Mpo Jagoan88
autonomousOnline gaming platform
autonomous 56
Autonomous AI agents operate with high independence, pursuing goals over multiple steps, using tools, browsing the web, writing and executing code, and self-correcting when tasks go off track. The 56 tools here represent an emerging category where the agent, not the human, decides how to complete an objective.
Automate Your Job Search with AI
autonomousOptimize resumes and cover letters for job success
ConvoZen
autonomousAI agent stack for customer conversations and team coaching
Soho
autonomousSwipeable real estate property listings
Stork.AI
autonomousAI tools directory queryable by agents
Celebrity Agent
autonomousAI-driven lead generation for real estate agents
Morphik
autonomousAI agents that handle accounts payable, billing, collections, and payroll
Tiktak (co-pilot) studio
autonomousDraft privacy policies with AI assistance
Kimi Membership
autonomousDeploy an AI assistant with memory to the cloud in one click
Website
autonomousHermes agent platform
Fetch AI
autonomousOpen network of autonomous AI agents and economic transactions
Cognition
autonomousAI agents for task and workflow automation
TrueFoundry
autonomousKubernetes-native platform for agentic AI workloads
Conversed.ai
autonomousBuild custom AI chatbots and agents without writing code
OpenSesame
autonomousBuild and deploy AI agents on one platform
Solvea by VOC AI
autonomousAI assistance for contact center agents
Superagent
autonomousAI security team that finds and patches vulnerabilities
NexusGPT
autonomousBuild AI agents from workflows in days
AgentRunner
autonomousOperational automation for enterprises
Skymel ADK (Agent Development Kit)
autonomousBuild production agents from prompts in hours
Rierino
autonomousCreate and manage intelligent AI agents for task automation
Flutch
autonomousPre-built AI agents for sales, support, and HR
VisionFX
autonomousGenerate images, videos, music, and voice with AI
Yobi
autonomousDeploy intelligent agents for business automation
Autonomous agents are fundamentally different from assistants or chatbots. They are given a goal and a set of tools, and they plan and act without requiring a human to approve each step. This makes them useful for long-horizon tasks like research, lead qualification, or multi-system integrations, but it also means errors can compound before a human notices. Products like NexusGPT and AgentRunner provide infrastructure for building custom agents, while Superagent leans toward ready-to-deploy solutions. When evaluating, the most important factor is how gracefully the agent handles ambiguity and failure. Look for guardrails, human-override features, and transparency into what the agent actually did. Memory architecture affects how well the agent stays on task over long runs. Most tools in this category are priced by compute usage or API calls rather than seats, so cost modeling at scale requires testing with realistic workloads.