head to head · open source

local-deep-research vs teslamate

local-deep-research has 9,109 GitHub stars, 824 forks, 889 open issues and last shipped yesterday. teslamate has 9,008 stars, 1,006 forks, 72 open issues and last shipped yesterday. local-deep-research leads on adoption by 1% (9,109 vs 9,008 stars). local-deep-research is written in Python under MIT; teslamate is written in Elixir under AGPL-3.0. local-deep-research has attracted 9% as many forks as stars, teslamate 11%. local-deep-research was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (home-automation), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

local-deep-research ★ 9.1K teslamate ★ 9.0K category Productivity & Utilities

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Side by side

local-deep-research teslamate
GitHub stars ★ 9.1K ★ 9.0K
License MIT AGPL-3.0
Written in Python Elixir
Last push 2026-09-19 2026-09-19
Forks ⑂ 824 ⑂ 1.0K
Self-hosting Yes Yes
Data ownership Your server Your server

pick local-deep-research if

  • You weight community size — 9.1K stars and counting
  • You want the MIT license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full local-deep-research profile →

pick teslamate if

  • You want the teslamate feature set and don't need the biggest community
  • You prefer the AGPL-3.0 license terms
  • Your stack matches Elixir
  • You evaluated both and teslamate fits your workflow better

full teslamate profile →

About local-deep-research

Local Deep Research is an MIT licensed, Python based AI research assistant that performs deep, agentic research with proper citations across any local or cloud LLM and more than ten search engines, built for researchers, developers, and privacy conscious self hosters who want both the workload and the data to stay on hardware they control.

read the full local-deep-research overview →

About teslamate

TeslaMate is an open source, self hosted data logger that records and visualises data from Tesla vehicles, built for Tesla owners who want their driving, charging and battery history to live on their own infrastructure instead of inside a third party service.

read the full teslamate overview →

More in Productivity & Utilities

n8n ★ 205K Excalidraw ★ 132K RustDesk ★ 124K LocalSend ★ 92K AppFlowy ★ 77K OBS Studio ★ 76K

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More Automation projects

Compare either of these against the rest of the Automation field.

local-deep-research vs n8n local-deep-research vs ProxmoxVE local-deep-research vs ActivePieces local-deep-research vs LiveKit local-deep-research vs amis local-deep-research vs Windmill local-deep-research vs Botpress local-deep-research vs mitosis local-deep-research vs Automatisch local-deep-research vs puck local-deep-research vs Typebot local-deep-research vs cadence

Frequently asked questions

Is local-deep-research or teslamate more popular?

local-deep-research has 9,109 GitHub stars and teslamate has 9,008. local-deep-research has the larger community by that measure.

Are local-deep-research and teslamate free?

Both are open source. local-deep-research is licensed under MIT and teslamate under AGPL-3.0. Neither carries a licence fee.

What is the difference between local-deep-research and teslamate?

local-deep-research is written in Python and teslamate in Elixir. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, local-deep-research or teslamate?

Choose local-deep-research if you want the larger community (9,109 stars) or its MIT licence terms. Choose teslamate if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.