Didon vs Reyn

Didon and Reyn are both personal assistants tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Didon

Didon runs as a background process on Mac, takes periodic screenshots, and feeds them through a locally-hosted Qwen-3-VL:2b model that writes a structured work journal without any manual input. You define your projects and activity categories upfront; the AI slots every window, file, and task into that context as the day progresses. The resulting logs are queryable in plain language and exportable to CSV for billing or reporting. The local-only architecture means your screen data never leaves the machine — a meaningful distinction if you're working on client material under NDA. The single-device license and Mac-only availability are hard ceilings for anyone working across machines or on Windows.

Reyn

Reyn passively records screen activity and surfaces it through a Q&A interface — ask what you worked on yesterday, and it pulls an answer from your actual session history, not from a search index you remembered to populate. A morning email digest recaps open items and recent completions, so you're not reconstructing your week at standup. The workflow capture feature watches you complete a process once, then documents the steps — which is useful for handing off SOPs without writing them from scratch. The hard ceiling appears the moment you need this on Windows or in a team context: Reyn is Mac-only and the data model is per-device, not shared. Teams that need collaborative activity logging or cross-platform coverage will find no path forward here.

Attribute	Didon	Reyn
Pricing	Paid	Paid
Price	€89 one-time (lifetime access)	$20/mo
Free trial	No	No
Open source	No	No
Has API	No	No
Self-hosted option	No	No
Platforms	macOS	Mac
Pros	All screen analysis runs locally via Qwen-3-VL:2b, so screenshots and work data never reach an external server — which means client confidentiality obligations do not conflict with using the tool. Context-aware categorization lets you define your own project names and activity types upfront, so the AI logs time against your actual work structure rather than generic app categories you have to remap later. Auto-launch and auto-pause tied to system sleep means tracking starts from the first minute and stops the moment you step away, so idle time does not inflate your reported hours. Plain-language queries against the work journal let you ask 'how much time did I spend on Acme this week' without building a report — which matters on a Friday when a client asks and you need an answer in two minutes. CSV export of daily logs is included without restriction, so billing reconstruction and end-of-month invoicing do not require a manual audit of your own memory.	On-device screen journaling means your screen contents — client work, code, internal docs — never transit a vendor's cloud, so you get AI-powered recall without the data exposure that cloud activity trackers carry. Live screen context at query time, not just historical indexing, so answers about 'what am I looking at right now' are grounded in the actual present state of your desktop rather than a stale snapshot. Workflow capture documents a process from a single live run-through, so you can hand off SOPs to a teammate without separately writing documentation after the fact. Morning email digest surfaces open items and recent completions automatically, so you're not reconstructing your week from memory at the start of each day. Multi-provider AI support, so you're not locked to one model vendor — if API costs or model quality shift, you switch providers without changing how your screen data is stored.
Cons	The license covers installation on one machine only. If you work across a laptop and a desktop on the same day, one machine goes untracked — there is no sync or secondary-device option, and the only workaround is running separate instances under separate purchases. Windows support does not exist in the shipping version — only a waitlist. A team where even one member is on Windows cannot standardize on Didon, and those users have to maintain a separate tracking workflow entirely. The natural language query interface operates against the locally stored log files, but there is no described API or external integration path. Teams that need time data flowing into a project management tool, accounting system, or calendar will be copying CSV exports by hand until integrations ship — a task the vendor lists as upcoming but not yet available. The local LLM is fixed at Qwen-3-VL:2b. There is no described option to swap in a different model if analysis accuracy on your specific workflow proves inconsistent. Teams that try the tool and find categorization errors on niche technical work have no tuning lever beyond adjusting the context configuration.	Reyn is Mac-only with no Windows support or self-hosted option described anywhere on the vendor page — a user who splits their work across platforms loses the journal entirely for their non-Mac sessions, and there is no documented path to extend coverage. The data model is per-device and there is no API or shared workspace feature, which means workflow documentation captured by Reyn cannot be accessed by a teammate directly from the tool — teams expecting a shared activity log or collaborative SOP repository will need a separate system, at which point Reyn becomes a personal note-taking layer rather than a team workflow tool. AI inference routes through external model providers, so the local-first claim applies only to raw screen data — queries still require an outbound call to whichever AI provider you configure, which means teams operating in fully air-gapped environments cannot use Reyn as described.

Bottom line

Didon and Reyn are closely matched on pricing model, openness, and API availability — pick by feature set and platform support in the table above.

Frequently asked questions

What is the difference between Didon and Reyn?

Didon is Paid, while Reyn is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Didon better than Reyn?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

Didon vs Reyn: which should I pick?

Pick Didon if its pricing model, openness, or platform fit matches your constraints; pick Reyn otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.