Fallom

About Fallom

Fallom is an AI-native observability platform specifically designed for large language model (LLM) and agent workloads. It provides users with the ability to see every LLM call in production through comprehensive end-to-end tracing. This includes crucial information such as prompts, outputs, tool calls, tokens, latency, and per-call costs. Fallom targets organizations that rely on AI agents, allowing them to monitor and optimize their LLM usage efficiently. The platform offers deep insights into user and session-level contexts, enabling teams to understand performance and usage patterns thoroughly. Additionally, it supports enterprise compliance needs with robust features like logging, model versioning, and consent tracking. With a single OpenTelemetry-native SDK, teams can instrument their applications in mere minutes, facilitating live monitoring, faster debugging, and effective cost attribution across models, users, and teams.

Features of Fallom

Real-Time Observability

Fallom provides real-time observability for AI agents, allowing users to track tool calls and analyze timing metrics seamlessly. This feature enhances debugging confidence by offering visibility into every aspect of LLM interactions, ensuring teams can address issues proactively.

Cost Attribution

With Fallom's cost attribution feature, organizations can track spending per model, user, and team. This full cost transparency is vital for budgeting and financial planning, enabling teams to understand and manage their AI expenditures effectively.

Compliance Ready

Fallom is built with compliance in mind, offering full audit trails that support various regulatory requirements such as the EU AI Act, SOC 2, and GDPR. This feature ensures that organizations can meet their legal obligations while maintaining operational efficiency.

Timing Waterfall Analysis

Debugging latency issues in multi-step agent workflows is simplified with Fallom's timing waterfall analysis. This feature allows users to visualize the time taken for each step, identifying bottlenecks and ensuring optimal performance of AI agents.

Use Cases of Fallom

Performance Monitoring for AI Agents

Fallom enables organizations to monitor the performance of their AI agents in real-time, providing insights into efficiency and responsiveness. This use case helps teams quickly identify and resolve performance issues, leading to improved user satisfaction.

Budget Management for AI Operations

By tracking costs associated with different models and user interactions, Fallom assists organizations in managing their AI budgets effectively. This ensures that resources are allocated efficiently, maximizing the return on investment in AI technologies.

Regulatory Compliance Management

Organizations can leverage Fallom to maintain comprehensive audit trails and logs necessary for regulatory compliance. This use case is critical for businesses operating in regulated industries, ensuring adherence to relevant laws and standards.

Debugging and Testing LLM Outputs

Fallom allows teams to run evaluations on LLM outputs, helping catch regressions before they reach production. This proactive approach to debugging ensures high-quality AI outputs and reduces the risk of errors impacting users.

Frequently Asked Questions

What types of organizations can benefit from Fallom?

Fallom is ideal for organizations utilizing AI agents and LLM workloads, particularly those in regulated industries that require compliance with standards such as GDPR and the EU AI Act.

How quickly can I set up Fallom for my applications?

Fallom boasts an OpenTelemetry-native SDK that allows teams to instrument their applications in under five minutes, making it incredibly easy to start monitoring AI workloads.

Is Fallom suitable for multi-step AI workflows?

Yes, Fallom is specifically designed to support complex multi-step agent workflows, providing detailed timing waterfalls that help identify and resolve latency issues effectively.

What compliance standards does Fallom support?

Fallom supports compliance with several regulatory standards, including the EU AI Act, SOC 2, and GDPR, making it a robust solution for organizations needing to meet stringent compliance requirements.