Every appliance has a lifespan, a maintenance schedule, and a replacement timeline. Covala structures that knowledge as API data — so you can build the app, not the database.
Structured maintenance tasks for every product type — filter cleaning frequencies, recommended service intervals, seasonal checklists.
Average lifespan, signs of failure, and replacement timelines by product type. Power warranty tracking and replacement planning.
Annual energy costs, common repair costs, and total cost of ownership data. Help users make informed decisions about repair vs replace.
{
"product_type": "Dishwashers",
"knowledge": [
{
"type": "maintenance",
"items": [
{
"task": "Clean filter",
"frequency": "Monthly",
"difficulty": "Easy"
},
{
"task": "Run cleaning cycle",
"frequency": "Monthly",
"difficulty": "Easy"
},
{
"task": "Inspect spray arms",
"frequency": "Every 3 months",
"difficulty": "Easy"
}
]
},
{
"type": "lifespan",
"avg_years": 10,
"signs_of_failure": [
"Leaking",
"Poor cleaning",
"Strange noises"
]
}
]
}Home product data is fragmented across manufacturer sites, user manuals, and energy databases. Covala structures it so you don't have to.
Maintenance data is the hook. The rest of the platform makes your app indispensable.
Current prices from 20 retailers for replacement purchasing. Cross-retailer matching means one product, every price — so users can find the best deal when it's time to replace.
When something breaks, structured diagnostics by product type. Error codes with causes, severity levels, and fix steps — so your app can help users troubleshoot before calling a technician.
1,400+ brand profiles with quality tiers to inform replacement recommendations. Help users understand which brands are reliable across different product categories.
Feed product knowledge directly to AI assistants. Request format=ai for condensed summaries optimized for LLM context windows — perfect for AI-powered home management chatbots.
Structured product maintenance data is machine-readable information about how to care for a product — organized by product type. For each category like dishwashers or HVAC systems, Covala provides maintenance tasks with frequencies (monthly, quarterly, annually), difficulty levels, seasonal considerations, and recommended service intervals. Instead of parsing user manuals, you query one API endpoint and get clean JSON.
Use Covala’s knowledge API with the lifespan type. For any product type, you get average lifespan in years, common signs of failure, and replacement timeline data. Combine this with the product’s purchase date in your app to show users how much life is left in their appliances and when to start planning replacements.
Yes. Covala’s knowledge layer includes cost of ownership data per product type — annual energy costs, common repair costs, and total cost of ownership estimates. This powers repair-vs-replace decisions: when a 9-year-old dishwasher needs a $400 repair, your app can show the user that a new one costs $550 and will save $50/year in energy.
Yes. Covala covers 620+ product types across appliances, HVAC, electronics, and home equipment — everything a property management platform needs. Maintenance schedules help you generate work orders. Lifespan data powers capital planning. Cross-retailer pricing helps with procurement. All structured as API data, not scattered across vendor sites.
Covala has maintenance data for 620+ product types including dishwashers, refrigerators, washing machines, dryers, HVAC systems, water heaters, range hoods, garbage disposals, air purifiers, dehumidifiers, and more. Each product type has structured maintenance tasks, lifespan data, and cost of ownership information — all accessible through a single REST API.
Cross-retailer pricing, already matched. Build comparison features without building matching infrastructure.
Give your agent structured product tools via MCP or REST. Specs, pricing, and knowledge — not web scraping.
Error codes, failure modes, and fix steps — structured as API data, not buried in PDFs and forum posts.
Maintenance schedules, lifespan data, and replacement planning for 620+ product types across 20 retailers — all from one API.