Ango Hub
Ango Hub is a quality-focused, enterprise-ready data annotation platform for AI teams, available on cloud and on-premise. It supports computer vision, medical imaging, NLP, audio, video, and 3D point cloud annotation, powering use cases from autonomous driving and robotics to healthcare AI.
Built for AI fine-tuning, RLHF, LLM evaluation, and human-in-the-loop workflows, Ango Hub boosts throughput with automation, model-assisted pre-labeling, and customizable QA while maintaining accuracy. Features include centralized instructions, review pipelines, issue tracking, and consensus across up to 30 annotators. With nearly twenty labeling tools—such as rotated bounding boxes, label relations, nested conditional questions, and table-based labeling—it supports both simple and complex projects. It also enables annotation pipelines for chain-of-thought reasoning and next-gen LLM training and enterprise-grade security with HIPAA compliance, SOC 2 certification, and role-based access controls.
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Langtail
Langtail is a cloud-based application development tool designed to help companies debug, test, deploy, and monitor LLM-powered apps with ease. The platform offers a no-code playground for debugging prompts, fine-tuning model parameters, and running LLM tests to prevent issues when models or prompts change. Langtail specializes in LLM testing, including chatbot testing and ensuring robust AI LLM test prompts.
With its comprehensive features, Langtail enables teams to:
• Test LLM models thoroughly to catch potential issues before they affect production environments.
• Deploy prompts as API endpoints for seamless integration.
• Monitor model performance in production to ensure consistent outcomes.
• Use advanced AI firewall capabilities to safeguard and control AI interactions.
Langtail is the ideal solution for teams looking to ensure the quality, stability, and security of their LLM and AI-powered applications.
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Langfuse
Langfuse is an open source LLM engineering platform to help teams collaboratively debug, analyze and iterate on their LLM Applications.
Observability: Instrument your app and start ingesting traces to Langfuse
Langfuse UI: Inspect and debug complex logs and user sessions
Prompts: Manage, version and deploy prompts from within Langfuse
Analytics: Track metrics (LLM cost, latency, quality) and gain insights from dashboards & data exports
Evals: Collect and calculate scores for your LLM completions
Experiments: Track and test app behavior before deploying a new version
Why Langfuse?
- Open source
- Model and framework agnostic
- Built for production
- Incrementally adoptable - start with a single LLM call or integration, then expand to full tracing of complex chains/agents
- Use GET API to build downstream use cases and export data
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vishwa.ai
vishwa.ai is an AutoOps platform for AI and ML use cases.
It provides expert prompt delivery, fine-tuning, and monitoring of Large Language Models (LLMs).
Features:
Expert Prompt Delivery: Tailored prompts for various applications.
Create no-code LLM Apps: Build LLM workflows in no time with our drag-n-drop UI
Advanced Fine-Tuning: Customization of AI models.
LLM Monitoring: Comprehensive oversight of model performance.
Integration and Security
Cloud Integration: Supports Google Cloud, AWS, Azure.
Secure LLM Integration: Safe connection with LLM providers.
Automated Observability: For efficient LLM management.
Managed Self-Hosting: Dedicated hosting solutions.
Access Control and Audits: Ensuring secure and compliant operations.
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