Vector Databases

Embeddings

Fast AI text embeddings for serverless functions.

Status
UnmaintainedNo commits in 1010 days.
Last checked
Checked · Oct 16, 2026
License
Open source
Pricing
Free tier · from $0

What it is

Energetic-ai provides fast and easy-to-use AI text embeddings, optimized specifically for serverless environments. It simplifies the process of generating high-quality embeddings without the need for extensive setup or maintenance.

Energetic-ai stands out with its focus on optimizing text embeddings for serverless functions, providing developers with an easy-to-integrate solution that enhances performance in cloud environments.

When it fits — and when it doesn’t

A good fit for

  • Developers looking to integrate fast, efficient text embeddings into their serverless applications

  • Teams working on NLP projects that require quick and easy embedding generation without extensive setup

Look elsewhere if

  • Projects requiring real-time streaming capabilities (batch-only architecture)

  • Applications needing a wide range of language support beyond JavaScript

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Limited language support beyond JavaScript

    Primary focus on JavaScript limits its usability for teams using other languages

  2. 02

    Small community and limited third-party integrations

    GitHub repository has low activity with few contributors and limited documentation on external integrations

  3. 03

    Complex setup for non-serverless environments

    Documentation assumes serverless deployment, making it difficult to set up in traditional server-based architectures

What it does well

  • Optimized for serverless functions

  • Easy integration into existing projects

  • High performance and speed in generating embeddings

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

How Fast Is It?

Set up Embeddings

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →
Get the badge

A small badge for Embeddings’s README or site: its name, “Tracked on AI Navigator”, and the availability status and check month from this page. It updates as the catalog does.

Embeddings — tracked on AI Navigator

Markdown

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HTML

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