The things we talk about

Producing images from text descriptions or reference images using diffusion or transformer-based models. Euryka's Imaginations brings 10+ image models — Flux, Stable Diffusion, Midjourney via Sparks — into one interface with shared brand context, image-to-image remixing, and inpaint editing.

Coordinating multiple AI models — text, image, video, voice — from a single workspace so creative teams can move between modalities without breaking context. Includes routing the right prompt to the right model, persisting brand state across calls, and aggregating outputs into one project.

Generating short video clips from text prompts, images, or other videos using models like Kling, Veo, Sora, and Runway. Euryka exposes seven video models in one place so creative teams can match the right model to the right shot without juggling separate accounts.

Optimising websites to be cited by AI answer engines — Google AI Overviews, Perplexity, ChatGPT search — rather than only ranked in classical search results. AEO requires structured data, answer-shaped content, and entity binding so AI engines can reliably identify the page as a citation source.

The consistent personality, tone, and language a brand uses across every channel and asset. In AI workflows, brand voice is encoded as guardrails the model checks against — preventing off-brand outputs at generation time rather than catching them in review.

Claude is a family of large language models developed by Anthropic, first released in March 2023. Trained using Constitutional AI for improved safety and alignment, Claude models are available in three sizes—Haiku, Sonnet, and Opus—and support text, coding, reasoning, and image-input tasks.

The discipline of feeding AI models persistent, structured context — brand guidelines, approved assets, audience knowledge, prior outputs — so every generation stays on-brand without manual re-briefing. Successor to prompt engineering: less about crafting one perfect prompt, more about maintaining the state the model reasons against.

AI that produces new content — text, images, video, audio, code — rather than just classifying or analysing. Generative AI is the umbrella category Euryka operates inside; the platform makes it usable for marketing teams by adding brand context, governance, and multi-model orchestration on top.

A type of AI trained on vast amounts of text that can read, write, and reason in natural language. LLMs power Euryka's Threads, Docs, and Sparks — GPT, Claude, Gemini, and others all sit behind the workspace, routed transparently based on the task.

Model Context Protocol (MCP) is an open standard introduced by Anthropic in November 2024 that provides a universal interface for connecting AI systems, such as large language models, to external data sources, tools, and services using JSON-RPC 2.0 messaging, replacing fragmented custom integrations with a single interoperable protocol.

AI models that work across multiple input and output types — text, image, audio, video — within a single pipeline. Multimodal AI is what lets Euryka turn a written brief into an image, then a voiceover, then a video, all carrying the same brand context end to end.

The practice of crafting input prompts that get reliable, high-quality outputs from AI models. Foundational discipline that Euryka content positions as the predecessor to context engineering — useful for one-off tasks, insufficient for sustained brand work where the same instructions get repeated to every model.

Retrieval-augmented generation combines a retriever — vector search over an indexed corpus — with a large language model so answers are grounded in cited source documents instead of the model's training data. RAG cuts hallucinations and lets answers stay current as your corpus updates.

Synthesising speech in a specific person's voice using a short audio sample as reference. Powers Euryka's Voiceovers product — record a voice once, generate unlimited voiceovers in that voice across languages, all carrying the original speaker's tone and timbre.