Natively Review 2026: Open-Source Cluely Alternative — Honest Verdict
Rishabh JainNatively is the first credible open-source disruptor to Cluely — a free, AGPL-licensed desktop app that you self-install, point at your own OpenAI/Anthropic/Gemini key (or run fully offline via Ollama), and get a near-pixel clone of the Cluely overlay with stealth mode, screenshot OCR for coding rounds, and local RAG memory. With 9,000+ users, 1.1k GitHub stars, and zero ability to be breached on a server (because there is no server), the privacy story is genuinely different. The catch is friction: you'll need Node.js, Rust, the command line, and your own API keys. If you're comfortable with `npm install` and you'd rather not pay $149.99/mo, this is the most honest "free Cluely alternative" answer in 2026.
What is Natively?
Natively is an open-source desktop application that recreates the Cluely interview-copilot experience pixel-for-pixel — but as a free, self-installed, BYOK ("bring your own key") tool with no subscription and no central server holding your data. The project lives on GitHub at github.com/Natively-AI-assistant/natively-cluely-ai-assistant, with a marketing site at natively.software. It runs on macOS 12+ (Apple Silicon and Intel) and Windows 10/11, with Linux on the roadmap.
The maintainers report roughly 9,000+ users, 700+ daily active users, 1.1k GitHub stars, 256 forks, and 24 releases as of mid-2026, putting it well past hobby-project territory. The license is AGPL-3.0 — you can use, modify, and self-host it, but anyone who runs a modified version as a network service has to share their changes back.
Every other tool in this category is a closed-source SaaS that streams your audio and screen to their servers, charges $20–$150/month, and asks you to trust them with the most sensitive moment in your career. Natively flips that: the binary you run is the source you can read, the API keys are yours, and the meeting transcripts and RAG vectors live in a SQLite file on your own disk. There's literally no server-side database to breach. The trade-off is that you become your own IT department — install, updates, key management, and debugging are all on you.
Natively Pricing in 2026
Natively itself is free. The cost is whatever your chosen LLM provider charges per token plus your speech-to-text bill. For most candidates running 3–5 interviews a month on GPT-class models, that lands in the single-digit dollars — and if you use Ollama with a local model, it's literally $0:
- Bring your own OpenAI / Anthropic / Gemini / Groq key
- Or run 100% offline via Ollama (literally $0)
- Stealth mode included on every install (no paywall)
- Screenshot OCR + local RAG memory included
- No surprise annual charges — there's nothing to bill
- Compare: Cluely $149.99/mo, Final Round $149/mo, LockedIn $55–70/mo
Real-World Trade-offs (The Honest Cons)
Install requires the command line. The project ships a `git clone`, `npm install`, `npm run build:native`, `npm start` workflow. You'll need Node.js v20+, Git, and a Rust toolchain (for the native audio capture module). If "open Terminal and run a command" makes you nervous, this is not the tool to debug the night before an interview.
You manage your own API keys and quotas. If your OpenAI account hits a rate limit mid-interview, that's on you. If your Deepgram speech-to-text key expires, no support team is watching the dashboard. The maintainers respond on GitHub Issues — the median response time is community-paced, not enterprise SLA.
No mock-interview mode. The roadmap is explicit: Natively focuses on live real-time assistance and explicitly does not ship a structured prep/practice mode. If you want to rehearse with AI feedback before the real thing, you'll need a separate tool. As one community thread put it: "This is a copilot, not a coach."
No Linux build, no proctoring bypass. Linux support is "actively seeking maintainers" — meaning it doesn't exist. And the README is upfront that Natively is not designed to bypass dedicated proctoring software (Pearson VUE, ProctorU, Respondus Lockdown Browser). Those tools run at the OS level and are a different category entirely.
How Natively Compares on Detection
Because Natively is open-source, anyone — including recruiter-tooling vendors like Sherlock AI and FabricHQ — can read the source and write detectors against it. In practice, the project's lower public profile means most off-the-shelf "Cluely detectors" target Cluely-specific binaries and process names by default, not Natively's. The maintainers ship a process-name disguise feature that makes the app appear as Terminal, Settings, or Activity Monitor in process lists.
Realistically: any stealth tool is a moving target, and the openness that makes Natively trustworthy on privacy is the same openness that makes detection easier for anyone motivated. Self-host honestly with that in mind.
Natively Features
- Real-time transcription with sub-500ms claimed latency via a Rust-based native audio module
- Dual-channel audio — separates system audio (interviewer) from microphone (you) cleanly, so transcripts are correctly attributed
- Invisible overlay — hidden from Zoom, Google Meet, Microsoft Teams, and Webex screen sharing on every install (no paywall)
- Screenshot OCR — capture LeetCode / HackerRank / CoderPad problem images and pipe them to the LLM for analysis
- Local RAG memory — SQLite-backed vector search over your past meetings; ask "what did the recruiter say about comp last week" and it pulls the answer
- BYOK across providers — OpenAI (GPT-5.4, o3 series), Anthropic Claude 4.6, Google Gemini 3.1, Groq Llama, OpenRouter, DeepSeek, custom endpoints
- Speech-to-text choice — Google Cloud, Deepgram, ElevenLabs, Azure Speech, IBM Watson, Groq
- Fully offline mode — run inference via Ollama on a local LLaMA / Qwen / DeepSeek model with zero external network calls
- Process disguise — masquerades as Terminal, Settings, or Activity Monitor in the process list
- Custom persona modes — switch presets between technical, behavioral, sales, and recruiter personas
- Meeting intelligence dashboard — full transcript search, export, and historical browsing
- AGPL-3.0 license — fork it, audit it, modify it for your own needs
How to Install Natively
Step 1: Make sure you have node v20+, git, and a Rust toolchain installed (for the native audio module). On macOS, brew install node rustup-init covers it.
Step 2: Clone the repo: git clone https://github.com/Natively-AI-assistant/natively-cluely-ai-assistant and cd into it.
Step 3: Run npm install && npm run build:native. The Rust step compiles the audio capture module — give it a few minutes the first time.
Step 4: Create a .env file in the project root with your API keys (OpenAI / Anthropic / Gemini for the LLM, plus Deepgram or another STT provider). Or skip the cloud entirely and install Ollama with a local model like Llama 3.
Step 5: Run npm start. Grant microphone, screen-recording, and accessibility permissions when macOS prompts. The overlay opens — you're live.
At a Glance
- Genuinely free — no subscription, no upsell, no surprise annual charge
- Open-source AGPL-3.0 — you can read every line that touches your audio
- BYOK across OpenAI, Anthropic, Gemini, Groq, Ollama, OpenRouter
- Fully offline mode possible via Ollama (zero external calls)
- Local-first storage — transcripts and RAG vectors live on your disk
- Stealth mode + screenshot OCR + RAG bundled, no tier-locking
- ~9,000 users, 1.1k stars, 24 releases — actively maintained
- No server-side database = no breach surface
- Install requires Node.js, Rust, and command-line comfort
- You manage your own API keys, quotas, and rotation
- No support team — community-paced GitHub Issues only
- No structured mock-interview / question-bank mode
- No Linux build (roadmap, not shipped)
- Open source means detection vendors can audit it too
- Not designed to bypass OS-level proctoring (ProctorU, Respondus)
- Speech-to-text and LLM costs add up if you use cloud providers heavily
Natively vs Top Alternatives
| Feature | ||||
|---|---|---|---|---|
| Open source | Yes (AGPL-3.0) | No | No | No |
| Stealth pricing | $0 + API costs | Free tier | $149.99/mo | $149/mo |
| Setup friction | CLI, Node, Rust | Sign up + go | Installer | Installer |
| Question bank / prep | None | 10,000+ | None | Yes (paid) |
| Data location | Your laptop | Vendor cloud (no breach) | Vendor cloud (2025 breach, 83K users) | Vendor cloud |
| Offline mode | Yes (Ollama) | No | No | No |
| Support model | GitHub Issues | Email + chat |
Our Cluely alternatives guide compares the leading options in detail, including more open-source picks.
Natively vs Interview Sidekick — Deeper Comparison
These two tools are honestly aiming at different users. Natively is for the engineer who already lives in Terminal, has an OpenAI key on file, and would rather audit the source than trust a vendor — and accepts the trade that there's no question bank, no mock-interview mode, and no support team if the build breaks the night before a Google onsite.
Interview Sidekick is for the candidate who wants the privacy and pricing benefits without becoming their own DevOps. The free tier covers the same real-time copilot use case (Zoom, Google Meet, Microsoft Teams, Webex), but adds 10,000+ structured interview questions, AI-graded mock interviews, and a hosted dashboard you don't have to maintain. Sign-up takes a minute, no credit card, no `npm install`.
On security, both projects have meaningfully better stories than Cluely (which had a 2025 breach exposing 83K users) or Final Round AI. Natively's edge is that there's no cloud database at all — but only if you use Ollama; if you BYOK to OpenAI, your prompts still hit OpenAI's servers. Interview Sidekick stores transcripts in a vendor-managed Postgres with no public breach incidents, and lets you wipe sessions on demand.
On detection: Natively's open-source nature is double-edged. Anyone can read the source to write detectors, but in practice the lower public profile means it's less actively targeted than Cluely. Interview Sidekick has a similarly low recruiter-tool profile and isn't named in any public detection playbook we've found.
Most candidates will pick based on installation tolerance. If `git clone` and a Rust compile aren't friction for you, Natively is the most ideologically clean option in the category. If you want the same outcome with a sign-up form instead of a setup script, Interview Sidekick is the closer fit.
Want the open-source ethos without the install script?
Interview Sidekick has a free tier with no credit card, 10,000+ structured interview questions, AI mock interviews, and a real-time copilot. No subscription gate on stealth, no surprise annual charges, no recruiter-detection products targeting it — and you don't need to compile Rust to use it.
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