Natively

Overview

Natively is a local-first AI interview assistant and meeting copilot engineered for technical professionals who require real-time assistance without compromising privacy. Unlike cloud-only tools, Natively processes screen capture, audio transcription, and language model inference entirely on your own device — on macOS or Windows. This architecture provides zero cloud exposure, complete data control, and the ability to run interviews in airplane mode with no internet connection at all.

At its core, Natively delivers real-time coding interview help through a discreet system-level overlay that remains invisible to screen-sharing software and video platforms. It reads on-screen problems via local OCR, analyzes algorithmic questions, and surfaces suggested approaches, code snippets, and Big-O complexity breakdowns. It also provides live transcription, automatic meeting notes with action items and decisions, and resume- and job-description-aware guidance. For system design questions, it offers structured breakdowns covering scalability, component architecture, database choices, caching strategies, and trade-offs. Behavioral questions benefit from STAR-format suggestions aligned to the target role.

Natively offers a unique three-mode flexibility: fully local execution via Ollama with models like Llama, Mistral, CodeLlama, and Gemma — generating zero outbound network traffic; bring-your-own-key (BYOK) support for OpenAI, Anthropic, Gemini, or Groq to leverage frontier models with a 2M-token context window; or the managed Natively API with hosted speech-to-text and LLM. Users are never locked into a single vendor; any OpenAI-compatible endpoint such as vLLM, LM Studio, OpenRouter, or DeepSeek can be connected. The app works seamlessly with Zoom, Google Meet, and Microsoft Teams without appearing as a participant.

Natively is free and open source (AGPL-3.0), with no account or credit card required for the local and BYOK tiers. It is purpose-built for coding interviews, system design discussions, take-home assessments, and meeting assistants, making it an ideal choice for engineers preparing for technical roles, privacy-focused professionals, and remote workers seeking an invisible, reliable AI co-pilot that runs entirely on their own hardware.

Core capabilities

Real-time coding interview assistance

Provides live code suggestions, algorithmic approaches, and Big-O analysis during technical interviews.

Invisible system overlay

Runs as a discreet native overlay that is undetectable by interviewers and screen-sharing software.

100% local mode with Ollama

Execute LLMs fully offline on-device with zero cloud exposure and zero outbound network traffic.

Bring-your-own-key (BYOK)

Connect OpenAI, Anthropic, Gemini, or Groq keys for cloud-grade AI without monthly subscription lock-in.

Live transcription and smart meeting notes

Automatically generates structured meeting notes with action items, key decisions, and highlights.

Resume and job description awareness

Tailors suggestions based on the specific role, expected tech stack, and interview context.

Works with major conferencing platforms

Operates on top of Zoom, Google Meet, and Microsoft Teams without injecting into calls.

Free and open source

AGPL-3.0 licensed, with no account or credit card required for the free tier.

Multi-model flexibility

Supports local models via Ollama or any OpenAI-compatible endpoint like vLLM, LM Studio, OpenRouter, and DeepSeek.

Cross-platform support

Available natively on macOS (Apple Silicon and Intel) and Windows, with Linux in development.

Use cases

LeetCode-style algorithmic coding interviews

System design interviews requiring structured architecture breakdowns

Behavioral interviews with STAR-format guidance

Take-home assessments and open-book technical evaluations

Online meetings requiring automatic transcription and action items

Interview practice and confidence-building in a private environment

Airplane-mode / offline interview scenarios with zero network footprint