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Flora Flow Example: Creating with prompt

Preview this Flora user flow: Creating with prompt. Explore the opening screens.

Bud logo
Bud | Your AI Worker screen
Bud | Your AI Worker screen
Bud | Your AI Worker screen

User starts in AI chat workspace and progresses through empty project states to browser preview with deployment menu while chatting with Bud agent

User enters natural language description on create page to generate a new product via AI, with manual configuration option available

User configures AI assistant nodes on workflow canvas with prompt and model selection, then compares multiple prompts side-by-side on prompt canvas

User engages with AI assistant on support page to resolve issues, browse documentation, or contact sales while viewing platform updates

User starts from empty agents list, uses floating AI chat to request agent creation, then encounters out-of-credits paywall and error state

Uploading a video file via modal on the home dashboard and waiting for AI to generate magic clips

User opens AI chat drawer or overlay to converse with Workspace admin agent for deal room analysis, recommendations, metrics review, and rewrite planning

User chats with AI assistant to generate and refine an e-commerce storefront while previewing live results on the right pane

User creates database table indexes from an empty list view using manual creation or AI-generated suggestions in Appwrite

Beside logo

Chatting with AI

4 screens

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FromBeside
Ask Beside AI - Beside screen
Ask Beside AI - Beside screen
Ask Beside AI - Beside screen

User opens AI chat interface to query notes and calls then prompts assistant to draft follow-up SMS messages while seeing identity verification banners

HeyGen logo
HeyGen - Avatar screen
HeyGen - Avatar screen
HeyGen - Avatar screen

User enters descriptive prompt in modal to generate preview and select custom AI voices

Exa logo

Running AI agent

4 screens

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FromExa
Playground | Exa API screen
Playground | Exa API screen
Playground | Exa API screen

Configure research query and JSON output schema in agent playground then monitor live execution trace to structured data output

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