Find instead of Search – Products that explain why they fit
With AGINITY AI, your catalogue becomes a network of intelligent product agents. They don't just respond to keywords – they ask a precise follow-up question when needed, check live inventory, and deliver the exactly relevant result in seconds.
Results from projects (up to):
Why classical search systems reach their limits
Black-Box Matching
Conventional vector or BM25 search shows scores, but not the reason.
Outdated Data
Re-indexing takes hours; stock changes go unnoticed.
Zero-Result Frustration
Vague queries or implicit intent lead to empty result pages.
High Integration Costs
Proprietary engines require deep changes to front- and back-end.
How AGINITY AI solves these problems
Agent-Based Product Intelligence
Every product receives a complete attribute profile plus contextual knowledge. When a query arrives, the agent acts like a knowledgeable sales advisor.
Explainable Results
For every result ranking, AGINITY AI shows a transparent attribute-weighting graph – understandable for end users and verifiable for audits.
Live Inventory Sync
If stock level, price or delivery time changes, AGINITY AI synchronises the information within 60 seconds.
Plug & play in 30 minutes
Two lines of code suffice: embed the widget, upload the feed, done. For headless setups a REST/GraphQL API is available.
Fair-Priced Pay-per-Use
Billing is per processed search query. From 1 million queries per month, price caps apply.
Hosting & Support in Germany
The platform runs in an ISO-certified data centre in Frankfurt am Main.
Why this delivers measurable results immediately
More Conversion
When buyers no longer need to research and compare at length, conversion rates rise significantly.
Fewer Wrong Purchases
Catalogue-wide matching plus clear guidance reduces wrong purchasing decisions.
Fewer Support Requests
When the consultation already answers typical product questions during the buying process, follow-up enquiries decrease.
Comparison: Conventional RAG Search vs. AGINITY AI
| Aspect | Conventional RAG Search | AGINITY AI Service Intelligence |
|---|---|---|
| Transparency | Black-Box Scores | Attribute-weighting graph per result |
| Data Currency | Batch re-indexing | Live sync ≤ 60 s |
| Relevance risk | Prone to hallucinations | Hallucinations minimized through structured product data |
| Integration | Weeks of effort | 30 Minuten Widget / Headless-API |
| Pricing model | Fixed costs + additional fees | Pure pay-per-use with caps |
Frequently Asked Questions
What is Agentic Search?
Agentic Search coordinates multiple specialised AI agents that translate purchase intent, requirements and constraints into a complete catalogue match across structured product data points per SKU. The result is not a top-k subset, but a complete, reasoned selection of all matching products.
How does Agentic Search differ from classic product search in an advisory context?
AGINITY AI matches the complete product catalogue via structured data points per product and returns all matching products with comprehensible justification – incl. hard attributes, compatibility and constraints.
What is the difference between Agentic Search and RAG?
RAG and vector systems typically return a semantically similar subset (top-k retrieval) from text or vector indexes. AGINITY AI works with structured product data points, validates hard criteria such as compatibility and constraints, and returns all products that fully meet the requirements.
