Fallom

Fallom is a cutting-edge AI-native observability platform specifically designed for large language models (LLMs) and agent workloads. As organizations increasingly rely on LLMs to drive their operations, the need for comprehensive visibility into these systems has never been greater. Fallom addresses this need by providing detailed insights into every LLM call made in production, allowing teams to trace end-to-end processes that include prompts, outputs, tool calls, tokens, latency, and associated costs. Tailored for developers, data scientists, and compliance officers, Fallom not only helps monitor LLM operations in real time but also accelerates debugging and improves performance insights. Its rich context around sessions, users, and customers, combined with robust enterprise features such as audit trails and consent tracking, makes Fallom indispensable for organizations aiming to ensure compliance and optimize their LLM deployments. With an OpenTelemetry-native SDK, teams can set up monitoring in under five minutes, making real-time usage tracking and cost attribution a seamless and efficient process.

Real-Time Observability

Fallom offers real-time observability for AI agents, enabling users to track every function call made by LLMs. This feature provides insights into timing, costs, and performance metrics, allowing teams to debug with confidence and optimize workflows effectively.

Cost Attribution

With Fallom's cost attribution capabilities, organizations can track spending on a granular level. Users can analyze costs per model, user, and team, providing full transparency essential for effective budgeting and financial planning in LLM operations.

Compliance Ready

Fallom is built with compliance in mind, offering complete audit trails that help organizations meet regulatory requirements such as the EU AI Act, SOC 2, and GDPR. This feature ensures that all interactions with LLMs are logged and traceable, thereby enhancing organizational accountability.

Session Tracking

The session tracking feature allows users to group traces by session, user, or customer, providing comprehensive context for each LLM interaction. This capability is crucial for understanding user behavior and refining LLM performance based on real-world usage.

Debugging LLM Workflows

Fallom is invaluable for teams debugging LLM workflows. By providing detailed insights into every call and its performance, users can quickly identify bottlenecks and optimize their models for better efficiency.

Cost Management

Organizations can leverage Fallom's cost attribution feature to manage their LLM-related expenses effectively. By tracking costs per user and model, teams can make informed decisions about resource allocation and budget planning.

Ensuring Compliance

For companies operating under strict regulatory frameworks, Fallom's compliance-ready features are essential. Users can maintain audit trails and ensure proper consent tracking, safeguarding their operations against potential legal pitfalls.

Performance Evaluation

Fallom enables organizations to run evaluations on LLM outputs, ensuring quality and accuracy before deployment. By analyzing metrics such as accuracy, relevance, and hallucination rates, teams can refine their models to meet high standards.

What types of organizations benefit from using Fallom?

Fallom is designed for a wide range of organizations, including those in regulated industries like finance and healthcare, as well as tech companies utilizing LLMs for various applications. Its features cater to developers, data scientists, and compliance teams.

How fast can I set up Fallom for my LLM monitoring needs?

Setting up Fallom is incredibly quick, with the OpenTelemetry-native SDK allowing users to begin monitoring their LLMs in under five minutes. This rapid setup is ideal for teams looking to implement observability without extensive overhead.

What kind of data does Fallom track during LLM calls?

Fallom tracks a variety of data points during LLM calls, including input prompts, output responses, tool calls, token usage, latency, and cost associated with each interaction. This comprehensive data helps teams analyze performance and optimize their deployments.

How does Fallom ensure user privacy while capturing data?

Fallom includes a privacy mode that allows organizations to disable content capture for sensitive data while still maintaining telemetry. This feature ensures compliance with privacy regulations and protects user confidentiality in LLM interactions.