A shopping agent that quotes last week's price is worse than no agent
Live product data, prices, availability, launches and reviews, pre-ingested and validated, so your agent recommends things that are actually in stock at the price it just quoted.
GET YOUR API KEYWhat you get from the layer
Accurate at the moment of recommendation
Stale price or availability data doesn't just disappoint, it generates a refund, a support contact and a trust problem. Continuous ingestion means the agent's answer matches the storefront.
No scraper fleet to maintain
Retail sites change structure constantly and block aggressively. Maintaining scrapers across a competitive set is permanent engineering cost with no product value at the end of it.
Breadth without per-source integration
Products, prices, availability, launches and reviews arrive through one endpoint instead of one integration per retailer.
Where teams put it to work
Shopping and recommendation agents
Answer product questions with current price, availability and review sentiment.
Dynamic pricing engines
Feed competitive pricing signal to models that set your own.
Assortment and launch monitoring
Detect competitor launches and catalogue changes as they happen.
Review and sentiment analysis
Query review content semantically across products and competitors.
Merchandising copilots
Give internal teams an assistant grounded in live category data instead of last month's export.
What the endpoint gives you
- Live product, price and availability data
- Launch and catalogue change detection
- Review content
Semantically searchable
- Freshness-ranked retrieval
- Six-dimension filtering
- Quorum validation
Before a price is served
- Global Memory
Shopper context across sessions
Questions teams ask first
- Which retailers and categories are covered?
- Coverage varies by category and region, check your specific category with the team before building against it.
- How current is pricing?
- Refreshed on the global ingestion cycle. For categories where pricing moves faster than that, Watchdog can prioritise ingestion.
- Can it handle a category we don't see indexed?
- Watchdog auto-spawns a pipeline for unknown data, so a gap on first request is served from the index afterwards.
- Can the agent complete a purchase?
- Incord provides the context layer. Transaction execution stays in your commerce stack.
- Does shopper context persist across sessions?
- Yes, via Global Memory. The agent remembers preferences without you operating a vector store.
- Can we use this for a voice shopping assistant?
- Yes. Voice & WebRTC gives you numberless web calls that carry full user context.