AirJelly Review 2026: The AI Assistant That Watches Your Screen So You Don't Have To
A trigger-based macOS assistant that captures context when you press Enter — not all day. We reviewed its dual-layer memory, local-only storage, and whether it earns a spot on your dock.
Reviewed by the ToolRadar Editorial Team · Independent analysis based on official documentation and verified user feedback
AirJelly arrived on Product Hunt in June 2026 with a premise that sounds familiar: an AI assistant that watches your screen, remembers everything, and helps before you ask. But beneath the tagline sits a genuinely different mechanical choice — instead of continuously recording your display, it captures context only when you press Enter. That small pivot, built by an 11-person Beijing team led by a former ByteDance product manager, cuts daily screenshot volume from roughly 1,500 to about 300 and frames AirJelly as a context-aware layer rather than a surveillance tool.
The question is whether that design decision is enough to justify a spot on your dock. AirJelly is currently free for macOS only, with Windows and Linux builds in development. It stores everything locally, runs a dual-layer memory system, and promises proactive suggestions. We reviewed the public documentation, launch materials, and early user reactions to see where it stands in the crowded "AI second brain" market.
The Real Innovation Isn't the AI — It's the Trigger. Every "AI that watches your screen" pitch runs into the same wall: constant recording is expensive, privacy-invasive, and mostly captures noise. AirJelly's answer is refreshingly mechanical rather than magical — it just waits for the moment you press Enter, the natural point where a human has already decided something is worth committing to. That's a five-fold cut in screenshots compared to full recording, and it means the "intelligence" isn't guessing what matters — you're telling it, just by doing what you were already going to do anyway.
What Is AirJelly?
AirJelly is a desktop AI assistant developed by Low Entropy AI, a startup founded by Bert, previously a product manager at ByteDance who led the context-engineering product MineContext. The company, backed by Five Rings Capital, operates out of Beijing with an 11-person team. It launched on Product Hunt on June 22, 2026, earning 139 upvotes and placing #8 on that day's leaderboard. The tool positions itself in the emerging "AI Chief of Staff" category — not a chatbot you query, but a background layer that observes your workflow across apps and surfaces tasks, reminders, and summaries without being asked.
Core Features & How It Works
Enter-Key Intent Capture
Instead of passive 24/7 screen recording, AirJelly captures context at the moment you press Enter. This models each capture as an "Event" and summarizes it into a "Task," cutting daily screenshots from ~1,500 to ~300. The approach treats the Enter key as a human intent signal rather than relying on AI to guess what matters. For example, when you send a Slack message or commit a code change, AirJelly logs that as a meaningful action worth remembering.
Dual-Layer Memory System
Static information like people and projects is stored as "Entities," while dynamic information is stored as "Tasks." Retrieval combines vector search, keyword search, and time-decay weighting. All data is stored locally on-device, with no cloud upload. If you ask "What did Sarah say about the Q3 budget?" AirJelly searches across Entities (Sarah, Q3 budget) and Tasks (recent conversations) simultaneously.
Proactive Triggering
Rather than waiting for a prompt, AirJelly recommends next steps based on task updates. If it detects a meeting on your calendar, it prepares a brief with background context and recent work. If it sees a conversation about a deadline, it creates a follow-up task automatically. The system surfaces these suggestions through a lightweight overlay, not a disruptive popup.
Cross-App Context Awareness
AirJelly reads across Slack, Zoom, Google Docs, Calendar, email, and more. It generates end-of-day reports, maintains a searchable timeline, and tracks relationship context across conversations. The goal is a unified memory layer that spans your entire digital workspace. All processing happens locally using on-device models, meaning your data never leaves your Mac.
Pricing & Availability
| Plan | Price | What's Included |
|---|---|---|
| Free Beta | Free | macOS only, Enter-key capture, dual-layer memory, proactive triggers, local storage, daily reports |
| Team Edition | TBA | Multi-user support, shared Entities, admin controls, team timeline (planned) |
| Enterprise | TBA | Custom integrations, SLA, dedicated support, advanced security controls (planned) |
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Pros & Cons
✓ What Works
- ✅ Enter-key trigger cuts screenshot noise by ~80% versus full screen recording
- ✅ Dual-layer memory (Entities + Tasks) with vector and keyword retrieval
- ✅ 100% on-device storage — no cloud upload, no training on user data
- ✅ Proactive next-step suggestions without waiting for prompts
- ✅ Free during beta with no feature gating
✗ What Holds It Back
- ❌ macOS only — Windows and Linux versions are not yet shipped
- ❌ No published pricing roadmap; post-beta cost is unknown
- ❌ Privacy correction workflow remains unresolved (Xuefei Mei's question on Product Hunt went unanswered)
- ❌ 11-person team with limited track record at scale
- ❌ Requires macOS Accessibility permissions, which some enterprise IT policies block
💡 Community Feedback
How AirJelly Compares
| Feature | AirJelly | Notion AI | Rewind (Limitless) |
|---|---|---|---|
| Screen Capture Method | Enter-key trigger (~300/day) | None — manual input only | Continuous recording |
| Data Storage | 100% local on-device | Cloud (AWS US) | Cloud + local hybrid |
| Proactive Assistance | Yes — task-based suggestions | No — reactive only | Limited — search-based |
AirJelly sits in a narrow but valuable middle ground. Notion AI is powerful for document summarization but captures nothing automatically — you must write or paste content first. Rewind captures everything continuously, which creates a comprehensive archive at the cost of privacy fatigue and higher compute bills. AirJelly's Enter-key compromise offers a pragmatic third path: high-signal context without the creepiness of a camera that never blinks. The trade-off is platform lock-in to macOS and a team too small to guarantee rapid feature expansion.
Learning Curve
AirJelly's learning curve is shallow for a tool in this category. Installation requires granting macOS Accessibility permissions — a single toggle in System Settings that takes under a minute. The Enter-key mechanic is intuitive because it requires no behavior change; you press Enter exactly as you already do. Most users report understanding the timeline, task list, and proactive alerts within 15 to 20 minutes of first launch. Compared to Screenpipe, which demands configuration of OCR pipelines and storage rules, or Rewind, which ingests everything and requires heavy search filtering, AirJelly's opinionated workflow is easier to adopt. The friction point is not the tool itself but the mental shift of trusting an AI to read your screen at all.
Who Should Use It
Ideal User: macOS power users who live in documents, Slack, and email — particularly solo founders, researchers, PhD students, and product managers who need context continuity across apps without manually organizing notes. If your workflow involves jumping between Google Docs, Calendar, and Slack threads, AirJelly's cross-app memory layer removes the burden of context-switching.
Look Elsewhere If: You are on Windows or Linux, you work in an enterprise with strict IT policies against Accessibility permissions, or you are privacy-paranoid and want an open-source, auditable codebase. Teams needing multi-user collaboration should also wait for the planned Team Edition, as the current build is strictly single-user.
Expert Editorial Opinion
The Enter-key trigger is AirJelly's most defensible technical decision. Most "AI memory" tools fall into one of two traps: continuous recording creates privacy fatigue and compute bloat, while manual input defeats the purpose of automation. By capturing at the moment of commitment — the Enter press — AirJelly gets high-signal context without the creepiness of a camera that never blinks. It is a product-design insight that feels obvious in retrospect and rare in practice.
The dual-layer memory architecture is solid in theory. Separating static Entities from dynamic Tasks mirrors how human memory actually works: you remember people and projects differently than you remember to-do items. The combination of vector search, keyword search, and time-decay weighting is a pragmatic retrieval stack. However, the lack of published benchmarks on retrieval accuracy — precision, recall, or latency figures — makes it impossible to verify whether this works at scale or degrades after months of use.
AirJelly's market positioning is smart but crowded. The "AI Chief of Staff" category already includes well-funded players like Lindy, bonded agents like Bond AI, and horizontal tools like Notion AI. AirJelly differentiates through its local-first, trigger-based approach, but that same differentiation limits its addressable market to macOS users willing to grant deep system permissions. An 11-person team with a single funding round from Five Rings Capital has limited runway to build Windows, Linux, and team features before competitors close the gap.
The pricing gap is the largest unanswered question in this review. AirJelly is currently free, which is generous, but there is no published roadmap for when or how that changes. The tool captures screenshots, runs local AI models, and maintains a vector database — all compute-intensive operations. If the post-beta price lands above $15 per month, it competes directly with Screenpipe's $400 lifetime license and Rewind's $19 monthly plan. If it lands below $10, the team may struggle to monetize enough to sustain development. The absence of a pricing page is not a strategy; it is a liability for users making adoption decisions.
Is AirJelly worth adopting without a guaranteed free tier? For macOS users who need proactive context today, the answer is cautiously yes — the beta offers genuine value at zero cost, and the local-storage promise reduces lock-in risk. But for anyone building a long-term workflow around this tool, the uncertainty is material. If the team pivots to a high per-seat price or introduces cloud features that break the local-only promise, early adopters face a painful migration. Our recommendation: adopt AirJelly as a beta experiment, not as infrastructure.
Final Verdict
AirJelly delivers a genuinely thoughtful approach to screen-aware AI assistance. The Enter-key trigger, dual-layer memory, and local-only storage are real technical strengths that solve problems its competitors ignore. But the macOS-only limitation, unanswered privacy-correction workflow, and complete absence of pricing transparency hold it back. It is a promising beta from a small team with good instincts — not yet a platform you can build a company around.
Technical Quality: 7.5/10 · Price / Value: 6.5/10 · Maturity / Documentation: 6.5/10
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❓ Frequently Asked Questions
Would you let an AI watch your screen if it only looked when you hit Enter?
AirJelly is betting that the answer is yes — and that the Enter key is enough of a privacy valve to earn your trust. The next six months will tell whether that bet pays off, or whether users decide that any screen watcher, however polite, is still a watcher.
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