AgentOps

Top Builders

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
Author	AgentOps, Inc.
Release Date	2023
Website	https://www.agentops.ai/
Documentation	https://docs.agentops.ai/v1/introduction
Technology Type	Monitoring 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

Edit on GitHub

AgentOps AI technology page Hackathon projects

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

Project Hermes

Hermes is an Android accessibility and translation assistant designed for real-time communication across text, camera, and voice workflows. The app is built in Kotlin with Android native UI components, CameraX for live camera preview, ML Kit Text Recognition for on-device OCR, Android SpeechRecognizer for fast speech-to-text, and ExecuTorch/QNN integration for experimenting with local AI inference using whisper and Qwen2.5-0.5B and Qwen3-7B and on Qualcomm-powered devices. Its camera mode lets a user point the phone at signs, notes, labels, forms, menus, or other printed text, recognize the text on-device, identify the source language, and translate it into English. Its voice mode supports quick speech transcription so spoken input can be converted into readable text during live interaction. The project is especially useful in real-world situations such as travel, hospitals, classrooms, public offices, accessibility support, and multilingual conversations where users need quick understanding without switching between multiple apps. Hermes also includes groundwork for local model execution using Whisper-style ASR assets, Qwen translation models, Android native libraries, and Qualcomm acceleration paths, making it a practical prototype for privacy-aware, low-latency mobile AI translation.

OBSERVA

OBSERVA is a privacy-first AI mobility assistant designed for blind and low-vision users who need safe, reliable navigation support in everyday environments. Unlike many tools that depend on cloud processing, OBSERVA is built to run core safety features fully on-device, including in airplane mode, so users can rely on it in low-connectivity settings and for sensitive private contexts. Our current Android prototype uses a continuous CameraX loop with low-latency audio and haptic alerts, a hazard engine with cooldown and scene memory to avoid repetitive alert spam, and an accessibility-focused interface optimized for non-visual interaction. The product direction includes robust object recognition, hazard detection, contextual navigation assistance, and multilingual interaction/translation pathways while maintaining strict local processing guarantees. We position OBSERVA in a gap between pure OCR/vision apps and infrastructure-dependent systems (e.g., code-tag ecosystems), focusing on independent mobility, comfort, and trust. Our core value proposition is simple: private, offline, safety-oriented assistive intelligence that is usable in the real world, not just in ideal network conditions.

FinFlow AI

FinFlow AI is an autonomous finance operations platform powered by multiple AI agents that work together like a real enterprise finance team. The system uses Band as the core collaboration layer where specialized agents communicate, share context, and complete financial workflows. Our platform includes Procurement, Accounts Payable, Accounts Receivable, Cash Flow Risk, and Tally agents. The Procurement Agent evaluates purchase requests, vendor risk, and budget availability. The AP Agent manages payment scheduling and approvals. The AR Agent analyzes incoming payments and receivables. The Cash Flow Risk Agent predicts financial risks, while the Tally Agent maintains reconciliation, audit trails, and financial summaries.

Concord SOC

The Problem: The Handoff Bottleneck Every serious security incident follows the same shape: detection, classification, investigation, containment, communication, approval, and documentation. The bottleneck isn't the work itself—it is the handoffs between the people doing it. Each handoff introduces context switching and a chance for critical institutional memory to get lost. Standard automation without shared context just moves the bottleneck. The Solution: Concord SOC Concord SOC collapses every handoff into a single, continuously visible Band room. Five specialized AI agents and one accountable human analyst read and write to this single thread in real time. Triage: Classifies the incoming alert into a severity, category, and summary. Forensics: Reads Triage's words directly to identify the attack vector, CVEs, IOCs, and affected assets. Containment: Uses Forensics' findings to map out isolation steps, access rules, and a rollback plan. Communications: Activates only after both Forensics and Containment post. It drafts customer notifications and internal summaries. Human Analyst: Sits inside the room. Their explicit approval is the sole gate required to release communications. Root-Cause Analyst: Activates post-approval, synthesizing the entire room's history into a final post-incident report. Design Philosophy The room is the system; there is no hidden database. Agents act only when visible conditions are met. Human approval is a core architectural feature, not a fallback. If the room disappears, the system stops instantly—an intentional design choice proving that coordination happens entirely in the open.

HELIOS

HELIOS— Heuristic Evaluation & Launch Intelligence for Operational Safety Every year, configuration changes cause billions of dollars in outages. Traditional CI/CD tools validate syntax, schemas, and tests, but they cannot reason about organizational consequences. HELIOS-V2 fills this gap. HELIOS-V2 is a decentralized multi-agent reasoning system built on the Band SDK. Instead of relying on a rigid pipeline, six specialized agents collaborate inside a shared Band Room to evaluate configuration changes before deployment. Each agent has a dedicated responsibility: * SENTINEL - performs semantic analysis of configuration changes. * CHRONICLE - searches historical incidents and organizational knowledge. * MERIDIAN - evaluates dependencies and blast radius. * CONTEXT - analyzes organizational readiness and operational signals. * ORACLE - predicts technical, financial, and operational consequences. * ARBITER - aggregates all evidence and issues the final verdict. The agents communicate through an event-driven Band orchestration layer using structured context and agent handoffs. The system produces one of four explainable decisions: SHIP, WARN, STAGE, BLOCK. HELIOS integrates with GitHub Actions, APIs, and local workflows to automatically prevent dangerous deployments. Rather than asking, "Is this configuration valid?", HELIOS asks, "Can your business survive this configuration?" The system was evaluated on a 73-case synthetic benchmark and achieved 94.5% overall accuracy. It was also backtested against five major real-world incidents, including CrowdStrike, Facebook, GitLab, Knight Capital, and AWS S3. HELIOS correctly blocked all five catastrophic failures. By combining historical evidence, dependency graphs, organizational signals, and explainable multi-agent collaboration, HELIOS-V2 provides an enterprise-grade safety layer between "CI passed" and "Production is on fire." Built for the Band of Agents Hackathon 2026.

Dzuka Agri: Global AI for Huge Farm Ops

Dzuka Agri Intelligence Platform Global multi-agent AI architecture for large-scale commercial farming. Farm managers submit problem, crop image, and GPS. Master Orchestrator coordinates specialized agents (Agronomy & Soil, Pest & Pathology, Climate & Hydrology, Market, Resource, Review) in real-time collaboration. Delivers unified, high-impact recommendations tackling climate, pests, soil, water, markets, and more at enterprise scale. MVP: Next.js frontend, API, Band/OpenAI orchestration. Built for huge operations worldwide. Impact: Reduced losses, optimized inputs, maximum profitability.