{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_visual-electric","slug":"visual-electric","name":"Visual Electric","type":"product","url":"https://visualelectric.com","page_url":"https://unfragile.ai/visual-electric","categories":["image-generation"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_visual-electric__cap_0","uri":"capability://image.visual.text.to.image.generation.with.professional.quality.optimization","name":"text-to-image generation with professional quality optimization","description":"Generates images from natural language prompts using a diffusion-based model pipeline optimized for design-quality outputs. The system likely implements prompt engineering preprocessing and quality-tuning parameters to prioritize aesthetic coherence and professional usability over novelty or artistic extremism. Generation is executed server-side with optimized inference serving, enabling fast iteration cycles suitable for rapid prototyping workflows.","intents":["Generate multiple design variations from a single creative brief for client presentation","Rapidly prototype visual concepts during early-stage design exploration","Create placeholder assets for mockups without waiting for external designer availability","Iterate on image composition and style parameters within a single design session"],"best_for":["Design studios and creative agencies evaluating AI image tools","Solo designers and freelancers needing fast asset generation without subscription lock-in","Product teams prototyping UI/UX mockups with AI-generated imagery"],"limitations":["Output quality and stylistic control likely inferior to Midjourney's iterative refinement or Stable Diffusion's fine-tuning capabilities","No documented support for advanced techniques like LoRA fine-tuning or custom model training","Generation speed and quality may degrade under high concurrent load due to smaller infrastructure footprint vs competitors"],"requires":["Active internet connection for cloud-based inference","Freemium account or paid subscription tier","Modern web browser with WebGL support for preview rendering"],"input_types":["natural language text prompts","optional style/aesthetic parameters"],"output_types":["PNG/JPEG images at configurable resolutions","metadata including generation parameters and seed values"],"categories":["image-visual","creative-tools"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_visual-electric__cap_1","uri":"capability://image.visual.batch.image.generation.with.queue.management","name":"batch image generation with queue management","description":"Supports generating multiple images in sequence or parallel batches through a job queue system, enabling designers to explore multiple creative directions simultaneously. The system likely implements request batching with priority queuing and asynchronous processing, allowing users to submit multiple generation jobs and retrieve results as they complete without blocking the UI.","intents":["Generate 5-10 variations of a design concept with different prompts in one workflow","Submit multiple image generation jobs and check results later without waiting","Explore multiple creative directions in parallel for client presentation options","Batch-process similar prompts with parameter variations to find optimal settings"],"best_for":["Design teams running multiple concurrent creative explorations","Agencies preparing presentation decks with diverse visual options","Designers optimizing prompt parameters through systematic variation testing"],"limitations":["Batch processing likely subject to rate limits or queue prioritization based on subscription tier","No documented support for conditional branching or dynamic prompt generation within batches","Results retrieval may require polling or webhook integration rather than native streaming"],"requires":["Freemium or paid account with batch processing quota","API access or web interface supporting multi-job submission","Sufficient account credits or subscription tier for parallel job execution"],"input_types":["array of text prompts","batch configuration parameters (resolution, style, count)"],"output_types":["array of generated images with metadata","job status tracking and completion timestamps"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_visual-electric__cap_2","uri":"capability://image.visual.professional.interface.with.design.team.collaboration.features","name":"professional interface with design-team collaboration features","description":"Provides a web-based UI specifically architected for design teams rather than general consumers, with features like project organization, generation history, and likely team workspace management. The interface prioritizes rapid iteration workflows with quick access to generation parameters, result comparison tools, and export functionality optimized for design handoff to production systems.","intents":["Organize generated images by project or client for easy retrieval and version control","Compare multiple generated variations side-by-side to select best options","Share generation results and parameters with team members for feedback","Export images with metadata and generation parameters for design documentation"],"best_for":["Design studios and creative agencies with 2-10 person teams","In-house design teams at product companies evaluating AI workflows","Freelance designers wanting professional asset organization without complex DAM setup"],"limitations":["Team collaboration features likely limited compared to enterprise design platforms (Figma, Adobe Creative Cloud)","No documented integration with version control systems or design handoff workflows","Workspace management and permission controls probably basic compared to dedicated team collaboration tools"],"requires":["Web browser with modern JavaScript support","Team account or workspace creation capability","Optional: SSO/SAML integration for enterprise deployments (unknown if supported)"],"input_types":["UI interactions for project creation and image organization","metadata tagging and annotation"],"output_types":["organized project views with generation history","exportable image collections with metadata"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_visual-electric__cap_3","uri":"capability://image.visual.fast.inference.serving.with.generation.speed.optimization","name":"fast inference serving with generation speed optimization","description":"Implements optimized inference serving infrastructure that prioritizes generation latency, likely using techniques like model quantization, batched inference, and GPU resource allocation to deliver results in seconds rather than minutes. The backend likely uses a load-balanced serving architecture with caching of common prompts or embeddings to reduce redundant computation.","intents":["Generate design variations within seconds to maintain creative flow during brainstorming","Rapidly iterate on prompt parameters without waiting for long generation cycles","Run multiple generation jobs in quick succession for A/B testing design directions","Deliver results fast enough for real-time client presentation and feedback loops"],"best_for":["Design professionals who need sub-10-second generation times for interactive workflows","Agencies running time-sensitive client presentations requiring rapid iteration","Teams prototyping multiple design directions in compressed timelines"],"limitations":["Fast inference likely achieved through model compression or quantization, potentially reducing output quality vs full-precision models","Speed optimization may limit advanced features like high-resolution generation or complex style control","Performance may degrade during peak usage periods if infrastructure is undersized relative to demand"],"requires":["Stable internet connection with sufficient bandwidth for image downloads","Freemium or paid account with generation quota","Modern GPU-accelerated browser for local preview rendering (optional)"],"input_types":["text prompts with optional style parameters"],"output_types":["generated images delivered within 5-15 seconds","generation metadata including latency and model version"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_visual-electric__cap_4","uri":"capability://image.visual.freemium.access.model.with.usage.based.quota.system","name":"freemium access model with usage-based quota system","description":"Implements a freemium pricing model that provides limited free generation credits to new users, reducing friction for design professionals evaluating the tool before committing to paid tiers. The quota system likely tracks usage per user account with daily or monthly reset cycles, and paid tiers unlock higher generation limits, priority queue access, and potentially advanced features like higher resolution or faster generation.","intents":["Evaluate Visual Electric's output quality and workflow fit before committing to paid subscription","Generate occasional design assets without ongoing subscription cost","Scale usage incrementally as team adoption grows, paying only for additional capacity","Test AI image generation workflows with minimal financial risk or platform lock-in"],"best_for":["Solo designers and small agencies with variable image generation needs","Design teams evaluating multiple AI tools before selecting primary platform","Organizations with budget constraints wanting to pilot AI workflows before enterprise commitment"],"limitations":["Free tier likely provides limited monthly quota (unknown exact numbers), requiring upgrade for production use","Paid tiers may have unclear pricing structure or feature differentiation vs competitors","No documented information on credit rollover, refund policies, or long-term pricing stability"],"requires":["Free account creation with email verification","Optional: payment method for paid tier upgrade","Compliance with terms of service regarding acceptable use and commercial licensing"],"input_types":["account creation and tier selection"],"output_types":["usage quota tracking and billing statements","tier-specific feature access and generation limits"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_visual-electric__cap_5","uri":"capability://image.visual.image.export.with.design.ready.format.support","name":"image export with design-ready format support","description":"Provides export functionality optimized for design workflows, supporting multiple image formats (PNG, JPEG, potentially WebP) and resolutions suitable for different use cases (web, print, presentation). The export pipeline likely includes metadata preservation (generation parameters, seed values) and optional integration with design tools or cloud storage for seamless handoff to production workflows.","intents":["Export generated images in formats compatible with design tools (Figma, Adobe Creative Suite)","Download high-resolution versions suitable for print production or large-format display","Preserve generation parameters and seed values for reproducibility and documentation","Batch export multiple images with consistent settings for project delivery"],"best_for":["Design professionals integrating AI-generated assets into production workflows","Agencies delivering design assets to clients with specific format requirements","Teams documenting design decisions and generation parameters for future reference"],"limitations":["Export resolution likely capped at standard web/print sizes (unknown maximum), potentially insufficient for large-format applications","No documented support for vector export or AI-powered upscaling to higher resolutions","Batch export may have file size or quantity limits based on subscription tier"],"requires":["Generated image available in user account","Sufficient storage quota or cloud integration for export destination","Design tool compatibility for imported formats (Figma, Adobe, etc.)"],"input_types":["generated image selection","export format and resolution parameters"],"output_types":["PNG/JPEG files at configurable resolutions","optional metadata JSON with generation parameters","cloud storage integration (Google Drive, Dropbox, etc. — unknown if supported)"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_visual-electric__cap_6","uri":"capability://image.visual.prompt.parameter.control.with.style.and.aesthetic.customization","name":"prompt parameter control with style and aesthetic customization","description":"Exposes generation parameters allowing users to control style, aesthetic direction, and composition through structured input fields or advanced prompt syntax. The system likely implements a parameter schema that maps user-friendly controls (style presets, composition guides, color palettes) to underlying model conditioning inputs, enabling non-technical designers to achieve consistent visual direction without deep prompt engineering knowledge.","intents":["Apply consistent visual style across multiple generated images for brand coherence","Control composition, color palette, and aesthetic direction without complex prompt engineering","Create style presets for rapid iteration on similar design concepts","Fine-tune generation parameters to match specific design briefs or brand guidelines"],"best_for":["Design professionals wanting style control without learning complex prompt engineering","Brand teams maintaining visual consistency across AI-generated assets","Designers exploring specific aesthetic directions (minimalist, photorealistic, illustration, etc.)"],"limitations":["Parameter control likely more limited than Stable Diffusion's fine-tuning or LoRA capabilities","No documented support for custom model training or style transfer from reference images","Advanced parameters may require technical knowledge or experimentation to use effectively"],"requires":["Understanding of basic design terminology (style, composition, color)","Optional: reference images or style guides for parameter tuning"],"input_types":["text prompt","style presets or parameter selections","optional: numeric parameters for fine-tuning (guidance scale, seed, etc.)"],"output_types":["generated images with applied style and aesthetic parameters","parameter metadata for reproducibility"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_visual-electric__cap_7","uri":"capability://image.visual.generation.history.and.result.tracking.with.metadata.preservation","name":"generation history and result tracking with metadata preservation","description":"Maintains a persistent history of all generated images per user account, storing generation parameters, timestamps, and seed values to enable reproducibility and design iteration tracking. The system likely implements a database-backed history view with filtering and search capabilities, allowing designers to revisit previous generations, compare variations, and understand the evolution of design concepts across sessions.","intents":["Retrieve and reproduce previous image generations using stored seed values and parameters","Track design iteration history to understand creative evolution and decision rationale","Compare multiple generations from different sessions to select best variations","Document design process and generation parameters for client handoff or team review"],"best_for":["Design teams needing to track and reproduce AI-generated assets across projects","Designers iterating on concepts over multiple sessions and wanting to revisit previous directions","Agencies documenting design decisions and generation parameters for client deliverables"],"limitations":["History storage likely limited by account tier or storage quota, with older generations potentially purged","No documented support for version control integration or collaborative history tracking across team members","Search and filtering capabilities probably basic compared to dedicated asset management systems"],"requires":["User account with persistent storage","Sufficient account storage quota for history retention","Optional: export functionality for archival or backup"],"input_types":["generation parameters and results stored automatically"],"output_types":["history view with filterable generation records","metadata including prompts, parameters, timestamps, and seed values","reproducibility data for re-generating previous images"],"categories":["image-visual","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Active internet connection for cloud-based inference","Freemium account or paid subscription tier","Modern web browser with WebGL support for preview rendering","Freemium or paid account with batch processing quota","API access or web interface supporting multi-job submission","Sufficient account credits or subscription tier for parallel job execution","Web browser with modern JavaScript support","Team account or workspace creation capability","Optional: SSO/SAML integration for enterprise deployments (unknown if supported)","Stable internet connection with sufficient bandwidth for image downloads"],"failure_modes":["Output quality and stylistic control likely inferior to Midjourney's iterative refinement or Stable Diffusion's fine-tuning capabilities","No documented support for advanced techniques like LoRA fine-tuning or custom model training","Generation speed and quality may degrade under high concurrent load due to smaller infrastructure footprint vs competitors","Batch processing likely subject to rate limits or queue prioritization based on subscription tier","No documented support for conditional branching or dynamic prompt generation within batches","Results retrieval may require polling or webhook integration rather than native streaming","Team collaboration features likely limited compared to enterprise design platforms (Figma, Adobe Creative Cloud)","No documented integration with version control systems or design handoff workflows","Workspace management and permission controls probably basic compared to dedicated team collaboration tools","Fast inference likely achieved through model compression or quantization, potentially reducing output quality vs full-precision models","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.117Z","last_scraped_at":"2026-04-05T13:23:42.559Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=visual-electric","compare_url":"https://unfragile.ai/compare?artifact=visual-electric"}},"signature":"9qxJ4NHErnmr1zlEzOOaG6Jyn6z1dlPKNoUqteL3Snu8/vlOQdejNR7OkDImOjzUgfG7kOO+X6oRBZmxcvULCw==","signedAt":"2026-06-20T09:11:55.429Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/visual-electric","artifact":"https://unfragile.ai/visual-electric","verify":"https://unfragile.ai/api/v1/verify?slug=visual-electric","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}