Welcome to Agentify
The first Agent-First product discovery platform. Built for the Zero-Click Economy, where AI agents make purchasing decisions on behalf of users.
The Problem We Solve
Traditional product databases are built for human search: browsing, filtering, comparing. But in 2025, most product discovery happens through AI agents (ChatGPT, Claude, voice assistants, autonomous shopping bots).
These agents face three critical challenges:
- Semantic Gap: Traditional category trees don't capture user intent ("eco-friendly for hiking" doesn't map to "Sports › Bottles").
- Trust Crisis: Agents can't verify data quality. Is this price accurate? Are specs validated? Who audited this information?
- Decision Paralysis: Agents receive raw data dumps requiring extensive post-processing to make actionable recommendations.
Result: AI agents either hallucinate product information, return low-quality recommendations, or refuse to help ("I can't verify this data").
Our Solution: Decision-Ready Product Passports (DPPA)
Agentify provides pre-validated, semantically enriched, AI-optimized product data that agents can trust and act on immediately.
Transparent Trust Scores
Every DPPA includes an ai:trustScore (0-1) with detailed breakdown showing exactly how it was calculated.
Agents can explain to users: "This product has a trust score of 0.87 because it was validated by 3 AI systems and is 95% complete."
Semantic Tags
Beyond categories, we provide intent-based tags that match how humans actually think about products.
Each tag has synonyms for fuzzy matching, allowing agents to understand natural language like "sustainable" → "EcoFriendly".
Multi-Agent Validation
Each DPPA is validated by a consensus of 3 LLMs to eliminate hallucinations and bias.
Consensus score is captured in sourceAudit component (30% weight).
Action-Ready Format
No post-processing needed. Each DPPA includes direct action links for immediate user tasks.
{
"ai:actions": {
"buyUrl": "https://amazon.com/dp/...",
"compareUrl": "...",
"reviewsUrl": "..."
}
}Agents can present: "Here's the best option. [Buy Now] for €44.95" without additional API calls.
The Economic Model: Cost-Transfer Architecture
Instead of building and maintaining expensive infrastructure, we transfer specific costs to you while handling the complex parts.
What You Handle (Embeddings)
- • Generate 1536-dim vectors (~$0.00002/query)
- • Use your own OpenAI API key
- • Total cost: ~$0.20 per 10,000 searches
This is negligible compared to building your own vector database, LLM orchestration, and validation pipeline.
What We Handle (Everything Else)
- • Qdrant vector storage (millions of products)
- • Multi-agent validation infrastructure
- • Real-time data quality monitoring
- • Semantic dictionary enrichment
- • API uptime and scaling
We save you from hiring ML engineers, managing databases, and orchestrating LLMs.
Result: You get production-grade semantic search for the price of embedding generation, while we handle millions in infrastructure costs.
Built for the Zero-Click Economy
By 2026, analysts predict 50% of product purchases will be initiated by AI agents without users clicking on search results. Agentify prepares your products for this future.
Traditional E-Commerce (Clicks Required)
⏱️ Average time: 15-20 minutes per purchase decision
Agent-First (Zero-Click)
⚡ Average time: 30 seconds | Zero product page visits | Trust score transparency
Ready to Get Started?
Jump into our quickstart guide and make your first API call in under 5 minutes.