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About

Actian VectorAI DB is a portable, local-first vector database designed for AI systems that need to run close to their data, including edge, on-premises, and hybrid environments. It enables developers to deploy semantic search, retrieval-augmented generation (RAG), and AI-powered applications without relying on cloud infrastructure, avoiding latency, network dependency, and per-query costs. It provides native vector storage and high-performance similarity search using techniques such as approximate nearest neighbor indexing and algorithms like HNSW, allowing efficient retrieval across large embedding datasets while balancing speed and accuracy. It delivers low-latency search directly on devices ranging from laptops to embedded systems like Raspberry Pi, supporting real-time decision-making and autonomous behaviors without a network round-trip.

About

The Universal Sentence Encoder (USE) encodes text into high-dimensional vectors that can be utilized for tasks such as text classification, semantic similarity, and clustering. It offers two model variants: one based on the Transformer architecture and another on Deep Averaging Network (DAN), allowing a balance between accuracy and computational efficiency. The Transformer-based model captures context-sensitive embeddings by processing the entire input sequence simultaneously, while the DAN-based model computes embeddings by averaging word embeddings, followed by a feedforward neural network. These embeddings facilitate efficient semantic similarity calculations and enhance performance on downstream tasks with minimal supervised training data. The USE is accessible via TensorFlow Hub, enabling seamless integration into various applications.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI engineers building edge or on-prem applications who need fast, local semantic search and scalable vector data processing without cloud dependency

Audience

Data scientists and machine learning engineers seeking a tool to optimize their natural language processing models with robust sentence embeddings

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Actian
Founded: 1980
United States
www.actian.com/databases/vectorai-db/

Company Information

Tensorflow
Founded: 2015
United States
www.tensorflow.org/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder

Alternatives

Alternatives

word2vec

word2vec

Google
voyage-4-large

voyage-4-large

Voyage AI

Categories

Categories

Integrations

Cohere
Docker
Google Colab
Hugging Face
OpenAI
Raspberry Pi OS
TensorFlow

Integrations

Cohere
Docker
Google Colab
Hugging Face
OpenAI
Raspberry Pi OS
TensorFlow
Claim Actian VectorAI DB and update features and information
Claim Actian VectorAI DB and update features and information
Claim Universal Sentence Encoder and update features and information
Claim Universal Sentence Encoder and update features and information