Demo tour

Get started

Feature 1

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam

Feature 2

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam

Demo tour

Get started

Feature 1

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam

Feature 2

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam

Pricing Blog
Accurate Hallucination Detection With NER ยป

Connect Trieve to Shopify

Compared to Algolia, Trieve offers vector based search, manged RAG, and pricing based on rate limits instead of number of search queries

VapiSigNozFlaviaravalanceGuardantBestwayCoolifyAlloBrain
VapiSigNozFlaviaravalanceGuardantBestwayCoolifyAlloBrain

The most unique and impressive advantage

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper nouns and compare them between the gen AI completion and the retrieved reference text. For numbers and unknown words, we use similarly straightforward techniques to flag potential issues.

The second most unique and impressive advantage

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper nouns and compare them between the gen AI completion and the retrieved reference text. For numbers and unknown words, we use similarly straightforward techniques to flag potential issues.

The third most unique and impressive advantage

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper nouns and compare them between the gen AI completion and the retrieved reference text. For numbers and unknown words, we use similarly straightforward techniques to flag potential issues.

The fourth most unique and impressive advantage

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper nouns and compare them between the gen AI completion and the retrieved reference text. For numbers and unknown words, we use similarly straightforward techniques to flag potential issues.

Enhance support for your Shopify store
and turn it into a profit center

Live chat

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper noun.

Social media posts & ads

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper noun.

Auto responder

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper noun.

Support & revenue statistics

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper noun.

Ticketing System

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper noun.

Macros

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper noun.

Intent and sentiment detection

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper noun.

Multi-store connection

Instead of throwing complex language models at the problem with a LLM-as-a-judge approach, we use Named Entity Recognition (NER) to spot proper noun.

Join 1000+ leading Shopify stores
across the world using Trieve