Fallom

Fallom is your all-in-one observability platform built from the ground up for the age of AI. It's designed to bring crystal-clear visibility to the complex world of large language models (LLMs) and AI agents running in production. Think of it as a powerful dashboard that lets you see every single LLM call, trace every step of an agent's reasoning, and understand exactly what's happening under the hood of your AI applications. For developers and data scientists, this means you can debug a slow or failing agent in minutes instead of hours. For product and business leaders, it provides crucial insights into costs, usage patterns, and performance to ensure your AI initiatives are efficient and scalable. Fallom empowers teams to move fast with confidence, offering enterprise-grade features like compliance-ready audit trails and detailed cost attribution right out of the box. With its OpenTelemetry-native SDK, you can start tracing your applications in under five minutes, making advanced AI observability accessible to every team.

End-to-End LLM Tracing

Fallom provides comprehensive, granular tracing for every LLM interaction in your system. You can track the full journey of a request, including the exact prompt sent, the model's output, any tool or function calls made by an agent, token usage, latency, and the calculated cost. This complete visibility is essential for understanding performance, debugging unexpected behavior, and optimizing each call for better efficiency and lower expenses.

Real-Time Cost Attribution & Dashboard

Gain instant clarity on your AI spending with Fallom's live dashboard. It automatically breaks down costs by model, user, team, or customer, turning opaque API bills into actionable insights. You can see a live feed of calls, monitor for spending anomalies, and attribute expenses accurately for internal chargebacks or client billing, ensuring full financial transparency and control over your AI budget.

Compliance-Ready Audit Trails

Built for regulated industries, Fallom creates immutable, detailed audit logs of every AI interaction. It supports critical compliance needs like model versioning, user consent tracking, and input/output logging, helping you meet requirements for standards like the EU AI Act, SOC 2, and GDPR. This feature provides the necessary documentation to demonstrate responsible AI usage and data handling.

Timing Waterfall & Tool Call Visibility

Debug complex, multi-step agent workflows with ease using Fallom's visual timing waterfall diagrams. These charts break down the exact sequence and duration of LLM calls, tool executions, and processing steps, making it simple to pinpoint latency bottlenecks. Coupled with deep visibility into every tool call—showing function names, arguments, and results—you can quickly identify and fix inefficiencies in your agentic chains.

Optimizing AI Agent Performance

Development teams use Fallom to monitor and debug their production AI agents. By analyzing timing waterfalls and tool call traces, engineers can identify why an agent is slow—perhaps a specific database query or external API call is lagging—and optimize the workflow to improve response times and user experience significantly.

Managing and Forecasting AI Costs

Finance and engineering leaders leverage Fallom's cost attribution features to track spending across different projects, teams, and models. This allows for accurate budgeting, forecasting, and internal chargebacks. Teams can identify if a specific feature or user is driving unexpected costs and take action, such as optimizing prompts or switching models, to stay within budget.

Ensuring Regulatory Compliance

Compliance and legal officers in healthcare, finance, or enterprise software use Fallom to maintain robust audit trails for AI systems. The platform logs all necessary data (inputs, outputs, model versions, user consent) in an immutable format, providing the evidence needed to pass security audits and demonstrate adherence to industry regulations and internal governance policies.

Improving LLM Application Reliability

SRE and DevOps teams implement Fallom for real-time monitoring and alerting on their LLM-powered applications. By watching the live dashboard for error spikes, latency increases, or hallucination rate changes, they can detect and resolve incidents proactively before they impact end-users, ensuring high reliability and uptime for critical AI services.

How quickly can I start using Fallom?

You can get started in under five minutes. Fallom uses a single, OpenTelemetry-native SDK that you integrate into your application. Once instrumented, traces will immediately begin flowing to your Fallom dashboard, requiring minimal setup or configuration to see your first data.

Does Fallom support all LLM providers?

Yes, Fallom is designed to be provider-agnostic. It works with every major LLM provider, including OpenAI, Anthropic, Google Gemini, and others via its OpenTelemetry foundation. This means you can monitor all your AI models from one unified platform without vendor lock-in.

How does Fallom handle sensitive or private data?

Fallom offers a Privacy Mode for sensitive deployments. This allows you to disable full content capture for prompts and responses, logging only the metadata (like timings, token counts, and costs) while redacting the actual text. You can configure these privacy controls per environment to balance observability with data security.

Can I use Fallom for A/B testing different models or prompts?

Absolutely. Fallom includes features for model A/B testing and a Prompt Store for version control. You can safely roll out a new model to a percentage of traffic or test different prompt variations, then use Fallom's analytics to compare their performance, cost, and quality metrics side-by-side before making a full switch.