Eclaire
Self-hosted, open-source AI assistant for tasks, notes, docs, photos, and bookmarks
Eclaire earns its place if data sovereignty is a hard requirement, not a nice-to-have. The five-way data unification plus OCR, extraction, and scheduled automations cover more ground than most local-AI projects, and v0.6.0's single-container Docker cut the setup pain that used to be the main reason to skip it. The catch is unchanged: you supply the hardware, the Docker know-how, and the model choices — there's still no hosted tier to fall back on.
Verified 1d ago · liveness 80/100 · cite: rightaichoice.com/tools/eclaire
- Privacy-focused professionals who need AI over tasks, notes, docs, photos, and bookmarks without cloud exposure
- Developers comfortable with Docker who want a self-hosted assistant with a REST API
- Small teams replacing Notion AI or Mem while keeping data on their own infrastructure
- Organizations with data sovereignty rules that need on-premise or private-cloud AI
- Users who want a hosted, zero-setup assistant like ChatGPT — Eclaire is self-hosted only
- Anyone without a GPU or an M1-or-later Mac willing to source models and manage memory
- Non-technical users who don't want to maintain Docker containers and upgrades
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Skip Eclaire if you're not comfortable with Docker and managing your own hardware, or if you expect a hosted, zero-setup AI assistant like ChatGPT without any infrastructure overhead.
You pay for your own hardware (GPU or Mac Mini/Studio) and electricity; there's no subscription but hardware costs can be significant.
Eclaire is free for self-hosters, making it cheaper than hosted productivity suites like Notion AI ($10/user/mo) or Mem, but you bear the hardware and setup costs. For business needs, custom consulting pricing is opaque; compare with self-hosted alternatives like Ollama or LocalAI.
In short
Eclaire — Self-hosted, open-source AI assistant for tasks, notes, docs, photos, and bookmarks. Best for Privacy-focused professionals who need AI over tasks, notes, docs, photos, and bookmarks without cloud exposure, Developers comfortable with Docker who want a self-hosted assistant with a REST API, Small teams replacing Notion AI or Mem while keeping data on their own infrastructure. Free to use.
What's new in Eclaire
Checked 17 days agoAcross the latest 4 updates: 2 feature updates, 1 changelog entry and 1 news mention.
Eclaire v0.6.0: Deploy Private AI in Minutes
Introduces single-container Docker deployment, optional Redis, and SQLite support, simplifying self-hosting significantly.
Eclaire v0.5.0: Node.js v24 LTS
Moves to Node.js v24 LTS and pnpm v10, with various bug fixes.
Running Qwen3-VL with LM Studio
Guide to running Qwen3-VL multimodal AI model with LM Studio for complete privacy and control.
Eclaire v0.4.0: Native Apple Silicon Support with MLX
Adds native Apple Silicon support via MLX-LM, MLX-VLM, and LM Studio for efficient local inference.
What people actually say about Eclaire — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
19 mentions across 3 sources (Hacker News, GitHub, Lemmy) · researched Jul 31, 2026.
Average across the 3 sources that answered — each source counts once, not each post.
- +Complete data privacy – all processing and storage on your own hardware.
- +Unifies tasks, notes, documents, photos, and bookmarks in one dashboard.
- +Supports open-source models like Qwen, Gemma, DeepSeek, Kimi, Llama.
- +Extensible via APIs, Apple Shortcuts, Android intents, and share sheets.
- +PWA support for mobile access without a native app.
- −Setup is confusing – missing default credentials block initial login.
- −Small community – only 890 GitHub stars, limited support resources.
- −Self-hosting requires significant technical skill and infrastructure.
- −Documentation is sparse, especially for troubleshooting common issues.
- −No native mobile apps – relies on PWA and share sheets.
- • Infrastructure costs for running own server (electricity, hosting, hardware)
- • Time investment for setup, maintenance, and troubleshooting
Viability Score
How well maintained and how widely used is Eclaire? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- AI assistant that searches, organizes, and manages all your local data
- Full-text search and Q&A across PDF, DOCX, XLSX, HTML, PPT, and Numbers
- OCR to extract text from images across JPEG, PNG, SVG, HEIC, and WEBP
- Object detection and automatic photo tagging and categorization
- Bookmark fetching, offline reading, and PDF conversion
- Intelligent metadata extraction from websites and platforms
- Rich text and Markdown notes with AI-powered creation and organization
- Task management with due dates, recurrence, and smart prioritization
- AI automation for scheduled and recurring tasks
- Single-container Docker deployment with optional Redis and SQLite (v0.6.0)
- Native Apple Silicon inference via MLX-LM, MLX-VLM, and LM Studio (v0.4.0)
- Runs open-source models like Qwen, Gemma, Deepseek, Kimi, and Llama
- Download models from Hugging Face or connect cloud inference APIs
- Switch between models or run multiple models simultaneously
- PWA with share sheets for web and mobile
About Eclaire
Eclaire is a local-first, open-source AI assistant that pulls tasks, notes, documents, photos, and bookmarks into one private workspace running on your own hardware. Nothing routes through a cloud you don't control: your files, images, and notes stay on your machine, and the assistant reasons over them in place. It's built for people who already self-host — developers, privacy-minded professionals, and small teams that want AI over their own data without handing it to a third party. The assistant answers questions, summarizes content, and executes actions across five data types. Bookmarks get fetched, saved offline, converted to PDF, and metadata-extracted. Documents support full-text search plus summaries, extractions, and Q&A across PDF, DOCX, XLSX, HTML, PPT, Numbers, and more. Photos get auto-tagging, object detection, and OCR across JPEG, PNG, SVG, HEIC, and WEBP. Notes handle rich text and Markdown with AI-assisted creation; tasks carry due dates, recurrence, and smart scheduling the assistant can act on. Deployment has gotten materially simpler. v0.6.0 shipped single-container Docker deployment with optional Redis and SQLite, and v0.5.0 moved the project to Node.js v24 LTS and pnpm v10. v0.4.0 added native Apple Silicon support via MLX-LM, MLX-VLM, and LM Studio. You can download models from Hugging Face or point Eclaire at cloud inference APIs, switching between models or running several at once. Eclaire is not a hosted assistant like ChatGPT, and it isn't trying to be. It's the self-hosted counterweight to cloud productivity suites like Notion AI or Mem. If you're comfortable with Docker and have a GPU box or an Apple Silicon Mac (M1 or above), it's a genuinely private way to keep AI on your own infrastructure. Official images live on GHCR, and the project exposes a REST API plus Apple Shortcuts and Android intents.
Behind the Verdict
The honest question with any local-first AI tool is whether the privacy payoff justifies the setup tax. For Eclaire, it increasingly does. The v0.6.0 single-container deploy with optional Redis and SQLite removes the multi-service dance that made earlier versions tedious, and v0.4.0's Apple Silicon path via MLX-LM and MLX-VLM means a Mac Studio is now a first-class host rather than a workaround. Pick Eclaire when your data can't leave your network and you still want the assistant to actually do things — search the doc library, extract fields from a scanned PDF, tag a photo archive, schedule a recurring task. The five-modality scope (tasks, notes, docs, photos, bookmarks) is the differentiator; most self-hosted assistants stop at chat over text. Pass if you want zero-setup. There is no hosted version, and the FAQ is blunt about it — self-host only, with business consulting as the escape hatch. If you don't have a GPU or an M1-or-later Mac, or you'd rather not maintain a Docker container, a cloud assistant will beat this on convenience every time. The closest comparison is running a local model behind Open WebUI or LM Studio directly. Eclaire's edge is the opinionated data layer — OCR, classification, tagging, and automations wired to real objects instead of a blank chat box. Where it bites: model quality is your responsibility, and the memory footprint scales with whichever Qwen, Gemma, Deepseek, Kimi, or Llama model you load. Choose a bigger model and a modest box will struggle. The project also moves fast — three releases in roughly three months — so expect to track upgrades rather than set and forget. For teams, the Business track offers custom-trained models, private cloud deployment, custom integrations, and onboarding support, which is the realistic route for
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Real-world workflow fit
Concrete scenarios for the personas Eclaire actually fits — and what changes day-one when you adopt it.
You want to build a private knowledge base from web bookmarks and documents, with AI Q&A and summaries, without cloud exposure.
Outcome: Deploy Eclaire via Docker, fetch bookmarks and upload PDFs, then ask the assistant to summarize a report or find a quote; all data stays local.
You want to automate tasks and integrate with your existing workflow via shortcuts and API.
Outcome: Connect Apple Shortcuts or Android intents to create tasks, use the REST API to push data, and let AI schedule and prioritize your tasks.
You need a private AI assistant for team collaboration without external data processing.
Outcome: Run Eclaire on an internal server, onboard team members, and use shared tasks, notes, and document Q&A with full data sovereignty.
Use Cases
- Securely manage and search personal documents and notes with local AI.
- Automatically organize and tag a large photo library using OCR and object detection.
- Create a private knowledge base from bookmarks, fetching and indexing web content.
- Automate recurring tasks and integrate with Apple Shortcuts or Android intents.
- Deploy a self-hosted AI assistant for team collaboration with complete data sovereignty.
Models Under the Hood
as of 2026-09-15
Limitations
- Eclaire is a self-hosted, open-source AI assistant that requires deployment on your own infrastructure, such as via Docker.
- It relies on local or connected AI models that you must provision and manage.
- Mobile access is provided through a PWA and share sheets rather than native apps.
as of 2026-08-29
Verification history
We have re-verified Eclaire 6 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Eclaire tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free (Self-Hosted)
$0/mo
Ideal for
Individuals or small teams who are comfortable with Docker and self-hosting, want full data control, and can invest time in setup.
What this tier adds
Starting tier: free, open-source, with unlimited local processing and multiple model support; no vendor hosting.
Business (Consulting & Managed)
Custom
Ideal for
Organizations that need custom AI models, private cloud deployment, and dedicated support for data sovereignty at scale.
What this tier adds
Adds custom-trained models, private cloud deployment, custom integrations, onboarding, and support; pricing is custom.
Where the pricing makes sense
The company stage and team size where Eclaire's pricing actually pencils out — and where peers do it cheaper.
Eclaire is free for self-hosters, making it cheaper than hosted productivity suites like Notion AI ($10/user/mo) or Mem, but you bear the hardware and setup costs. For business needs, custom consulting pricing is opaque; compare with self-hosted alternatives like Ollama or LocalAI.
Setup time & first value
How long it actually takes to get something useful out of Eclaire — broken out by persona, not the marketing-page minute.
Docker-savvy users: 15–30 minutes to get a basic instance running (single-container v0.6.0). Mac users on Apple Silicon: add model setup via MLX/LM Studio, roughly 30–60 minutes to full functionality. Non-technical users may take 2–4 hours or more to configure hardware and models.
Switching to or from Eclaire
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Notion or OneNote: Export your notes and documents, then upload them into Eclaire's Notes and Documents sections; bookmarks can be imported manually.
- →From browser bookmarks: Export HTML bookmarks and import them into Eclaire for offline reading and metadata extraction.
- →From a local photo folder: Upload photos via the Bulk Upload feature; Eclaire will auto-tag and OCR them.
- ↗To Notion or Mem: Export your data from Eclaire via the client or API, then import into your new system.
- ↗To a different self-hosted tool: Use the REST API to export your assets and documents as needed.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Eclaire”, and we withheld 6: 6 could not be judged, because “Eclaire” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Eclaire.
Official links
Tools that pair well with Eclaire
Common stack mates teams adopt alongside Eclaire, with the specific reason each pairing earns its keep.
Featured Head-to-Head Comparisons
Eclaire vs Genspark
For privacy-first users who want a self-hosted personal assistant managing tasks, notes, photos, and bookmarks locally, Eclaire is the clear choice. If you need a cloud-based all-in-one workspace for research, content creation, and automation with no coding required, Genspark offers a richer set of integrated AI apps. Your decision hinges on whether you prioritize data sovereignty or a turnkey feature set.
Eclaire vs Air Ai
These tools serve completely different markets. If you're in defense procurement needing to compress materiel release from 15 months to 3 months, Air is the obvious choice (pricing requires contact). For privacy-conscious individuals who want a local AI assistant for notes, documents, and photos without cloud dependency, Eclaire is free and open-source. Buyers in commercial enterprises without defense ties have no reason to consider Air.
Eclaire vs Truleo
Eclaire vs Presto Voice
Eclaire vs Locus Robotics
Eclaire vs B Rokratt
Choose Bürokratt if you're an Estonian citizen or e-resident needing a free, secure gateway to government services. Pick Eclaire if you're a privacy-focused individual or techie wanting a local, open-source AI assistant for personal productivity — especially after its recent v0.6.0 update that simplifies deployment.
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