Interview Copilots That Don't Store Your Data on Someone Else's Server

I started looking at interview copilots after my third phone screen in a week where I blanked on a system design question I definitely knew the answer to. Pressure does that. You know the material, you've built the systems, but when someone's evaluating you in real time, your brain decides to forget how a load balancer works.

So I tried the popular ones. Cluely, Final Round AI, LockedIn AI. They all do roughly the same thing - listen to your interview audio, transcribe it, feed the question to an LLM, show you a suggested answer. Some of them charge $75 to $150 a month for this. Some of them had a data breach.

Here's what actually happened when I tried them.

The cloud problem

Most interview copilots send your audio and transcripts to their servers. That's how they work - the AI processing happens on their infrastructure, not yours. The trade-off is convenience for control. You paste in your resume, your job description, your personal stories about that production outage at 3 AM. All of it lives on their servers.

Cluely's pricing page lists $20/month for the basic plan. Stealth mode (hiding the app during screen sharing) is a separate $75/month tier. Final Round AI charges $149/month for their basic plan, $96/month if you commit quarterly. LockedIn AI runs $55/month, or about $50 if you pay quarterly.

For a job search that lasts 2-3 months, that's $225 to $450 on the low end. And your interview data - every answer you gave, every company you interviewed with, every question they asked you - stays on their servers after you cancel.

What changed in 2025

In mid-2025, Cluely had a data breach. The details are widely reported - interview transcripts and screenshots from around 83,000 users were exposed. It was a bad look for the whole category, not just Cluely. If you're storing interview recordings on a server, that server can get breached. That's not a Cluely problem, that's an architecture problem.

After that, a bunch of alternatives popped up. The market split into two camps. Cloud-based tools that charge a monthly subscription and process everything on their servers. And BYOK tools (bring your own key) that run locally and let you use your own API key with whatever AI provider you want.

The BYOK approach

BYOK means the app doesn't have its own AI service. You paste in your Anthropic key, your OpenAI key, or you point it at Ollama running on your own machine. The app sends your prompts directly to the provider you chose. No middleman server. No subscription. You pay the AI provider directly for what you use - usually about $1 to $2 per interview session with Claude, less with cheaper models.

Two tools take this approach right now: Natively and Talqo.

Natively is open source, built on Electron, runs on Mac and Windows. It started as a clone of Cluely's interface (they say this openly in their GitHub README) and added features from there. Supports OpenAI, Claude, Gemini, Groq, DeepSeek, and Ollama. Free. Source code on GitHub.

Talqo is native macOS only. Built in Swift, not Electron. Also free, also BYOK. Supports Anthropic, OpenAI, and auto-detects local servers like Ollama and LM Studio. The difference: you can mix local and cloud per mode - fast answers from your machine, heavy analysis from the cloud.

Both store everything locally. No cloud servers involved.

Where they actually differ

I've used both. Here's what's different in practice, not in marketing copy.

Electron apps are memory hogs. Natively sits at 200-400 MB of RAM in my testing. Talqo runs at 50-80 MB. If you're running an interview on Zoom while also running a code editor, browser, and the copilot, RAM matters. Especially on a 16 GB MacBook.

On the audio side, Natively uses a Rust module for audio capture. Talqo uses Apple's CoreAudio Process Tap natively. Both work, but native macOS APIs integrate better with things like screen sharing permissions and audio routing. I had fewer issues with Talqo picking up the interviewer's audio correctly.

System design interviews are where I noticed the biggest gap. Most copilots give you a wall of text when the interviewer says "design a URL shortener." Talqo has a structured approach - it walks through requirements, entities, API, high-level design, then deep dives using a tiered solution format (here's why the obvious answer is bad, here's the good answer, here's the great answer). The output reads like how a senior engineer would actually present a system design, not like a ChatGPT response dump.

For coding rounds, Talqo detects the programming language from your screen instead of defaulting to Python. Small thing, but if your interviewer opened a Java editor, you don't want Python suggestions.

Talqo also lets you save complete session configurations - different system prompts, different AI models, different context files for different companies. If you're interviewing at five companies simultaneously (which, if you're job hunting in 2026, you probably are), this saves real time. Natively doesn't have presets.

There's also ambient analysis. Talqo runs a passive background check every 60 seconds during your interview, looking at what topics have been covered and what gaps remain based on the job description you loaded. It doesn't interrupt you. It just quietly updates a small strip showing "you haven't covered distributed systems yet" or "interviewer seems skeptical on this topic." I haven't seen any other tool do this.

Platform is the big trade-off. Natively runs on Mac and Windows. Talqo is Mac only. If you're on Windows, Natively is your only BYOK option right now.

The cloud options, honestly

If you don't care about local storage and you just want something that works with minimal setup, the cloud tools are more polished in some ways. You don't need to get an API key. You don't need to think about which model to use. You pay your subscription and it works.

Final Round AI has the largest user base (they claim 10 million users on their homepage, though that number is disputed). They have mock interview features, resume tools, and a lot of prep material beyond just the live copilot. If you're early in your career and need the full package, there's something to be said for that. But $149/month is a lot, and the basic plan only gives you 4 live sessions.

LockedIn AI has a "Duo" feature where you can invite a friend to help you during your interview alongside the AI. That's genuinely clever. They also let you pick between OpenAI, Claude, Gemini, and DeepSeek models, which is unusual for a cloud tool. $55/month, or about $50 quarterly.

Sensei AI runs as a Chrome extension, which means it works on any OS but also means it can't do stealth mode on desktop apps. If your interview is on a native Zoom app instead of browser Zoom, Sensei can't see it. $24/month annual, $89 monthly.

Interview Coder is the most expensive option at $299/month or $899 for lifetime access. It's focused entirely on coding interviews and LeetCode problems. If that's all you need, it's specialized. But $899 is a lot to spend on something you'll use for a few months.

Cost comparison

Assuming a 3-month job search with about 15 interviews:

The BYOK tools cost roughly 1/10th to 1/20th what the cloud subscriptions cost. The catch is you need an API key. If you've never done that before: go to console.anthropic.com, sign up, create a key, paste it into the app. Takes about a minute. They give you $5 in free credit to start.

What I'd pick

If you're on a Mac and you want the most structured interview help, especially for system design and coding rounds, Talqo. The preset system, ambient analysis, and structured methodology are things nobody else has. The fact that it's native Swift instead of Electron is a bonus - it's noticeably faster and lighter.

If you're on Windows or you want open source, Natively. No other option in this category.

If you want zero setup and don't mind paying, LockedIn AI has the best balance of features and price among the cloud tools. The multi-model support is a nice touch.

If you're applying to investment banking or finance roles, look at Superday AI. It's the only tool I've seen that actually understands DCF models and LBO questions.

Whichever you pick, think about where your data ends up. Interview transcripts have your personal stories, salary expectations, opinions about former employers, and the specific questions companies ask. Some of that is stuff you wouldn't even put in an email. Worth considering before you hand it to a third-party server that may or may not still exist in two years.