AI Native Product Insights – 2025W35

🏅 Product Hunt Data

Ranking: 2025W35-rank9
Upvote: 493

🚀 Product Overview

TraceRoot.AI is an open-source, AI-native observability platform designed to streamline debugging by connecting logs, traces, metrics, code, and team conversations. It not only detects issues — it proposes fixes, tightly integrated with GitHub workflows.

📋 More Details

Created by developers for developers, TraceRoot centralizes telemetry data and reduces cognitive load by using AI agents to correlate signals, explain the root cause, and even draft pull requests. It optimizes debugging with context-aware reasoning and supports both cloud and self-hosted deployments.

📊 Evaluation

AI Native Application Modernization: 92/100
AI powers the platform’s core functionality — from resolving observability signals to drafting actionable fixes — making automation and developer experience central to its architecture.

🔗 Website

https://traceroot.ai/?ref=producthunt

🏅 Product Hunt Data

Ranking: 2025W35-rank11
Upvote: 485

🚀 Product Overview

Rube is a universal AI-native command platform that lets users trigger actions across 600+ apps directly from conversational interfaces like Claude, ChatGPT, or VS Code. It removes friction from tool execution by handling authentication, permissions, and app context inside the chat.

📋 More Details

Many AI assistants get stuck at conversation—they can advise, but not act. Rube changes that by giving your AI the ability to execute multi-step workflows across tools like Slack, GitHub, Asana, and Google Slides. With parallel task execution, memory of user workflows, and no-code setup, Rube turns your language model into an actual operator.

📊 Evaluation

AI Native Application Modernization: 92/100
Rube is deeply AI-native: rather than augmenting legacy tools, it builds on top of LLMs as the core interface and control plane. It empowers models to act, not just predict—bridging intelligence and execution with a well-architected MCP layer.

🔗 Website

https://rube.app/?ref=producthunt

🏅 Product Hunt Data

Ranking: 2025W35-rank12
Upvote: 479

🚀 Product Overview

Roark is a QA and observability platform purpose-built for Voice AI. It helps teams test, monitor, and iterate on voice agents by capturing real-time call data, running AI-driven evaluations, and generating test cases from failed calls. Designed to improve agent reliability across diverse speakers and scenarios.

📋 More Details

The Roark team built this product to address common development challenges: manual testing, missing monitoring, and unpredictable regressions. It enables detailed simulation across accents, languages, and speech profiles, supports 40+ call metrics, and integrates seamlessly via SDK/API. With 10M+ minutes processed, Roark powers companies like Aircall and Radiant Graph.

📊 Evaluation

AI Native Application Modernization: 92/100
Roark is an AI-native platform—AI models are integral for speech analysis, evaluation automation, and persona simulations. Rather than adding AI features on top, Roark is built entirely around enabling voice AI teams with continuous testing and learning workflows.

🔗 Website

https://roark.ai/?ref=producthunt

🏅 Product Hunt Data

Ranking: 2025W35-rank16
Upvote: 397

🚀 Product Overview

HiveMind is an AI-powered hiring platform built for skill-based talent screening. It automates resume review, assessments, and interview scheduling to return a ranked shortlist of qualified candidates—no manual vetting required.

📋 More Details

Created by the founding team of RocketDevs, HiveMind was born out of the pain of scaling technical hiring. Unlike traditional ATS tools that sit idle, it activates intelligent workflows the moment a candidate applies, handling assessment delivery, follow-ups, and more. It’s workflow-first and designed as a true assistant, not just a digital spreadsheet.

📊 Evaluation

AI Native Application Modernization: 91/100
HiveMind is deeply AI-native, built as an autonomous agentic system from the ground up. Its resume parsing, assessment orchestration, and decision logic operate continuously without human intervention—making AI central to both workflow and value delivery.

🔗 Website

https://gethivemind.ai/?ref=producthunt

🏅 Product Hunt Data

Ranking: 2025W35-rank27
Upvote: 218

🚀 Product Overview

gpt-realtime is OpenAI’s cutting-edge speech-to-speech model designed for production-level voice agents. It delivers expressive, natural audio responses with low latency, making real-time voice interactions significantly more compelling.

📋 More Details

Unlike traditional systems that transcribe audio to text before generating responses, gpt-realtime utilizes a voice-in, voice-out approach—processing speech signals end-to-end. This enables more accurate handling of tone, pauses, and emotional nuance. The API is now generally available, supporting features like remote MCP, image input, and SIP calling, further supporting scalable voice-based applications.

📊 Evaluation

AI Native Application Modernization: 93/100
This product exemplifies AI-native design. The generative model at its core handles raw audio as both input and output, eliminating traditional intermediary steps. It’s a fundamental leap toward human-like multimodal interaction.

🔗 Website

https://openai.com/?ref=producthunt

🏅 Product Hunt Data

Ranking: 2025W35-rank29
Upvote: 263

🚀 Product Overview

Google’s Gemini 2.5 Flash Image, affectionately called “nano-banana🍌”, is a new state-of-the-art generative vision model. It sets a new benchmark for character consistency, seamless multi-image fusion, and nuanced image editing with natural language prompts.

📋 More Details

The model grabbed attention on LMArena even before its official reveal. Its standout feature—maintaining character fidelity across generations—won praise from early users. With capabilities extended by Gemini’s world knowledge, it offers a powerful multimodal experience available through API, Google AI Studio, and the Gemini app.

📊 Evaluation

AI Native Application Modernization: 92/100
Built from the ground up as a generative AI-first vision system, Gemini 2.5 Flash Image demonstrates mature integration of foundational models, multimodality, and real-world inference, marking it as a fully AI-native product.

🔗 Website

https://www.google.com/?ref=producthunt

🏅 Product Hunt Data

Ranking: 2025W35-rank49
Upvote: 155

🚀 Product Overview

Qwen Chat is a conversational AI that now enables real-time webpage reading. Just paste a URL into the chat, and the system will fetch and analyze the page content contextually, turning the browser into a multimodal assistant.

📋 More Details

Qwen-VL enhances the product’s capabilities across vision-language scenarios: image-based Q&A, math problem solving from images, video comprehension, object detection, document parsing into structured HTML, and multilingual OCR across 11+ languages. Strong spatial and semantic understanding make it versatile for education, media, and enterprise content workflows.

📊 Evaluation

AI Native Application Modernization: 90/100
Qwen Chat is deeply AI-native—web content analysis and understanding are powered end-to-end by multimodal and language models. The product architecture tightly integrates generative AI for parsing, summarizing, and interacting with unstructured data.

🔗 Website

https://chat.qwen.ai/?ref=producthunt