AR-Based Interior Planning & Furniture Try-On

From Uncertainty to 1:1 Scale Precision

Choosing the right furniture is often a guessing game will it fit? Does the material match the room? For a global furniture brand, these uncertainties led to high return rates and hesitant customers.

At Shwaira we engineered a spatial computing-based furniture try-on experience to solve this. By utilizing room mapping and persistent spatial anchoring, customers can now place and evaluate high-fidelity 3D assets at a 1:1 real-world scale within their own living spaces.

This isn’t just a visual tool it’s an engineering-led solution that validates size, fit, and layout flow before a single dollar is spent.

Business Challenge Client Faced

A global furniture brand lacked true-to-scale visualization for large-format products, resulting in high return rates caused by customer uncertainty around size, fit, and spatial compatibility. Shoppers were unable to accurately judge how furniture would appear or function within their real living environments prior to purchase.

This gap in the buying experience reduced customer confidence, increased logistics and restocking costs, and limited the brand’s ability to effectively showcase premium and large-format products. The company needed an immersive, reliable solution that would allow customers to validate furniture placement and design choices before completing a purchase.

Solution Engineered by Shwaira

Shwaira engineered a spatial computing-based furniture try-on experience that enables customers to place and evaluate furniture at 1:1 real-world scale within their own living spaces.

The solution leverages room mapping, persistent spatial anchoring, and high-fidelity 3D assets to ensure accurate representation of size, fit, layout flow, and material appearance. Customers can explore multiple configurations, compare options, and confidently finalize purchases, all within an intuitive and immersive AR environment.

Business Impact
Experienced
  • +38% higher purchase conversion among users who experienced furniture in their own space.
  • 45% reduction in product returns, significantly lowering logistics and restocking costs.
  • +32% increase in average order value (AOV) through effective cross-sell and bundle purchases.
  • $150M+ in incremental annual revenue driven by widespread adoption of the spatial try-on experience.

These outcomes reshaped the customer journey, strengthened brand trust, and unlocked substantial new revenue streams through immersive digital commerce.

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Commonly asked questions and answers

Phone:
+91 7770030073
Email:
info@shwaira.com
Most teams struggle not with lack of technology, but with too many options like - AI, automation, IoT, digital twins, XR, cloud, edge.
Choosing incorrectly often leads to overbuilt or fragile systems.

How Shwaira helps:
  • Shwaira begins by identifying the decision, process, & system behavior that needs improvement.
  • We then assess data availability, latency requirements, reliability constraints, and operational risk before defining the technology mix.
  • This ensures AI, automation, or simulation is introduced only where it creates real system value.
In most cases, no.
Many systems fail not because they are outdated, but because they lack observability, automation, or intelligence.

How Shwaira helps:
  • Shwaira designs architectures that extend existing platforms, devices, and data pipelines.
  • We integrate intelligence & automation incrementally to modernize systems without disrupting live operations or forcing risky, large-scale replacements.
A common failure pattern is moving too quickly from concept to full rollout without validating performance, data integrity, or integration complexity.

How Shwaira helps:
  • Shwaira validates systems early through structured prototypes, technical spikes, and controlled pilots.
  • We test data pipelines, decision logic, system load, and integration boundaries before scaling, so production systems behave predictably under real-world conditions.
AI is powerful, but not always the most reliable or cost-effective choice.
Many production systems benefit more from deterministic logic, automation, or edge processing, with AI applied selectively.

How Shwaira helps:
  • Shwaira designs hybrid systems to combine AI models, rules, automation, and simulations where each fits best.
  • This results in systems that are explainable, resilient, and easier to operate long term.

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