{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_ai-interior-pro","slug":"ai-interior-pro","name":"AI Interior Pro","type":"product","url":"https://www.aiinteriorpro.com","page_url":"https://unfragile.ai/ai-interior-pro","categories":["image-generation"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_ai-interior-pro__cap_0","uri":"capability://image.visual.room.style.transformation.generation","name":"room-style-transformation-generation","description":"Generates photorealistic renderings of interior spaces in specified design styles by accepting user-uploaded room photos and style prompts, then applying diffusion-based image-to-image transformation with style conditioning. The system likely uses a vision encoder to understand spatial layout from the source image, embeds the style description as a text prompt, and iteratively refines the output through guided diffusion steps to maintain room geometry while applying aesthetic transformations.","intents":["visualize how my living room would look in a minimalist vs maximalist style without hiring a designer","generate multiple design direction options from a single room photo to compare aesthetics","explore color palettes and furniture arrangements before committing to purchases"],"best_for":["homeowners exploring design directions before professional consultation","renters wanting low-commitment visualization of design possibilities","interior design students prototyping mood boards rapidly"],"limitations":["output quality degrades significantly with poor source photo lighting, shadows, or extreme angles — AI struggles to infer true spatial dimensions from compromised input","generated designs ignore practical constraints like furniture scale, structural feasibility, electrical outlets, and load-bearing walls that professional designers account for","style prompts require specificity; vague requests like 'modern' produce generic outputs, while detailed prompts demand user design literacy","no awareness of material costs, availability, or real-world sourcing — generated designs may feature unavailable or prohibitively expensive pieces"],"requires":["image upload capability (JPEG/PNG format, minimum 512x512px recommended)","internet connection for cloud-based diffusion inference","modern browser with WebGL support for preview rendering"],"input_types":["image (room photograph)","text (style description or design direction)"],"output_types":["image (photorealistic room rendering)"],"categories":["image-visual","design-inspiration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-interior-pro__cap_1","uri":"capability://image.visual.multi.style.comparative.visualization","name":"multi-style-comparative-visualization","description":"Enables side-by-side or sequential generation of the same room in multiple design styles (minimalist, bohemian, industrial, maximalist, etc.) from a single source photo, allowing users to compare aesthetic outcomes. The implementation likely batches style prompts through the same image encoder and diffusion pipeline with different conditioning vectors, potentially caching the spatial understanding from the source image to reduce redundant computation across style variations.","intents":["compare how different design styles would work in my specific room before deciding on a direction","quickly generate a mood board showing 4-6 design alternatives from one photo","overcome design paralysis by seeing unexpected style combinations applied to my actual space"],"best_for":["indecisive homeowners needing visual comparison to make design commitments","interior designers presenting multiple options to clients without manual rendering","design enthusiasts exploring personal aesthetic preferences through rapid iteration"],"limitations":["batch generation increases API costs and processing time compared to single-style generation","user must manually compare outputs without built-in side-by-side diff tools or annotation features","style definitions are AI-interpreted from text descriptions, leading to inconsistent or unexpected interpretations of the same style across different rooms"],"requires":["single high-quality source image (well-lit, straight-on angle preferred)","ability to specify 3-6 distinct style names or descriptions","sufficient API quota or credits for multiple generation requests"],"input_types":["image (room photograph)","text array (multiple style descriptions)"],"output_types":["image array (multiple photorealistic renderings)"],"categories":["image-visual","design-inspiration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-interior-pro__cap_2","uri":"capability://image.visual.photo.quality.adaptive.rendering","name":"photo-quality-adaptive-rendering","description":"Analyzes source image quality metrics (lighting, focus, angle, resolution) and adapts the diffusion inference strategy to compensate for suboptimal input conditions. The system likely detects poor lighting, extreme angles, or low resolution and adjusts prompt weighting, inference steps, or applies preprocessing (denoising, perspective correction) before diffusion to improve output coherence despite source limitations.","intents":["get usable design visualizations even from my phone camera photo with poor lighting","understand how my room would look in a design style despite having only a low-quality source image","improve output quality without needing to retake professional photos of my space"],"best_for":["mobile-first users uploading casual smartphone photos","renters unable to take professional photos of their space","users wanting quick inspiration without photo preparation overhead"],"limitations":["adaptive rendering cannot fully recover spatial information from severely compromised photos (extreme angles, heavy shadows, motion blur)","preprocessing steps add 1-3 seconds latency per image before diffusion begins","quality improvements are heuristic-based; some poor-quality inputs still produce mediocre outputs regardless of adaptation"],"requires":["image with minimum 320x320px resolution (lower resolution triggers aggressive preprocessing)","room must be identifiable despite lighting/angle issues"],"input_types":["image (room photograph, any quality level)"],"output_types":["image (improved-quality rendering)"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-interior-pro__cap_3","uri":"capability://text.generation.language.design.style.prompt.interpretation","name":"design-style-prompt-interpretation","description":"Translates user-provided design style names and descriptions into structured conditioning signals for the diffusion model, mapping natural language style terms (minimalist, bohemian, industrial, etc.) to learned style embeddings or prompt templates. The system likely maintains a curated taxonomy of interior design styles with associated visual attributes, color palettes, material preferences, and furniture characteristics that are encoded into the diffusion conditioning to guide generation.","intents":["describe a design style in my own words and have the AI understand and apply it to my room","explore named design styles (minimalist, maximalist, scandinavian, etc.) without needing design terminology knowledge","mix style descriptors (e.g., 'minimalist with warm tones') to create hybrid aesthetic directions"],"best_for":["non-designers wanting to explore styles without learning design vocabulary","users experimenting with style combinations and hybrid aesthetics","homeowners translating Pinterest inspiration into actionable design directions"],"limitations":["style interpretation is AI-driven and inconsistent — the same style name may produce different outputs across different rooms or model versions","vague style descriptions (e.g., 'modern', 'nice') produce generic outputs; specificity is required for coherent results","no feedback loop to refine style interpretation — users cannot teach the system their personal style preferences","style taxonomy is fixed and may not include emerging or niche design movements"],"requires":["text input describing desired style (minimum 2-3 words recommended)","familiarity with at least one design style name or ability to describe aesthetic preferences"],"input_types":["text (style name or description)"],"output_types":["embedding or conditioning signal (internal to diffusion model)"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-interior-pro__cap_4","uri":"capability://automation.workflow.freemium.access.with.quota.management","name":"freemium-access-with-quota-management","description":"Implements a freemium business model with tiered access where free users receive limited monthly generation quotas (e.g., 5-10 renders/month) and premium subscribers unlock unlimited generations. The system tracks per-user generation counts, enforces quota limits at the API gateway, and provides clear feedback on remaining credits or quota status, likely using a simple counter-based system tied to user accounts.","intents":["try the tool with a few design explorations before committing to a paid subscription","generate unlimited design variations once I'm convinced of the tool's value","understand exactly how many generations I have remaining and plan my usage accordingly"],"best_for":["budget-conscious homeowners wanting risk-free exploration","casual users who need only occasional design inspiration","power users and professionals who justify unlimited access through frequent use"],"limitations":["free tier quota is restrictive enough to encourage upgrade but may frustrate users mid-project","quota resets on fixed schedule (monthly) rather than rolling window, creating artificial scarcity at month-end","no quota sharing or family plans — each user has independent quota","free tier may receive lower priority in inference queue, resulting in slower generation times"],"requires":["user account creation (email or social login)","no payment method required for free tier access"],"input_types":["user identity (account)"],"output_types":["quota status (remaining generations, reset date)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-interior-pro__cap_5","uri":"capability://image.visual.room.geometry.preservation.during.transformation","name":"room-geometry-preservation-during-transformation","description":"Maintains spatial layout, room dimensions, and architectural features (walls, windows, doors, ceiling height) from the source image while applying style transformations, preventing the AI from hallucinating new walls or distorting the room's footprint. This likely uses spatial masking or inpainting techniques where the diffusion model is constrained to modify only furniture, colors, and decorative elements while preserving structural geometry detected from the source image.","intents":["see how my room would look in a new style without the AI inventing new walls or changing the layout","trust that the generated design respects my actual room's dimensions and architectural constraints","avoid designs that are spatially impossible in my specific room configuration"],"best_for":["users wanting realistic design previews that respect their actual room constraints","homeowners unable to renovate structural elements and needing designs within current layout","designers presenting options that are actually feasible in the client's space"],"limitations":["geometry preservation is imperfect — windows or doors may shift slightly or be partially obscured by generated furniture","source image must clearly show room boundaries and architectural features; cluttered or obscured layouts confuse geometry detection","preservation constraints may limit design creativity by preventing furniture arrangements that would require structural changes","extreme perspective angles in source photos reduce geometry preservation accuracy"],"requires":["source image with clear view of room boundaries and architectural features","room must be identifiable as a distinct space (not open-concept or ambiguous)"],"input_types":["image (room photograph with visible architecture)"],"output_types":["image (rendering with preserved room geometry)"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-interior-pro__cap_6","uri":"capability://memory.knowledge.design.inspiration.mood.board.curation","name":"design-inspiration-mood-board-curation","description":"Curates and presents generated design renderings as a visual mood board, organizing multiple style variations in a gallery or carousel interface that allows users to save, compare, and export their favorite designs. The system likely stores generated images in a user-specific gallery, provides tagging or favoriting mechanisms, and enables batch export or sharing of selected designs.","intents":["save my favorite design variations to reference later when shopping for furniture","organize generated designs by style or room area to build a cohesive mood board","share my favorite AI-generated designs with a designer or family members for feedback"],"best_for":["homeowners building design direction before furniture shopping","users collaborating with partners or family on design decisions","design enthusiasts collecting inspiration across multiple projects"],"limitations":["saved designs are static images without editable parameters — users cannot adjust colors or furniture after generation","no annotation or note-taking features to explain design choices or capture specific product links","gallery storage is cloud-based and subject to data retention policies; designs may be deleted after account inactivity","sharing is limited to image export; no collaborative editing or real-time feedback features"],"requires":["user account with persistent storage","ability to tag or favorite generated images"],"input_types":["image (generated design rendering)"],"output_types":["image collection (mood board), shareable link or exported image file"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_ai-interior-pro__cap_7","uri":"capability://safety.moderation.design.feasibility.awareness.limitations","name":"design-feasibility-awareness-limitations","description":"The system acknowledges but does NOT implement practical design constraints such as furniture scale, structural feasibility, budget considerations, material availability, or building codes. Generated designs may feature furniture that doesn't fit the space, materials that are unavailable or prohibitively expensive, or layouts that violate building codes — the AI has no awareness of these real-world constraints.","intents":["understand that AI-generated designs are inspiration, not actionable plans","recognize which design elements from generated outputs are feasible vs aspirational","know when to consult a professional designer to validate feasibility"],"best_for":["users understanding AI limitations and using outputs as mood inspiration only","homeowners planning to consult professionals before implementing designs","design students using the tool for ideation, not final specifications"],"limitations":["generated furniture may be incorrectly scaled relative to the room — a sofa might appear to fit but actually be 2x the room width","designs may feature materials or finishes that are unavailable, discontinued, or cost 10x the user's budget","layouts may violate building codes (e.g., blocking emergency exits, insufficient clearance)","no awareness of utility placement (electrical outlets, HVAC, plumbing) that constrains furniture arrangement","color recommendations may not account for existing fixtures (kitchen cabinets, flooring) that cannot be changed"],"requires":["user understanding that AI outputs are inspirational, not prescriptive"],"input_types":["none (this is a capability gap, not a feature)"],"output_types":["none (this is a capability gap, not a feature)"],"categories":["safety-moderation","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["image upload capability (JPEG/PNG format, minimum 512x512px recommended)","internet connection for cloud-based diffusion inference","modern browser with WebGL support for preview rendering","single high-quality source image (well-lit, straight-on angle preferred)","ability to specify 3-6 distinct style names or descriptions","sufficient API quota or credits for multiple generation requests","image with minimum 320x320px resolution (lower resolution triggers aggressive preprocessing)","room must be identifiable despite lighting/angle issues","text input describing desired style (minimum 2-3 words recommended)","familiarity with at least one design style name or ability to describe aesthetic preferences"],"failure_modes":["output quality degrades significantly with poor source photo lighting, shadows, or extreme angles — AI struggles to infer true spatial dimensions from compromised input","generated designs ignore practical constraints like furniture scale, structural feasibility, electrical outlets, and load-bearing walls that professional designers account for","style prompts require specificity; vague requests like 'modern' produce generic outputs, while detailed prompts demand user design literacy","no awareness of material costs, availability, or real-world sourcing — generated designs may feature unavailable or prohibitively expensive pieces","batch generation increases API costs and processing time compared to single-style generation","user must manually compare outputs without built-in side-by-side diff tools or annotation features","style definitions are AI-interpreted from text descriptions, leading to inconsistent or unexpected interpretations of the same style across different rooms","adaptive rendering cannot fully recover spatial information from severely compromised photos (extreme angles, heavy shadows, motion blur)","preprocessing steps add 1-3 seconds latency per image before diffusion begins","quality improvements are heuristic-based; some poor-quality inputs still produce mediocre outputs regardless of adaptation","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":"2026-05-24T12:16:29.132Z","last_scraped_at":"2026-04-05T13:23:42.562Z","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=ai-interior-pro","compare_url":"https://unfragile.ai/compare?artifact=ai-interior-pro"}},"signature":"feU2UD8D461n33SqBUN/Vm0mz2LItvQpma+DNqKGm9t0gTxZrBvFa32AZ9FzA28A5aONUqH9Xmylf/WcIg2FCg==","signedAt":"2026-06-22T06:41:00.994Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/ai-interior-pro","artifact":"https://unfragile.ai/ai-interior-pro","verify":"https://unfragile.ai/api/v1/verify?slug=ai-interior-pro","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"}}