Kimi-VL
Alternatives
0 PH launches analyzed!
Problem
Users rely on traditional VLMs with limited context windows and dense architectures, leading to inefficient multimodal reasoning and inability to handle long-context tasks.
Solution
An open Mixture of Experts (MoE) VLM enabling multimodal reasoning with 128K context length and agent task support, e.g., analyzing lengthy image-text sequences for AI workflows.
Customers
AI developers, researchers, and engineers building agents requiring long-context multimodal processing (e.g., document analysis, complex QA systems).
Alternatives
Unique Features
MoE architecture with 2.8B active parameters balances efficiency and performance; 'Thinking' variant optimizes reasoning pipelines.
User Comments
Handles 100+ page PDFs with images effortlessly
Outperforms larger models in agent tasks
Low latency for real-time applications
Easy API integration
Limited fine-tuning documentation
Traction
2.8B active parameter model launched by Moonshot AI (known for 200K-context LLMs); used in 50+ enterprise AI agent deployments as per PH comments.
Market Size
The multimodal AI market is projected to grow from $1.2 billion in 2023 to $8.3 billion by 2028 (CAGR 47.3%) per MarketsandMarkets.
Open Agent Kit - Build Agents in Minutes
Build, Customize, Deploy – AI Agents Your Way with OAK!
186
Problem
Users face time-consuming and inflexible development processes when creating AI agents, struggling with challenges in integrating various LLMs and workflows using traditional coding methods.
Solution
Open-source platform enabling developers to build, customize, and deploy AI agents quickly by allowing them to connect to any LLM, extend functionality with plugins, and embed AI into workflows (e.g., automating customer support or data analysis tasks).
Customers
Developers and AI engineers seeking scalable, customizable AI solutions for enterprise or startup environments.
Unique Features
Open-source architecture, modular plugin system, multi-LLM compatibility, and workflow embedding capabilities.
User Comments
Simplifies agent deployment for non-experts
Plugins accelerate feature development
Seamless integration with existing tools
Highly customizable for niche use cases
Reduces AI prototyping time by 70%
Traction
Launched on ProductHunt with 480+ upvotes, GitHub repository trending with 1.2k+ stars, active community of 3k+ developers on Discord
Market Size
The global AI developer tools market is projected to reach $136 billion by 2025 (Grand View Research 2023), driven by demand for customizable AI solutions.
Open Agent Studio
Build no-code agents to target markets untouched by AI
373
Problem
Businesses attempting to integrate AI and automation technologies often struggle with the complexity and rigidity of traditional RPA tools, which rely heavily on brittle code selectors or computer vision.
Solution
Open Agent Studio is a no-code platform that allows users to build RPA agents using simple English to create business automations previously considered impossible.
Customers
Businesses in various industries looking to simplify their automation process and remove barriers posed by traditional coding requirements.
Alternatives
View all Open Agent Studio alternatives →
Unique Features
Uses natural language processing to interpret simple English for automation creation, breaking away from traditional complex coding methods.
User Comments
Simplifies the RPA implementation process
Revolutionary use of natural language in automation.
Reduces the learning curve for non-technical users.
Enables rapid prototyping and deployment.
Lowers the barrier to entry for small businesses.
Traction
Recently launched on ProductHunt, gaining initial attention and interest from the tech community.
Market Size
The global RPA market is expected to reach $13.74 billion by 2028.
Prompt Builder: Long-Context Prompts
Build rich, multi-file LLM prompts from a single interface
3
Problem
Currently, users struggle with creating comprehensive, multi-file AI prompts, which hampers the efficiency in tasks such as writing, coding, and research.
Creating comprehensive, multi-file AI prompts is a complex task leading to inefficiencies.
Solution
This product is a macOS app for building multi-file AI prompts.
Users can aggregate local files, fetch transcripts, reorder blocks, track token usage, and summarize large text.
For example, users undertake long-context tasks like writing, coding, and research more efficiently.
Customers
Researchers, coders, and writers
Demographic: Professionals using AI extensively for content creation
User behavior: Frequent AI tool users needing streamlined, comprehensive prompt construction
Unique Features
Open-source macOS app
Ability to manage and track long-context prompts efficiently
Comprehensive functionality from a single interface
User Comments
Highly functional for organizing complex prompts.
Appreciated for being open-source and versatile.
Streamlines the process of prompt building significantly.
Useful for professional writers and developers.
Great for managing extensive and diverse AI tasks.
Traction
Newly launched with growing interest
Integrated features for long-context tasks
Market Size
The generative AI market was valued at approximately $10 billion in 2022 and is expected to grow significantly.
Agent TARS
An open-source multimodal AI agent.
3
Problem
Users manage browser operations and system integrations through manual, time-consuming processes that require constant oversight and lack automation.
Solution
An open-source multimodal AI agent enabling users to automate browser tasks via visual interpretation of web pages and integrate with command lines/file systems, e.g., automating form submissions or data scraping.
Customers
Developers, DevOps engineers, and IT professionals seeking to automate workflows and reduce manual intervention in web-based and system-level tasks.
Unique Features
Combines visual web page analysis with CLI/file system integration, open-source flexibility for customization, and multimodal AI for context-aware automation.
User Comments
Saves hours on repetitive tasks
Intuitive visual automation
Easy CLI integration
Open-source transparency boosts trust
Scalable for complex workflows
Traction
Newly launched (v1.0), featured on Product Hunt with 500+ upvotes, GitHub repository trending with 1.2k stars, active community contributions.
Market Size
The global process automation market is projected to reach $22.8 billion by 2028 (Grand View Research, 2023), driven by demand for AI-driven workflow solutions.
Agent Development Kit
Build multi-agent systems with Google's open framework
171
Problem
Developers and engineers building multi-agent systems face challenges with time-consuming setup, lack of integrated tooling, and difficulty in evaluating system performance using fragmented or custom-built frameworks.
Solution
An open-source development framework (ADK) enabling users to build multi-agent systems with flexible orchestration, a rich tool/model ecosystem, and built-in evaluation capabilities, e.g., creating collaborative AI agents for automated workflows.
Customers
AI developers, machine learning engineers, and researchers working on complex multi-agent applications in industries like automation, robotics, or enterprise AI solutions.
Alternatives
View all Agent Development Kit alternatives →
Unique Features
Google-backed open-source infrastructure, native integration with Google’s AI ecosystem, declarative orchestration, and pre-built evaluation metrics for agent performance.
User Comments
Simplifies multi-agent development
Seamless Google ecosystem integration
Powerful evaluation tools
Lacks extensive documentation
Steep learning curve for beginners
Traction
1,100+ upvotes on Product Hunt, 2.8k GitHub stars, used by 500+ teams (self-reported), founder has 5.4k followers on X.
Market Size
The global AI developer tools market is projected to reach $42 billion by 2028 (Grand View Research, 2023), driven by demand for collaborative AI systems.
Problem
Users relying on base LLMs with limited vision, reasoning, and long-context capabilities face challenges in handling multimodal AI tasks efficiently
Solution
Open-source MLLM family enabling vision, reasoning, long-context processing & agent integration via native multimodal pre-training (1B-78B parameters)
Customers
AI researchers, developers, and engineers building complex multimodal AI systems requiring vision-language integration
Unique Features
Native multimodal pre-training architecture spanning 1B to 78B parameters, outperforms text-focused LLMs on pure language tasks without domain-specific tuning
User Comments
Superior vision-language alignment
Effective long-context handling
Strong reasoning capabilities
Scalable model architecture
Open-source accessibility
Traction
Part of OpenGVLab's ecosystem (12k+ GitHub stars across projects)
Supports model sizes from 1B to 78B parameters
Integrated with agent frameworks
Market Size
The global natural language processing market is projected to reach $341.5B by 2030 (Grand View Research), with multimodal AI driving growth
Open Agent Cloud (Antler F24)
Generate no-code automation agents from screen recordings
611
Problem
Users need to generate no-code automation agents from screen recordings, which can be a complex and time-consuming process.
Solution
A platform that allows users to upload loom videos or screen recordings to automatically generate no-code desktop automation agents that run on the cloud without requiring any installations. Users can test it on cheatlayer.com without the need to log in.
Customers
Users who want to automate tasks without writing code, such as business owners, automation enthusiasts, and professionals in the technology industry
Unique Features
Automated generation of no-code automation agents from screen recordings
Cloud-based deployment without the need for installations
Instantly running automation agents
User Comments
Extremely impressed with the automation capabilities
Easy to use and saves a significant amount of time
Effective for various industries and tasks
Great tool for streamlining workflow processes
Highly recommended for those new to automation
Traction
This product has gained traction with over 5,000 active users within its first month of launch.
Market Size
The global market for no-code automation tools was valued at $5.6 billion in 2021.
Open Soccer
Platform to connect talented players with agents
5
Problem
Aspiring players struggle to get discovered by professional agents due to lack of exposure and connections in the industry.
Solution
Platform that connects talented players with professional agents, providing the necessary tools for discovery and collaboration.
Customers
Aspiring players seeking opportunities in the soccer industry and professional agents looking for talented players to represent.
Unique Features
Utilizes technology to bridge the gap between aspiring players and professional agents, streamlining the discovery process.
Market Size
Global sports market was valued at approximately $557.06 billion in 2020.
A2A Agent List
Explore & Share A2A-Compatible AI Agents Easily
5
Problem
Users need to manually discover and share AI agents compatible with the A2A protocol, leading to fragmented ecosystems and inefficient collaboration.
Solution
A2A Agent List is an open directory tool that lets developers discover, publish, and integrate A2A-compatible AI agents, e.g., browsing agents by use case or sharing their own via the platform.
Customers
AI developers, tech startups building multi-agent systems, and researchers focused on agent interoperability (ages 25-45, tech-savvy, active in AI communities).
Alternatives
View all A2A Agent List alternatives →
Unique Features
Focuses exclusively on the A2A protocol, enabling standardized agent communication and a centralized hub for discovery.
User Comments
Simplifies agent integration
Saves development time
Lacks advanced filtering
Needs more documentation
Promising for ecosystem growth
Traction
Launched on ProductHunt in 2024, early-stage traction with 150+ agents listed (as per product description).
Market Size
The global multi-agent systems market is projected to reach $4.8 billion by 2028 (MarketsandMarkets, 2023).