Mnml AI - Architecture AI Render Tools

What is Mnml AI?

mnml.ai (pronounced minimal) is an AI rendering platform focused on architecture and interiors. Upload a rough image or sketch and the system generates multiple visualization styles—day/night, CGI/realistic, ink/watercolor—without the usual lighting/material tweaking you’d do in traditional 3D software. Architizer singled it out as a top AI tool for stylizing architectural images, specifically for transforming rough inputs into varied render styles.

mnml.ai is offered as both a web app and a developer API. The API exposes dedicated endpoints—/exterior, /interior, /imagine-ai, /style/transfer, /virtual-staging-ai, /sketch-to-img, /ai-eraser, /upscale, /inpaint, /video-ai, /prompt-generator, plus status/credits routes—so teams can automate render pipelines in their own products.

Mnml AI Key features

• Architecture‑specific toolset: Exterior AI, Interior AI, Imagine AI (text‑to‑render), Style Transfer, Render Enhancer, Virtual Staging, Sketch‑to‑Image, AI Eraser, 4K Upscaler, Inpainting, Video AI, Prompt Generator. Each has a documented API endpoint and parameters (see Tutorial section).
• Mixture of Experts (MoE) model routing for exteriors, interiors, masterplans, landscapes, plans, virtual staging, and edits—automatically picking the right “expert” for your input.
• Geometry preservation controls (e.g., geometry_input, “Precise” vs “Creative” modes) and style selectors to keep the original massing while exploring finishes/lighting.
• Exact Render & Flexibility workflow in the web app to preserve materials/geometry or allow broader exploration (think “lock it down” vs “let it riff”).
• From concept to animation: short videos from a reference image + prompt via Video AI.
• Professional post‑process: Style Transfer, 4K upscaling, AI Eraser (masking remove), and Inpainting (remove/add elements) to finish images without round‑tripping to other tools.
• Status & credit endpoints so teams can monitor jobs and manage usage at scale.

Who is using Mnml AI?

• Architecture & interior studios using it for quick design alternatives and presentation‑ready imagery. The company positions the platform specifically for these workflows.
• Visualization professionals who want to stylize rough shots/white renders from Lumion, V‑Ray, Enscape, Corona, etc., using a render enhancer pipeline.
• Real estate & staging teams creating furnished imagery from empty rooms via Virtual Staging AI.
• Students & educators, supported with education pricing/discounts.
• Developers & product teams integrating mnml.ai’s Architecture & Interior Design API into internal tools and client‑facing apps.

Mnml AI Pricing (as of September 22, 2025)

Web app subscriptions (Lemon Squeezy store listing):

• Basic $19/month (also listed $190/year)
• Pro $39/month (also listed $390/year)
• Expert $79/month (also listed $790/year)
• Studio $199/month
• One‑time credits/top‑ups are available (e.g., $49 pack).
  Enterprise/API bulk credit packs are also listed. Always check the store for current offerings.

API (credit packs)

• Examples on the API site include 100 credits for $29, 500 credits for $49, 1,000 credits for $99, 2,500 credits for $249 (1 credit ≈ one design generation; check docs for per‑feature costs).

Education: 30% discount for students/educators (with an .edu or equivalent).

Pricing changes over time—verify on mnml.ai before purchasing.

What makes Mnml AI unique?

1. Built specifically for AEC (architecture, interiors, landscape). The feature set and defaults are tailored to architectural massing, elevations, rooms, and site views—not just general image gen.
2. MoE (Mixture of Experts) routing selects architecture‑aware “experts” (exterior, interior, masterplan/landscape, plans, virtual staging, edit) to improve fidelity.
3. Control over fidelity vs. creativity via Exact Render/Flexibility and parameters like geometry_input, letting you keep the original model intact when needed.
4. Production finishing tools (Upscaler, Inpaint, Eraser, Style Transfer) inside the same platform reduce app‑hopping.
5. Speed + workflow tutorials (multi‑camera iterations, render enhancement pipelines) frequently showcased by the team.

Mnml AI Pros and cons

Pros

• Fast iteration from rough inputs to polished images.
• AEC‑aware controls for geometry preservation and style.
• Complete pipeline (stylize → enhance → up-res → inpaint/erase) in one place + API automation.
• Education discount eases adoption for studios with interns/academia.
• Positive practitioner reviews about usability and speed (independent round‑ups).

Cons

• Precise geometry editing is still limited compared with plugin‑based tools (e.g., Veras) that manipulate scene geometry—some practitioners note dialing in client‑ready results can take trial and error.
• Credit accounting across many tools can be confusing at first (different endpoints may bill different credits—e.g., Video AI, Virtual Staging).
• Marketing claims (e.g., native resolution) should be tested within your pipeline to ensure they meet your board/print specs.

Hands‑on tutorial: Using every mnml.ai tool (web app + API)

Below is a practical, end‑to‑end guide. First, the web workflow (designer‑friendly). Then API endpoints (for automation/integration).

A) Web app setup

1. Create an account and pick a plan or credits.
2. (Optional) Apply education discount if eligible.
3. Get familiar with mnml’s Exact Render (locks geometry/materials) vs Flexibility slider (lets the AI explore). You’ll see this language in mnml’s own beginner guides.
4. For multi‑camera iterations in the same space, mnml has a demonstrated workflow (create → pick tool → upload 3D shot → choose room/camera views).
5. If you already have a draft from Lumion/V‑Ray/Enscape/Corona, try Render Enhancer to quickly polish the look.

B) Web tools—what to use and when

• Exterior AI — Upload a facade/elevation or massing to re‑render in different styles (day/night, CGI/realistic, weathered, etc.). Use Exact Render for technical reviews; Flexible for exploration.
  Tip: Start with a clean, full‑frame shot of the building and keep the horizon straight for best results.
• Interior AI — 1‑click room re‑renders; helpful for trying furniture/material options fast. Use Precise to preserve layout; raise geometry preservation for technical fidelity.
• Imagine AI (text‑to‑render) — No input image needed; write a prompt (“double‑height lobby with travertine, skylight, evening mood, soft indirect lighting”). You can specify exterior / interior / layout and set aspect ratio.
• Style Transfer — Match the look of a reference image (e.g., “make my lobby look like this Scandinavian case study”), with strength and color‑preservation options.
• Sketch‑to‑Image — Turn line drawings or marker sketches into photoreal or illustrated images; choose detail/color/lighting preferences.
• Render Enhancer — Upload a draft render for AI enhancement (sharpening, dynamic mood, creativity vs. geometry sliders). Ideal for lifting bland white renders quickly.
• Virtual Staging — Drop furniture/decor into an empty photograph (great for real‑estate listings).
• 4K Upscaler — Final up‑rez for boards, print, or hero shots.
• AI Eraser — Provide an image + mask to remove unwanted objects (e.g., dumpsters, signage) without re‑rendering everything.
• Inpainting — Similar to Eraser but replace or add content within a mask (e.g., “replace red brick with travertine panels”).
• Video AI — Generate short cinematic animations from a reference image + prompt; useful for pitch decks and social teasers.
• Prompt Generator — Feed an image to get SDXL‑optimized prompts for architectural visualization; handy for teams that use multiple image engines.

C) API quick‑start (for automation)

Authentication
All endpoints require an API key via Authorization: Bearer YOUR_API_KEY. Create and manage keys in the dashboard.

Monitoring

• Status: GET /v1/status/{id}
• Credits: GET /v1/credits

Below are minimal curl examples for each major capability (see docs for Node/Python samples and full parameter lists).

Exterior AI

curl -X POST https://api.mnmlai.dev/v1/exterior \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/facade.jpg" \
  -F "prompt=Modern glass facade, warm evening lighting" \
  -F "imageType=photo" \
  -F "scenario=precise" \
  -F "geometry_input=85" \
  -F "styles=realistic" \
  -F "renderspeed=best"

Parameters to know: imageType (photo/drawing/wireframe/3dmass), scenario (creative/precise), geometry_input (0–100), styles, renderspeed.

Interior AI

curl -X POST https://api.mnmlai.dev/v1/interior \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/room.jpg" \
  -F "prompt=Scandinavian living room, oak floors, linen sofa" \
  -F "scenario=creative" \
  -F "geometry_input=70" \
  -F "styles=realistic"

Imagine AI (text‑to‑render)

curl -X POST https://api.mnmlai.dev/v1/imagine-ai \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "prompt=Double-height lobby with skylight, travertine, evening mood" \
  -F "render_type=interior" \
  -F "aspect_ratio=horizontal" \
  -F "style_strength=60"

Costs ~0.5 credits per image (per docs).

Mixture of Experts (MoE)

curl -X POST https://api.mnmlai.dev/v1/mixture-of-experts \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/shot.jpg" \
  -F "prompt=Convert to Mediterranean villa with stucco + clay roof" \
  -F "expert_name=exterior" \
  -F "imageType=model" \
  -F "form_control=0.8" \
  -F "seed=12345"

Style Transfer

curl -X POST https://api.mnmlai.dev/v1/style/transfer \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/source.jpg" \
  -F "reference_image=@/path/to/style.jpg" \
  -F "strength=0.7" \
  -F "color_preservation=0.3"

Sketch‑to‑Image

curl -X POST https://api.mnmlai.dev/v1/sketch-to-img \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/sketch.png" \
  -F "prompt=Modern house with deep eaves and floor-to-ceiling glazing" \
  -F "detail_level=high" \
  -F "lighting=natural"

Render Enhancer

curl -X POST https://api.mnmlai.dev/v1/render/enhancer \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/draft-render.jpg" \
  -F "prompt=Polish materials, add realistic indirect bounce" \
  -F "geometry=1" -F "creativity=0.3" -F "dynamic=5" -F "sharpen=0.5"

Virtual Staging

curl -X POST https://api.mnmlai.dev/v2/virtual-staging-ai \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/empty-room.jpg" \
  -F "prompt=Contemporary staging with light oak bed and two nightstands" \
  -F "seed=542371"

Docs note file types, size limits, and credits per request.

4K Upscaler

curl -X POST https://api.mnmlai.dev/v1/upscale \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/final.jpg"

AI Eraser

curl -X POST https://api.mnmlai.dev/v1/ai-eraser \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/image.jpg" \
  -F "mask=@/path/to/mask.png" \
  -F "output_format=png"

Inpainting

curl -X POST https://api.mnmlai.dev/v1/inpaint \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/image.jpg" \
  -F "mask=@/path/to/mask.png" \
  -F "prompt=Replace brick with travertine panels"

Video AI

curl -X POST https://api.mnmlai.dev/v1/video-ai \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/hero-shot.jpg" \
  -F "prompt=Slow dolly-in, cinematic lighting, evening" 

(~10 credits per generation, per docs).

Prompt Generator

curl -X POST https://api.mnmlai.dev/v1/prompt-generator \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/building.jpg"

Returns SDXL‑optimized prompts.

Check status & credits

# Status of an async job
curl -X GET "https://api.mnmlai.dev/v1/status/REQUEST_ID" \
  -H "Authorization: Bearer YOUR_API_KEY"
# Remaining credits
curl -X GET "https://api.mnmlai.dev/v1/credits" \
  -H "Authorization: Bearer YOUR_API_KEY"

Best practices: Use high‑quality inputs, keep horizons straight, clearly show the building/room, and be specific in prompts (style, materials, lighting). Save seed values to reproduce results and balance fidelity vs. exploration with geometry/flexibility controls.

Comparisons & ecosystem context

• Architizer lists mnml.ai among the top AI tools for architectural rendering, highlighting its ability to turn rough inputs into multiple styles (day/night, sketch→real).
• Alternatives often mentioned by practitioners include Veras, LookX, PromeAI, and others. Community threads note that plugin‑based tools may offer finer geometry control inside Revit/SketchUp, whereas mnml.ai excels at rapid stylization and iteration.

Final take

If your priority is speed + control for architecture imagery—without wrestling with render engines—mnml.ai delivers a specialized, end‑to‑end pipeline and a well‑documented API. Use Exact Render when you need fidelity, Flexible when you need options, and chain Style Transfer → Enhancer → Upscale → Inpaint for client‑ready results in minutes. For teams, the API makes it easy to scale.

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