Eclaire is live · free plan; paid plans on request · last verified 26 Oct 2026 · viability healthy
Eclaire
Self-hosted AI assistant that unifies tasks, notes, documents, photos, and bookmarks on your own hardware.
Eclaire is the pick when data sovereignty is a hard requirement rather than a preference. Unifying five data types with OCR, extraction, and scheduled automations puts it ahead of most local-AI projects, and v0.6.0's single-container Docker removed the setup friction that used to justify skipping it. You still supply the hardware and the Docker tolerance, and there is no hosted fallback if your box goes down.
Verdict generatedVerified 4d ago · liveness 79/100 · cite: rightaichoice.com/tools/eclaire
- Privacy-focused professionals who want AI over tasks, notes, docs, photos, and bookmarks without cloud exposure
- Developers comfortable with Docker who want a self-hosted assistant exposing a REST API
- Small teams replacing Notion AI or Mem while keeping data on their own infrastructure
- Organizations with data residency rules needing private-cloud or on-prem deployment
- 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 want the assistant to live in someone else's cloud and start working in five minutes — Eclaire only exists self-hosted, and it expects you to bring an M1-or-later Mac or a GPU box plus Docker and model-selection know-how.
The software is free, but you pay for the hardware — a Mac Mini/Studio (M1 or above) or a Linux/Windows GPU machine is the real entry price, and memory needs scale with the models you pick.
The self-hosted tier is $0/mo — the whole product, open source — which puts Eclaire below Notion AI and Mem on sticker price and above them only in hardware and setup effort. Cost scales with the machine you buy and the models you choose, not with seats. For teams that need training, custom models, or a managed private cloud, pricing is quoted per engagement rather than published.
In short
Eclaire — Self-hosted AI assistant that unifies tasks, notes, documents, photos, and bookmarks on your own hardware. Best for Privacy-focused professionals who want AI over tasks, notes, docs, photos, and bookmarks without cloud exposure, Developers comfortable with Docker who want a self-hosted assistant exposing a REST API, Small teams replacing Notion AI or Mem while keeping data on their own infrastructure. Free to start; it also has paid plans whose price we could not confirm — see the pricing table.
What is Eclaire?
Eclaire — Self-hosted AI assistant that unifies tasks, notes, documents, photos, and bookmarks on your own hardware. Best for Privacy-focused professionals who want AI over tasks, notes, docs, photos, and bookmarks without cloud exposure, Developers comfortable with Docker who want a self-hosted assistant exposing a REST API, Small teams replacing Notion AI or Mem while keeping data on their own infrastructure. Free to start; it also has paid plans whose price we could not confirm — see the pricing table.
Eclaire is an open-source, local-first AI assistant that folds tasks, notes, documents, photos, and bookmarks into one workspace running on hardware you control. The pitch is straightforward: your files and images stay on your machine, and the assistant reasons over them in place rather than shipping them to someone else's cloud. It suits developers, privacy-minded professionals, and small teams who already self-host and want AI over their own data. The assistant searches, summarizes, organizes, and acts across five data types. Bookmarks are fetched and saved offline as readable PDFs with metadata extracted per platform. Documents get full-text search, summaries, extractions, and question answering across PDF, DOCX, XLSX, HTML, PPT, and Numbers. Photos receive automatic tagging, object detection, and OCR across JPEG, PNG, SVG, HEIC, and WEBP. Notes handle rich text and Markdown with AI-assisted creation, and tasks carry due dates and recurrence plus automation the assistant can execute on a schedule. Inference runs on open-source models including Qwen, Gemma, Deepseek, Kimi, and Llama, downloaded from Hugging Face or pointed at cloud inference APIs, with the option to switch models or run several at once. Deployment got substantially easier with v0.6.0's single-container Docker setup (optional Redis and SQLite), and Apple Silicon users get native acceleration via MLX-LM and MLX-VLM. Requirement is a Mac Mini or Studio (M1 or above) or a Linux/Windows box with a GPU; memory needs scale with whichever models you pick. Against hosted assistants like ChatGPT, Notion AI, or Mem, Eclaire trades setup effort and hardware cost for data sovereignty and no per-seat ceiling. For organizations with data residency rules, Eclaire Labs offers consulting, custom integrations, and private-cloud deployment rather than a hosted product.
Key features
- AI assistant that searches, answers, summarizes, and creates content across all workspace data
- Unified workspace for tasks, notes, bookmarks, documents, and photos
- Full-text search and question answering across PDF, DOCX, XLSX, HTML, PPT, and Numbers
- OCR text extraction from JPEG, PNG, SVG, HEIC, and WEBP images
- Object detection and automatic photo tagging and categorization
- Bookmark fetching with offline reading, PDF conversion, and metadata extraction
- Rich text and Markdown notes with AI-assisted creation and organization
- Task management with due dates, recurrence, and smart prioritization
- Assign tasks for the assistant to perform automatically on a schedule
- 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 including Qwen, Gemma, Deepseek, Kimi, and Llama
- Download models from Hugging Face or connect cloud inference APIs
- Run multiple models simultaneously and switch between them
- REST API for building custom integrations and extending the platform
Behind the verdict
Reach for Eclaire when the data can't leave the building. If your documents, photos, or notes are governed by a residency rule or a client contract, a cloud assistant is off the table before features even get discussed. The five-way unification is the real draw: most local-AI tools handle one data type, whereas Eclaire runs search and Q&A across documents, tags photos, and turns a bookmark into an offline PDF and then a summary. The automation layer is what separates it from a chat-with-your-files setup. Tasks carry due dates and recurrence, and you can hand work to the assistant on a schedule. In practice that means a nightly pass that classifies new documents, or a morning digest pulled from bookmarks and notes. It's a different workflow than asking questions in a window. Where it bites is everything around the model. You choose which of Qwen, Gemma, Deepseek, Kimi, or Llama to run, and memory pressure tracks that decision, so a Mac Mini that handles one model comfortably may struggle running two. Expect to babysit upgrades and container config if you're solo. v0.6.0's single-container Docker with optional Redis and SQLite cut most of that pain, but it didn't erase it. Set against Notion AI or Mem, you're trading polish and zero maintenance for control and the absence of a per-seat ceiling. Notion AI wins on writing quality inside a wiki you already use; Eclaire wins when the assistant must never phone home. Against a bare local model in Ollama, Eclaire's advantage is the plumbing around it: OCR, classification, metadata extraction, and schedulable actions that a raw model won't do for you. Our advice: start with the self-hosted free build on a machine you already own before committing a team to it. If it runs your photos and documents well for a month, the
Models under the hood
as of 2026-10-22
Limitations
- Eclaire requires deployment on your own infrastructure, such as via Docker, and you provision and manage the AI models it uses.
- Answer quality and processing speed depend largely on which models the admin selected, and larger models need more memory and compute.
- Hardware floor is a Mac Mini/Studio (M1 or above) or Linux/Windows with a GPU.
- Mobile access is a PWA with share sheets plus Apple Shortcuts and Android intents rather than native apps, and the official documentation is explicitly still a work in progress, so GitHub is the practical reference for setup and troubleshooting.
as of 2026-09-29
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Is Eclaire still active?
Eclaire is live · free plan; paid plans on request · last verified 26 Oct 2026 · viability healthy.
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: October 2026
How we score →What do users say about Eclaire?
What people actually say about Eclaire — is it worth it?
Our community sentiment research written Jul 31, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
How we verified this
Every listed fact about Eclaire— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 26 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Eclaire 8 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.
- — changed integrations, description, who it suits, features, summary, pricing tiers, who should skip it, our verdict
- — changed models
- — changed features, who it suits, description, our verdict, hidden costs, integrations, limitations, switching in, switching out, models, who should skip it, pricing fit, setup time, summary, use cases
- — changed SSL certificate
- — changed models, limitations
- — changed integrations, who it suits, who should skip it, description, pricing tiers, summary, our verdict, features
Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Eclaire cost in 2026?
Eclaire: Free to start; it also has paid plans whose price we could not confirm — see the pricing table. Pricing last verified 26 Oct 2026.
Plans compared
Every published Eclaire tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Self-Hosted (Open Source) | Free | — | — |
| Business (Consulting & Managed) | Custom | quote | Organizations with data sovereignty requirements that don't want to run the stack in-house and need industry-specific model tuning.Adds: Adds custom-trained models, private-cloud deployment with full data sovereignty, custom integrations and API development, and onboarding, training, and ongoing support, quoted per engagement. |
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.
Where the pricing makes sense
The company stage and team size where Eclaire's pricing actually pencils out — and where peers do it cheaper.
The self-hosted tier is $0/mo — the whole product, open source — which puts Eclaire below Notion AI and Mem on sticker price and above them only in hardware and setup effort. Cost scales with the machine you buy and the models you choose, not with seats. For teams that need training, custom models, or a managed private cloud, pricing is quoted per engagement rather than published.
Has Eclaire's pricing changed?
No plan price for Eclaire has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Eclaire?
Pick Eclaire if you are Privacy-focused professionals who want AI over tasks, notes, docs, photos, and bookmarks without cloud exposure, Developers comfortable with Docker who want a self-hosted assistant exposing a REST API, Small teams replacing Notion AI or Mem while keeping data on their own infrastructure, Organizations with data residency rules needing private-cloud or on-prem deployment.
Look elsewhere if you are 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, Teams that need a polished wiki editor and writing assistant rather than a data-workspace AI.
Skip it if Skip Eclaire if you want the assistant to live in someone else's cloud and start working in five minutes — Eclaire only exists self-hosted, and it expects you to bring an M1-or-later Mac or a GPU box plus Docker and model-selection know-how.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Eclaire actually fits — and what changes day-one when you adopt it.
Install the single-container Docker image from v0.6.0, point Eclaire at a model downloaded from Hugging Face, and drop in a folder of PDFs, receipts, and screenshots.
Outcome: Documents get full-text indexed with summaries and OCR runs over the images, so you can ask questions across the whole pile without any file leaving the machine.
Deploy Eclaire on an internal GPU box for the team, connect the Telegram notification channel, and use the REST API and API keys to hook in existing scripts.
Outcome: Tasks, notes, and bookmarks live in one self-hosted workspace with AI over all of it, and nothing is subject to a third party's terms or retention policy.
Generate an API key, wire up Apple Shortcuts on an iPhone or an Android intent, and assign recurring tasks so the assistant processes new content on a schedule.
Outcome: Bookmarks, notes, and photos get captured from mobile and land in Eclaire already tagged and classified, with scheduled AI actions running against them.
Use cases
- Search and question-answer across a personal document library without uploading anything to a cloud service
- Auto-tag and classify a large photo library using OCR and object detection
- Build a private, searchable knowledge base from saved bookmarks with offline reading and PDF export
- Schedule recurring tasks and automations the AI executes against your own content
- Deploy a data-sovereign AI assistant for a small team on internal hardware
- Wire Eclaire into Apple Shortcuts or Android intents to capture and query from a phone or watch
- Generate new notes and summaries from existing photos and documents on request
- Run several local models at once and route different jobs to different models
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.
On an M1-or-later Mac or a Linux/Windows GPU box, v0.6.0's single-container Docker deployment is the fastest path — expect an afternoon to get the container up, pick a model, and index a first batch of content. Teams adding custom integrations or a private-cloud rollout should plan on days to weeks, likely with Eclaire's consulting or managed deployment help.
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 Mem: export your pages and notes, import them as documents or notes in Eclaire, and let the assistant index them for search and Q&A.
- →From a cloud AI assistant like ChatGPT: replace the chat-over-uploaded-files workflow with local ingestion — add the same documents, photos, and bookmarks to Eclaire so the assistant reasons over them in place.
- →From a self-hosted notes or bookmark app: bulk upload existing content through the Upload view, which accepts bookmarks, documents, notes, and photos.
- →From browser bookmarks: add them to Eclaire so each is fetched, saved offline, converted to readable format or PDF, and metadata-extracted.
- ↗To a hosted productivity suite like Notion AI: export your notes, documents, and tasks through the client or API and re-import them, accepting that your data moves to a third-party cloud.
- ↗To a plain notes or task app: use the client or API data export to pull notes, tasks, and bookmarks back out, since you retain full ownership of the content.
- ↗To a different self-hosted assistant: export via the API and re-index your documents, photos, and bookmarks in the new system, reusing the same local models.
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
What are the best Eclaire alternatives?
The closest alternatives to Eclaire we list are Notion, Olares and Open Webui. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Notion | Freemium | Pricing not published | — |
| Olares | Freemium | Pricing not published | — |
| Open Webui | Freemium | Pricing not published | — |
Alternatives to Eclaire
View all
Notion
Notion is the AI workspace where docs, wikis, databases and agents that run on them share one system of record.
Olares
Olares is an open-source personal AI cloud OS for running local LLMs, agents, and self-hosted apps on hardware you own.
Open Webui
Open WebUI is the self-hosted AI interface for running Ollama, OpenAI, or Anthropic models on your own hardware.
Tools that pair well with Eclaire
Common stack mates teams adopt alongside Eclaire, with the specific reason each pairing earns its keep.
Notion
Notion is the AI workspace where docs, wikis, databases and agents that run on them share one system of record.
Olares
Olares is an open-source personal AI cloud OS for running local LLMs, agents, and self-hosted apps on hardware you own.
Open Webui
Open WebUI is the self-hosted AI interface for running Ollama, OpenAI, or Anthropic models on your own hardware.
Eclaire vs its closest rival
Eclaire's closest head-to-head is with 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. Verdict generated
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.
GeneratedEclaire 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.
GeneratedEclaire vs Truleo
These are not competing products and no buyer should be choosing between them. Truleo serves police agencies that need to triage open cases across jail calls, RMS, CAD, LPR, BWC and 140+ OSINT sources — it is investigative case intelligence priced around $100/month per connected application plus per-user seats, with a 60-day unlimited trial. Eclaire is a free, open-source, self-hosted personal assistant for developers and privacy-minded professionals who want AI over their own notes, docs, photos, and bookmarks. If you run a law-enforcement agency, evaluate Truleo; if you want a private local AI workspace on your own hardware, evaluate Eclaire. Buying one instead of the other isn't a trade-off — it's a category error.
GeneratedEclaire vs Presto Voice
These are not competitors, and no buyer should be choosing between them. Presto Voice is an enterprise, vendor-managed service that replaces headset order-taking at QSR drive-thru speaker posts and upsells add-ons to lift average check; it's sold on a contact basis and rolled out at scale across franchise locations — now reachable via the Toast Partner Ecosystem as of Sept 21, 2026. Eclaire is a free-to-start, open-source assistant you run yourself in a Docker container over your own notes, docs, photos, and bookmarks. If you run drive-thrus, evaluate Presto on non-intervention, upsell, and ROI reporting. If you want private AI over your own files, install Eclaire. There is no overlap in problem, buyer, or budget line.
GeneratedEclaire vs Locus Robotics
These are not competitors and no one is choosing between them. Locus Robotics sells physical warehouse automation — AMRs, LocusONE orchestration, and the new Locus Array Physical AI class for Robots-to-Goods fulfillment — to 3PLs and high-volume fulfillment centers under a contact-priced RaaS model. Eclaire is a freemium, self-hosted open-source assistant that runs local models (Qwen, Gemma, Deepseek, Kimi, Llama) over your own files. If you're automating a picking floor, only Locus applies; if you want private AI over your personal data, only Eclaire applies. Treat this page as two separate buying guides, not a head-to-head.
GeneratedEclaire 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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