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Explore the top contributors showcasing the highest number of app submissions within our community.

AgentOps

AgentOps is a comprehensive platform designed for monitoring, debugging, and optimizing AI agents in both development and production environments. It provides advanced tools such as session replays, metrics dashboards, and custom reporting, enabling developers to track the performance, cost, and interactions of their AI agents in real-time.

Some of the out-of-the-box integrations include:

  • CrewAI,
  • Autogen,
  • Langchain,
  • Cohere,
  • LiteLLM,
  • MultiOn.

This wide compatibility ensures seamless integration with a diverse range of AI systems and development environments.

General
AuthorAgentOps, Inc.
Release Date2023
Websitehttps://www.agentops.ai/
Documentationhttps://docs.agentops.ai/v1/introduction
Technology TypeMonitoring Tool

Key Features

  • LLM Cost Management: Track and manage the costs associated with large language models (LLMs).

  • Session Replays: Replay agent sessions to analyze interactions and identify issues.

  • Custom Reporting: Generate tailored reports to meet specific analytical needs.

  • Recursive Thought Detection: Monitor recursive thinking patterns in agents to ensure optimal performance.

  • Time Travel Debugging: Debug and audit agent behaviors at any point in their operational timeline.

  • Compliance and Security: Built-in features to ensure that agents operate within security and compliance standards.

Start Building with AgentOps

AgentOps offers developers powerful tools to enhance the monitoring and management of AI agents. With easy integration through SDKs, it provides real-time insights into the performance and behavior of agents. Developers are encouraged to explore community-built use cases and applications to unlock the full potential of AgentOps.

👉 Start building with AgentOps

👉 Examples

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AgentOps AI technology page Hackathon projects

Discover innovative solutions crafted with AgentOps AI technology page, developed by our community members during our engaging hackathons.

Pulse IQ Real-Time Enterprise Intelligence Agent

Pulse IQ Real-Time Enterprise Intelligence Agent

PulseIQ is a real-time enterprise intelligence agent designed to act as an AI Chief of Staff for product and executive teams. Instead of relying on fragmented dashboards or manual analysis, PulseIQ continuously monitors business activity across customers, partners, and revenue to automatically detect meaningful changes, explain why they happened, and generate executive-ready briefings. PulseIQ unifies live operational data into a metrics layer and a business knowledge graph, enabling true cross-domain reasoning. When key indicators like Client LTV decline, the system traverses this graph to identify upstream causes — such as shifts in partner quality or acquisition channels — and converts those signals into structured insights. The platform answers four critical questions in real time: what changed, why it changed, what risks are emerging, and what actions can be taken. These are surfaced through a live executive dashboard showing KPIs, detected root causes, and AI-generated Insights, Risks, and Opportunities. Unlike traditional BI tools or chat-over-data interfaces, PulseIQ operates autonomously. It proactively surfaces intelligence as it happens, allowing teams to move from reactive reporting to continuous decision intelligence. This enables leaders to focus on building and scaling while PulseIQ continuously tracks performance, flags emerging issues, and recommends corrective actions. For the hackathon, PulseIQ demonstrates this capability using synthetic real-time data, a knowledge graph for causal analysis, and an executive dashboard with automated briefings. The architecture is designed to integrate with enterprise APIs in production environments, making it applicable to use cases such as revenue health monitoring, partner quality analysis, churn risk detection, and platform-wide operational intelligence. In short, PulseIQ transforms raw business events into actionable executive insight — helping organizations move from dashboards to decisions.

Secure-AI

Secure-AI

LLMs have recently adopted persistent memory to provide models with better user knowledge and personalisation. However, this introduces a new vector for adversarial manipulation. This report investigates Memory Injection, a threat model where adversaries exploit indirect prompt injection within web content to poison an agent's long-term memory. Employing user manipulation scenarios, we show that memory attacks, should they succeed, are effective at changing model behaviour towards the user, often more so than a direct system prompt. Hence, this highlights the need for more robust evaluations of memory updates in agentic memory systems.

AI-Powered Multi-Agent Enterprise Platform

AI-Powered Multi-Agent Enterprise Platform

Deriv Agent is a comprehensive AI-powered agent management platform that transforms enterprise operations through intelligent automation and multi-agent collaboration. Built with Agno and OpenRouter, the platform addresses three core business challenges that require sophisticated AI capabilities. **HR Operations Automation**: The platform provides a self-service HR system that automates contract generation, answers policy questions through conversational AI, and tracks compliance proactively. Specialized agents handle document generation, policy Q&A, benefits administration, and compliance monitoring. Multi-agent teams collaborate to process complex HR workflows, from onboarding documentation to visa compliance tracking, dramatically reducing manual work and improving employee experience. **Financial Crime Detection**: The system employs advanced AI agents for transaction monitoring, anomaly detection, and network analysis to identify money laundering, fraud, and suspicious trading patterns in real-time. The platform uses behavioral anomaly detection, graph-based network analysis, and automated evidence collection to reduce false positives from thousands of alerts to high-confidence cases. Agents automatically generate suspicious activity reports (SARs) with full investigation packs ready for compliance review. **Trading Intelligence**: The platform provides comprehensive market analysis, behavioral coaching, and social content generation for traders. Specialized agents analyze market trends, explain price movements, detect emotional trading patterns, and generate engaging social media content. The system combines market intelligence with behavioral insights to help traders understand markets, recognize their own patterns, and stay informed through AI-generated content. The platform features a flexible architecture with multiple interfaces including a Telegram bot with live streaming of agent actions, a web UI, and a full REST API.

GoSec is Agentic Security Compliance Recon Tool

GoSec is Agentic Security Compliance Recon Tool

GoSec is a security automation tool built on the Google Agent Development Kit (ADK) pattern. It wraps standard security scanners like Nmap, Lynis, and Nikto into a single interface, using an AI agent to manage the execution and data aggregation. The core of the project is an agent loop that connects to an LLM provider. When you give it a command like "Check for HIPAA compliance," the agent interprets the request and decides which tools to run. It handles the arguments and execution logic for each tool, so you don't have to manually run scripts or remember CLI flags. Instead of just printing output to the console, GoSec-ADK parses the results from each tool and feeds them into a "Unified Finding Graph." This graph stores everything as nodes (hosts, services) and edges (relationships). This structure allows the system to correlate findings from different sources. For example, if Nmap finds an open port and Lynis reports a configuration issue on that same service, the graph links these two facts together. The system analyzes the graph to find paths from an attacker to critical assets. It looks for chains of vulnerabilities like an exposed service leading to a database and flags them as high-risk paths. Security standards (HIPAA, PCI, etc.) are defined in simple YAML files. The engine reads these profiles to determine which specific checks need to be run to satisfy a requirement. If a vulnerability is found, the tool can generate a fix script based on pre-written YAML templates. These templates include the commands to fix the issue, verify the fix, and rollback if needed. You can save the current state of the graph to a JSON file. This allows you to compare scans over time to see exactly what changed. GoSec-ADK is designed to be a practical wrapper for security tools. It automates the routine work of running scans and parsing output, uses a graph database to make sense of the data, and provides a conversational interface to interact with your security infrastructure

AgentPaywall

AgentPaywall

Hoping to finally say Goodbye to permanent .env API keys. They are the weakest link in modern AI infrastructure—and were never designed for autonomous agents. API keys grant broad, long-lived access with no economic context. Once leaked or abused, the damage is immediate. Providers must trust users upfront, bill later, and absorb fraud and overuse. For autonomous agents, static keys are incompatible: agents cannot reason about cost, enforce budgets, or decide whether access is worth paying for when authorization is detached from payment. AgentPaywalls eliminates API keys as an access primitive. Instead of granting access first and billing later, AgentPaywalls introduces payment-as-authorization. Each request, session, or quota is unlocked only after a verified USDC payment, delivered via short-lived, scoped capability tokens. Tokens expire automatically, are scoped to what was purchased, and cannot be reused. No permanent secrets. No blanket permissions. APIs remain unchanged. Blockchain settlement is off the hot path, preserving low latency. Providers replace static credentials with a lightweight middleware that issues access only after payment confirmation. Autonomous agents powered by Gemini evaluate cost versus expected utility before spending, enforcing budgets and making economically rational decisions without human approval. Agents dynamically choose when to buy data, inference, or content—and when not to. Payments are executed via x402 and Circle Gateway, enabling sub-cent, HTTP-native micropayments, and are settled in USDC on Arc, an EVM-compatible Layer 1 optimized for predictable fees and instant finality. AgentPaywalls does not reinvent APIs—it replaces brittle API keys with programmable, payment-verified access, enabling a secure, autonomous, and scalable machine-to-machine economy where software can finally pay for intelligence safely.

AgentInvoice

AgentInvoice

**Autonomy when you want it, Control when you need it, Billing infrastructure for AI agents** AgentInvoice is a dual-mode agentic invoicing and escrow system designed for the next generation of autonomous commerce on Arc. It enables AI agents and humans to create, approve, escrow, and settle USDC invoices securely using trustless smart contracts and Circle infrastructure. The core innovation of AgentInvoice is its dual-mode payment architecture. In Autonomous Mode, AI agents can independently negotiate terms, generate invoices, lock USDC into escrow, and release payments once predefined conditions are met — without human intervention. This is ideal for agent-to-agent commerce, API monetization, and automated service marketplaces. In Manual Mode, enterprises and users can require human approval before escrow funding or release, providing compliance, safety, and governance while still leveraging the same on-chain infrastructure. AgentInvoice uses USDC as the settlement asset and executes all transactions on Arc, ensuring deterministic finality, transparent verification, and predictable fees. Smart contract escrow guarantees trustless execution, automatic refunds, and deadline-based releases. To support adoption, AgentInvoice includes a developer-first toolkit: SDK for integrating agentic billing into applications REST APIs for invoice creation, escrow management, and settlement CLI tools for developers and operators Monitoring dashboards for invoice and escrow lifecycle tracking This allows builders to easily add agentic payments to AI systems while giving enterprises the controls they need to safely adopt autonomous workflows. AgentInvoice bridges the gap between fully autonomous AI commerce and real-world business requirements, making agentic payments practical, secure, and production-ready.