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Description
Agent Search on Gemini Enterprise Agent Platform is an advanced search solution that brings Google-level search capabilities to enterprise data and applications. It allows developers to create intelligent search experiences for websites and internal systems using both structured and unstructured data. By incorporating generative AI, the platform replaces basic keyword matching with conversational and context-aware search results. It functions as a ready-to-use retrieval augmented generation (RAG) system, grounding AI responses in enterprise data for improved accuracy. The platform simplifies complex backend processes such as ETL, indexing, and embedding generation, reducing development time significantly. It offers industry-specific solutions for sectors like healthcare, media, and retail, enabling more personalized and relevant search experiences. Developers can also build custom solutions using APIs for vector search, document parsing, and ranking. The integration with vector databases allows for advanced semantic search and recommendation systems. With minimal setup, users can deploy search engines directly into websites or applications. Continuous refinement tools help optimize search performance and relevance. Overall, it empowers businesses to deliver faster, smarter, and more engaging search experiences powered by generative AI.
Description
HyperCrawl is an innovative web crawler tailored specifically for LLM and RAG applications, designed to create efficient retrieval engines. Our primary aim was to enhance the retrieval process by minimizing the time spent crawling various domains. We implemented several advanced techniques to forge a fresh ML-focused approach to web crawling. Rather than loading each webpage sequentially (similar to waiting in line at a grocery store), it simultaneously requests multiple web pages (akin to placing several online orders at once). This strategy effectively eliminates idle waiting time, allowing the crawler to engage in other tasks. By maximizing concurrency, the crawler efficiently manages numerous operations at once, significantly accelerating the retrieval process compared to processing only a limited number of tasks. Additionally, HyperLLM optimizes connection time and resources by reusing established connections, much like opting to use a reusable shopping bag rather than acquiring a new one for every purchase. This innovative approach not only streamlines the crawling process but also enhances overall system performance.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Chat Mitra
Docker
Gemini
Gemini 2.5 Flash Native Audio
Gemini Enterprise
Gemini Enterprise Agent Platform
Google Cloud Document AI
Google Cloud Platform
Google Colab
Integrations
Amazon Web Services (AWS)
Chat Mitra
Docker
Gemini
Gemini 2.5 Flash Native Audio
Gemini Enterprise
Gemini Enterprise Agent Platform
Google Cloud Document AI
Google Cloud Platform
Google Colab
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/products/gemini-enterprise-agent-platform/agent-search
Vendor Details
Company Name
HyperCrawl
Website
hypercrawl.hyperllm.org
Product Features
Enterprise Search
AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery