by Azizul Hasan 0 (0 reviews)

Smart Local AI – Related Posts, AI Alt Text & Personalized Recommendations

Name: Smart Local AI – Related Posts, AI Alt Text & Personalized Recommendations
Author: Azizul Hasan

Private, on-device AI for WordPress: semantic related posts, AI alt text and personalized recommendations. No API keys, no cloud, no fees.

Smart Local AI ranks #69,937 among WordPress.org plugins with 0+ active installations, is #3,855 of 5,058 in the Security category, and was last updated Oct 19, 2026. Data from WordPress.org, refreshed twice daily — see methodology.

Compatible with WP 7.1.4

v1.2.0 Current Version v1.2.0

Updated 2 weeks ago Last Update on 19 Oct, 2026

Refreshed 1 week ago Last Refreshed on

#3,855 of 5,058 in Security Downloads +9.3% this week Actively maintained

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Rank

#69,937

— No change

Active Installs

-100%

KW Avg Position

N/A

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Downloads

1.2K

+30 today

Support Resolved

— No change

Rating

Review 0 out of 5

0 (0 reviews)

Next Milestone 10

Total Progress 0%

0+ 10+

42,369

Ranks to Climb

Growth Needed

8,000,000

Active Installs

Pro

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Current #69,937

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Active Installs 0,000,000+

Growth +0.0%

Peak 0,000,000

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Plugin Details

Version: 1.2.0
Last Updated: Oct 19, 2026
Requires WP: 6.2+
Tested Up To: 7.1.4
PHP Version: 7.4 or higher
Author: Azizul Hasan

Support & Rating

Rating: ☆ ☆ ☆ ☆ ☆ 0
Reviews: 0
Support Threads: 0
Resolved: 0%

Keywords

AI Alt Text personalization related posts similar posts

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Frequently Asked Questions

Common questions about Smart Local AI – Related Posts, AI Alt Text & Personalized Recommendations

Smart Local AI is a free WordPress plugin that adds AI features without cloud APIs. It runs open-source machine learning models in the browser (on-device AI) to produce semantic related posts, image alt text and personalized recommendations, and stores only the results in your WordPress database. It is made by AtlasAiDev and has a Pro add-on.

No. Smart Local AI does not call any cloud AI service. There is nothing to sign up for and no usage bill.

For related posts, alt text and on-site personalization, yes: those features run locally and cost nothing per use. It does not write blog posts or chat; it focuses on recommendations, accessibility and personalization.

No. Posts are embedded and images are captioned in the browser of the editor who runs the task; only the result is saved to your database. The only AI-related outside request is the one-time model download from Hugging Face, which you start yourself. Every outside connection is listed under "External services".

In the browser of the logged-in user who triggers it: the editor building the index, uploading an image or running the setup wizard. Visitors never download a model. They see related items and recommendations that were computed earlier and stored on your server.

RelevantFlow uses the sentence-transformer all-MiniLM-L6-v2 (about 23 MB). AltGenius uses ViT-GPT2 image captioning (about 250 MB) or Florence-2 base (about 460 MB) for more detailed alt text. All are open-source models from the Hugging Face Hub, run with Transformers.js and ONNX Runtime Web.

About 23 MB for related posts, 250 MB for the fast alt-text model and 460 MB for the detailed one. Each downloads once per browser, usually in one to two minutes, with a progress bar. On HTTPS sites the browser keeps the model, so later loads are instant.

No. The AI runs in the admin's browser, never on the server and never for visitors. Visitors load small scripts and pre-computed lists after the page has loaded. PersonaFlow's taste profiles are calculated on your server by scheduled tasks and cached per visitor.

Yes. Choose the content type on the Dashboard: posts, pages, WooCommerce products or any public custom post type. Each page recommends items of its own type, so product pages show products. The free plugin indexes one type at a time; when you switch, the old index is kept, so switching back needs no rebuild.

Yes, with Smart Local AI Pro. It adds more content types next to the one you chose. Each type gets its own index, its own number of items and heading, and learns each visitor's interest in that type separately, so reading blog posts does not steer product recommendations.