Presti AI

What do they actually do

Presti AI makes a browser-based tool that turns a single furniture product photo into finished, photorealistic lifestyle images. Users upload a silo or warehouse shot, and the app keeps the product intact while changing the scene around it — background, props, lighting, people — to create on-brand images without a photoshoot or CGI. It’s built specifically for furniture brands and retailers that need many consistent visuals for product pages and marketing (site, YC listing).

The workflow is straightforward: upload one product photo, auto-cutout the item, choose or describe a scene, and optionally swap colors/materials, add or remove props, and adjust lighting/composition. Teams can batch the same style across a collection and export for e‑commerce and ads — all from the web app (product/how it works, plans & features). Pricing is SaaS with credit tiers and enterprise plans (pricing).

The system is tuned for furniture, which reduces the typical artifacts seen in general-purpose image models. As with any synthetic workflow, results depend on input image quality and some iteration to meet strict brand standards. Presti has also begun rolling out video generation (e.g., 360° spins and short product videos) as an extension of the still-image workflow (trade coverage, press releases).

Who are their target customer(s)

• E‑commerce manager at a furniture brand or retailer: Needs many lifestyle images for PDPs and ads but can’t shoot every SKU/variant; traditional shoots/3D are slow and costly and make it hard to keep catalogs consistent (how it works, plans & features).
• In‑house creative lead or agency art director: Must keep imagery visually consistent across seasons/campaigns; spends time directing shoots and retouching to match brand rules; wants predictable outputs that follow the house look (brand fine‑tuning context).
• Product/production manager at a furniture manufacturer: Has to produce dozens/hundreds of color/finish/upholstery variants quickly while samples are limited; can’t wait for prototypes or bespoke CAD renders; needs bulk outputs (features, plans & features).
• Digital marketing or social team focused on paid creative: Wants short product videos, 360° spins, and dynamic ad assets; video shoots and edits are expensive and slow; needs motion content at scale (video rollout coverage).
• Catalog/content operations at multi‑brand retailers or marketplaces: Must standardize thousands of listings with tight SLAs; current workflows bottleneck on photography and manual QA; needs a predictable, high‑throughput imaging pipeline with team/enterprise features (enterprise & batch features, YC B2B focus).

How would they acquire their first 10, 50, and 100 customers

• First 10: Founder‑led pilots with a few mid‑size furniture brands and 1–2 specialist e‑commerce agencies. Produce a small batch from their existing product photos (free or discounted), handle onboarding/QA, and capture before/after cost and time saved to create reference case studies.
• First 50: Hire 1–2 sales reps to repeat the pilot playbook via targeted LinkedIn/cold email to e‑commerce and production leaders; convert with short paid trials and bundled credit plans. Support with trade shows and focused paid campaigns that drive demo signups using early case studies.
• First 100: Add channel partners (agencies/platform integrators) and a self‑serve trial with templates and clear credit pricing for smaller brands. Introduce customer success to uphold quality SLAs for bulk jobs, sell brand‑style fine‑tuning to larger accounts, and drive referrals and enterprise pilots.

What is the rough total addressable market

Top-down context:

Furniture is a large, global category: the market was estimated around $746B in 2024 and projected to exceed $1.3T by 2033, with the U.S. at ~$172B in 2024 (Grand View Research – global, Grand View Research – U.S.). Only a small slice of this spend is product imagery/content, but the scale highlights how many SKUs require visuals across channels.

Bottom-up calculation:

If ~5,000 mid‑to‑large furniture brands/retailers globally adopt AI visual pipelines and spend $25k–$75k per year on software/credits and managed services for stills and basic motion, the TAM would be roughly $125M–$375M. As video and brand fine‑tuning standardize, average spend could rise, lifting TAM accordingly.

Assumptions:

• Targetable segment focuses on mid‑to‑large brands/retailers that manage large SKU catalogs (~5,000 accounts globally).
• Average annual spend per customer on imaging software/credits/services is $25k–$75k for stills and light video.
• Adoption and spend expand as video and brand‑style models become standard in production workflows.

Who are some of their notable competitors

• Cylindo (by Chaos): Furniture‑focused 3D visualization platform (lifestyle imagery, 360 spins, AR, analytics) widely used by furniture brands; a mature CGI/3D alternative to AI scene generation (site).
• Nfinite: Retail visual content platform that automates packshots, lifestyle images, spins, and videos at catalog scale; positions around AI/3D and workflow for large retailers (site).
• Threekit: Visual commerce and 3D configurator platform with Virtual Photographer (2D renders), space planning, and AR; used by manufacturers and retailers including furniture (site).
• Adobe Photoshop (Generative Fill): General‑purpose AI editing to add/remove objects and change backgrounds; creative teams can manually build furniture lifestyle shots but without furniture‑specific constraints (Adobe).
• Pixelcut: Broad AI product photo editor/generator used by small brands and creators for background replacement and quick lifestyle scenes; not furniture‑specialized but a common lightweight alternative (site).