that enhance clarity between human intent, software context, and AI output while ensuring customer content remains local by default and under your control.
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Enterprise teams are heavily investing in AI-enabled software, but unreliable outputs can lead to workflow confusion, privacy concerns, and adoption risks. Yanerva develops AI communication infrastructure that aligns human intent, application state, and AI-generated guidance, making AI support clearer, more controlled, and easier to trust.
AI often delivers generic responses. Without structured application context, guidance can become unsupported or disconnected from the workflow in front of the user, quickly reducing trust. As AI becomes more deeply integrated into software, guidance must remain grounded, context-aware, and honest about its limits.
Many AI assistants rely on external processing that may send sensitive interface content outside the customer environment. Yanerva’s privacy-first architecture keeps customer screen content, sensitive application content, model responses, and direct end-user identity out of Yanerva’s managed operational telemetry by default.
When users struggle to understand complex software workflows, support demand increases. Context-aware guidance can reduce confusion at the point of use, improve the user experience, and preserve support capacity.
Silk Screen is Yanerva’s first product, designed as a drop-in managed SDK runtime. It serves as an embeddable guidance layer, enabling software to explain itself in context while keeping customer screen content local by default.
Silk Screen functions as a translation layer for interface guidance. Applications provide a screen region, relevant context, and a rendering surface; Silk Screen transforms visible interface information into structured guidance output. It operates between your application and an AI model, organizing the context supplied to the model, enforcing response boundaries, and producing guidance grounded in the visible application state and configured workflow.
Contact YanervaInterprets visible application state, page context, and configured workflow locally. That information is then structured into a format the AI can use more reliably, reducing unsupported inference.
You define the rules. Silk Screen’s communication infrastructure enforces them. The AI operates within configured boundaries rather than improvising beyond the available context.
No screen data is transmitted to Yanerva or external AI services by default. Silk Screen is designed for environments where sensitive interface content must remain within the customer environment.
Application state, visible interface context, and workflow position are captured and interpreted within your environment. Customer screen content remains local during this process.
Your configured context rules and guidance boundaries are applied. The AI is guided by structured context and deterministic constraints rather than relying on open-ended prompting alone.
The user receives targeted, context-sensitive guidance within the software experience, ensuring it is practical, securely bounded, and aligned with the visible context and configured workflow.
Silk Screen keeps everything local, processing application context directly on your device. Your screen content remains private and isn't shared with external AI services unless you choose otherwise. You control what the AI sees and says and where it offers help.
Contact YanervaWe capture and process your app's context locally, ensuring your screen content stays with you unless you opt for a different setup.
You define the context boundaries, guidance rules, and AI response constraints. Yanerva does not receive customer screen content, prompts, model responses, or direct end-user identity by default.
AI output is shaped by structured context rules and configured boundaries. Users receive application-specific guidance designed to reduce unsupported or out-of-context responses.
Structured AI guidance can help wherever software complexity creates friction between users and successful outcomes.
Help engineers reach proficiency faster when learning complex internal platforms, tools, and APIs.
Reduce avoidable support demand by giving users structured, in-context guidance at the point of confusion.
Deliver contextual guidance inside your product while keeping customer screen content out of third-party AI services by default.
Help users understand multi-step processes and conditional logic without forcing them to leave the workflow to search through documentation.
Teach users how to apply your product within their specific workflows, complementing documentation with guidance at the point of use.
Support environments where customer screen content and sensitive application data cannot be sent to external AI services.
Yanerva aims to partner with innovative software teams to build privacy-first AI guidance layers that help users understand complex applications in real time. Let's discover if we're the ideal fit for your goals.