Deploy production-ready AI SaaS tools, hire vetted engineers with 100% Escrow milestone security, or earn recurring revenue as a certified sales partner.
Production copilots and automated workflows in 1 click.
Zero advance risk. Funds released only upon delivery.
Tailored enterprise architectures with 0% data leakage.
Silent real-time audio copilot that monitors Zoom, Teams, Meet & in-person meetings. It instantly queries your internal RAG knowledge vault and prompts the host with accurate answers as clients ask questions.
LiveAssist runs completely silently in the background. It transcribes incoming speech, filters casual small talk, queries your company docs (RAG) with AES-256 encryption, and prompts the speaker with verified talking points.
Define triggers, daisy-chain multiple AI nodes, and execute tasks autonomously (BYOK Model, 0% markup).
Client funds are safely held in Escrow and released only when deliverables pass automated validation.
Cloud SaaS, downloadable ZIP codebases, and custom enterprise AI engineering.
Silent in-meeting AI audio copilot with real-time RAG document retrieval & bilingual translation.
Multi-agent orchestration to automate customer tickets, data ETL, and business ops.
Hire certified senior AI engineers to build custom RAG, fine-tune LLMs, or integrate custom APIs.
Never risk advance payments. Your project budget is safely secured in Escrow and released only after the developer delivers clean, test-passing code approved by your team.
Specify milestones, stack, and deliverables.
Funds safely locked with 0% advance risk.
Developer delivers code verified via tests.
Payment disbursed only upon your confirmation.
Verified technical deep-dives, benchmark reports, and model releases.
Analysis2026-09-14© GateOfAI, LLC IBM Granite PatchTST-FM-r2: A Commercial-Friendly Forecasting Model IBM Research has released Granite Time Series PatchTST-FM-r2, an approximately 385M-parameter time-series model that ranks #2 overall on GIFT-Eval and #1 among permissively licensed commercial-friendly models. Gate of AI Editorial & Engineering Teams·2026-09-14·10 min read Key Takeaways Granite Time Series PatchTST-FM-r2 is an approximately 385M-parameter
Handpicked emerging AI technologies approved by experts.
Tool Review 2026-09-14 © GateOfAI, LLC GPT-6 Astra is an OpenAI model with dedicated developer guidance and published work focused on skills, prompting, and game creation. Current third-party reporting highlights its performance in computer use, front-end engineering, and general knowledge. At a Glance 🏢 Developer OpenAI 🤖 AI Type OpenAI frontier AI model for developer
Full Details →
Tool Review 2026-09-06 GateOfAI, LLC Kilo Code is an open-source, model-agnostic AI coding assistant positioned as an agentic engineering platform. Its verified public Product Hunt record describes pay-per-use pricing, more than 420,000 downloads across VS Code and Cursor, and a JetBrains offering for IDEs including IntelliJ IDEA, PyCharm, and WebStorm. At a Glance 🏢 Developer
Full Details →
Tool ReviewUpdated 2026-09-05© Gate of AI Muse Spark is Meta’s latest large language model and the underlying model of Meta AI. Meta’s official materials currently identify Muse Spark 1.1, not Muse Spark 1.3, and provide meaningful safety information while leaving commercial and developer-access details unconfirmed. At a Glance 🏢 Developer Meta 🤖 AI Type Large
Full Details →
Wispr Flow is an AI-powered dictation tool with a reported iOS release and a free access option. The verified evidence supports a practical personal-productivity evaluation, but it does not establish detailed privacy, enterprise, accuracy, or paid-plan terms. Wispr Flow at a Glance Developer Wispr Flow Website wisprflow.ai Pricing Free access is reported in independent coverage
Full Details →Gate of AI isn't just a directory — it's a living platform powered by builders like you. Discover tools submitted by the global AI community, or list your own and get in front of thousands of developers and professionals worldwide.
Raw & real submissions
Tools submitted directly by creators worldwide — unfiltered, fresh, and updated daily.
Community voted
Every tool gets upvoted or downvoted by real users — the best rise to the top naturally.
Free submission
Submit your tool in under 2 minutes — no fees, no friction. Our AI fills in the details automatically.
Global reach
Get your tool discovered by AI professionals, developers, and builders from around the world.
Intensive tutorials and courses from our experts.
Secure Next.js Copilot Design: An Evidence-Led Review Guide A customer-support copilot can be useful, but a working prototype is not automatically a secure product. This tutorial provides a practical review process for teams planning an OpenAI API and Next.js copilot workflow while keeping its claims within the verified evidence available for this article. The central
Start Learning →
Build a TypeScript pull-request reviewer that combines Git diffs, TypeScript Compiler API diagnostics, local AST rules, and OpenAI structured output. The result is a small CLI that can run locally or in CI while keeping compiler failures separate from contextual AI feedback. What You Will Build TypeScript is valuable because it makes contracts visible before
Start Learning →
Build a Qdrant Retrieval Workflow with OpenAI Embeddings Vector retrieval is a practical building block for retrieval-augmented generation (RAG): content is represented as embeddings, relevant items are retrieved for a question, and the retrieved evidence is passed to a language model. This tutorial explains how to design an automated workflow around Qdrant and OpenAI embeddings
Start Learning →
A verification-first guide to planning a private qualitative-research codebook workflow with Mistral Small 3.1, Ollama, and FastAPI—without overstating what local AI can prove. What Is Verified—and What Must Be Validated First This tutorial outlines a defensible way to design a private qualitative research workflow in which a locally operated model helps researchers propose thematic codebook
Start Learning →
Tutorial Plan a Next.js AI Task Copilot With Evidence-Led Guardrails This tutorial helps product, engineering, and operations teams define a responsible task-copilot project before choosing an SDK, model, database, or deployment pattern. It uses verified research on AI coding assistance to set realistic expectations and to create an evaluation plan for a future Next.js implementation.
Start Learning →Beyond the marketing hype. Join Technical Architect Mohammad Saed on an exclusive 4-part cinematic journey decoding the true engineering history of AI—from Alan Turing's early dreams to the reality of Sovereign AI and Edge Tech in 2026.
Exploring the philosophical roots of AI, the Dartmouth workshop, and how Transformers hit the KV Cache wall.
The story of overhyped expectations, the Perceptron limits, and how researchers survived the funding freeze.
How GPUs collided with Big Data to birth AlexNet, rescuing AI from the winter and sparking the neural network revolution.
Our reality in 2026. Why the MENA region is shifting towards Sovereign AI and on-premise edge computing models.
Stop the trial and error. Watch our latest step-by-step guides.
