Making Commerce
Understandable to Machines.
The commerce data infrastructure for AI-ready product catalogs — interpretability, structure, knowledge, action, and measurement in one stack.
Turn ecommerce catalogs into machine-readable commerce data that ChatGPT, Perplexity, Google AI, Claude, and autonomous shopping agents can read, rank, and recommend.
The Arc
Five products. One promise.
The Interpretability Layer for AI Commerce
Transforming catalogs into machine-readable commerce intelligence.
Explore the layer →Catalog Data, Structured for Machines
Ingestion, transformation, enrichment, and delivery across commerce channels.
See NSOLVIA DATA →Retrieval Built for Commerce
Grounding AI agents in product truth, merchant context, and structured commerce knowledge.
See Semantic RAG →The AI Seller That Understands Your Catalog
Answers questions, recommends products, and guides shoppers using your commerce data.
See NSOLVIA MSA →Know What Machines See
Measure catalog interpretability with the Agentic Catalog Readiness Score™ and uncover the gaps limiting AI-driven discovery.
Run the audit →Where Catalogs Become Intelligence
Original research, insights and frameworks on how AI agents understand products, brands and digital commerce.
Explore Intelligence →Compatible with
How it all fits
The full stack of AI commerce
Layer makes catalogs machine-readable.
DATA delivers clean feeds & APIs.
RAG grounds agents in product truth.
MSA sells through your catalog 24/7.
Audit scores AI commerce readiness.
Use cases supported
AI-ready product catalogs for every channel
Five intent surfaces that AI assistants and shopping agents actually use — answered directly by structured product data, not by guesswork.
Product Discovery
Shoppers (and AI agents) find the right product by meaning and intent, not just keywords.
Goal-Oriented Shopping
Catalogs answer outcomes — 'help me sleep better,' 'build muscle,' 'host 8 people' — not just SKUs.
Product Comparison
Structured attributes let AI compare options like-for-like across brands and variants.
Occasion/Use-Case Matching
Wedding, gym, rainy commute, gift for mom — products surface to the moment they fit.
Agentic Commerce Retrieval
Autonomous shopping agents query your catalog by meaning and get back ranked, structured products.
Frequently asked
The questions merchants ask first
Why are stores that “did everything right” suddenly invisible?
Because the rules changed quietly. For twenty years catalogs were built for two readers — shoppers and search engines. Now a third reader increasingly shapes what gets discovered: AI systems that read structure, not pages. Presence is no longer the bar; interpretability is.
What is NSOLVIA?
NSOLVIA is built around the Semantic Commerce Layer — the infrastructure that makes your product catalog understandable to the AI systems now driving discovery, so machines can find, understand, and surface what you sell.
Do I really need five different tools for this?
No — and that’s the point. Instead of stitching together a feed tool, an SEO agency, a schema plugin, and a chatbot, NSOLVIA is one layer that handles machine-readability across all of them, from one enriched catalog.
Isn’t this kind of thing expensive?
NSOLVIA was designed for growing merchants, not only enterprise teams — and you can start free. The deeper infrastructure scales with you as you grow.
Who is NSOLVIA for, and where do I start?
For merchants, SMBs, and agencies who sell online and want to stay visible as discovery shifts to AI. Pick the surface you need: measurement at /audit, deployment at /msa, /semantic-rag, or /semantic-commerce-layer.
See your catalog through
the eyes of AI.
Free Agentic Catalog Readiness Score™ · coming soon.
Audit My Catalog Free