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What is Milvus?

A robust vector database tailored for efficient similarity searches at scale, Milvus is both open-source and exceptionally fast. It enables the storage, indexing, and management of extensive embedding vectors generated by deep neural networks or other machine learning methodologies. With Milvus, users can establish large-scale similarity search services in less than a minute, thanks to its user-friendly and intuitive SDKs available for multiple programming languages. The database is optimized for performance on various hardware and incorporates advanced indexing algorithms that can accelerate retrieval speeds by up to 10 times. Over a thousand enterprises leverage Milvus across diverse applications, showcasing its versatility. Its architecture ensures high resilience and reliability by isolating individual components, which enhances operational stability. Furthermore, Milvus's distributed and high-throughput capabilities position it as an excellent option for managing large volumes of vector data. The cloud-native approach of Milvus effectively separates compute and storage, facilitating seamless scalability and resource utilization. This makes Milvus not just a database, but a comprehensive solution for organizations looking to optimize their data-driven processes.

What is DocsGPT?

DocsGPT helps organisations get instant, accurate answers from their own documents, databases, and internal systems using AI that runs entirely on their own infrastructure. Unlike general-purpose AI tools, DocsGPT is built for businesses that cannot afford to send sensitive data to third-party cloud services. Deploy it on your servers, choose your AI provider, and connect it to the data sources your team already uses: document libraries, databases, wikis, customer support systems, and more. Employees ask questions in plain English and receive answers grounded in your actual company data with the source document cited, so they can verify the response. No hallucinations, no guesswork. Customer support teams use DocsGPT to build chatbots trained on product documentation. IT teams use it to give employees instant answers from internal policies. Operations teams use it to automate multi-step workflows that previously required manual intervention. Flexible pricing starts at free. Enterprise plans include role-based access control, dedicated support, 99.9% uptime SLA, and team analytics. Used in production by HM Government, AMD and Deloitte across more than 200 deployments.

Media

Media

Integrations Supported

Amazon S3
Apache Kafka
Apache Pulsar
Azure Blob Storage
Cognee
Database Mart
Discord
Docker
GitHub
Google Docs
IBM watsonx.data
Jira
Kubernetes
MinIO
PostgreSQL
Prompt Security
Slack
Telegram
Zilliz Cloud

Integrations Supported

Amazon S3
Apache Kafka
Apache Pulsar
Azure Blob Storage
Cognee
Database Mart
Discord
Docker
GitHub
Google Docs
IBM watsonx.data
Jira
Kubernetes
MinIO
PostgreSQL
Prompt Security
Slack
Telegram
Zilliz Cloud

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Zilliz

Date Founded

2020

Company Location

United States

Company Website

milvus.io

Company Facts

Organization Name

Arc53

Date Founded

2019

Company Location

Edinburgh, United Kingdom

Company Website

www.docsgpt.cloud/

Categories and Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

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