Fallom

Fallom provides essential real-time observability for tracking and analyzing all your LLM and AI agent operations.

Visit

Published on:

January 10, 2026

Pricing:

Fallom application interface and features

About Fallom

Fallom is the essential AI-native observability platform built specifically for the complexities of Large Language Model (LLM) and AI agent workloads. In a landscape where AI operations are critical but opaque, Fallom delivers the non-negotiable visibility that development and enterprise teams require. It provides comprehensive, end-to-end tracing for every LLM call in production, capturing vital data like prompts, outputs, tool calls, token usage, latency, and cost. This platform is a necessity for AI developers, data scientists, and enterprise teams who must monitor usage in real-time, ensure compliance with evolving regulations, and optimize costly AI operations. By offering a single OpenTelemetry-native SDK, Fallom enables instrumentation in minutes, eliminating blind spots. The core value proposition is absolute control: the ability to troubleshoot performance bottlenecks, attribute costs accurately across teams and models, and maintain robust audit trails for governance, all from a unified dashboard. Without Fallom, organizations are flying blind with their most critical and expensive AI initiatives.

Features of Fallom

End-to-End LLM Tracing

Fallom provides mandatory, granular visibility into every interaction within your AI stack. It automatically traces each LLM call, capturing the full context including the exact prompt sent, the model's output, any intermediate tool or function calls with their arguments and results, token counts, latency, and calculated cost. This complete trace is fundamental for debugging complex agent workflows and understanding the precise chain of events that led to any given response.

Real-Time Cost Attribution & Analytics

Gaining control over spiraling and unpredictable AI costs is a critical business necessity. Fallom offers precise, real-time cost tracking broken down by model, user, team, or even individual customer. This feature provides the transparency required for accurate budgeting, internal chargebacks, and identifying inefficient or expensive patterns in model usage, ensuring every dollar spent on AI is accountable and optimized.

Compliance-Ready Audit Trails

Meeting regulatory standards like the EU AI Act, GDPR, and SOC 2 is not optional for enterprise AI. Fallom is built with compliance as a core requirement, generating immutable, complete audit trails of all LLM interactions. This includes logging of inputs and outputs, model versioning, user consent tracking, and session history, providing the necessary evidence and traceability for legal and security audits.

Advanced Debugging with Timing Waterfalls

Diagnosing performance issues in multi-step AI agents is a fundamental challenge. Fallom's timing waterfall visualizations are an indispensable tool for this, breaking down the latency of each step in an agent's execution. You can instantly see how much time was spent on each LLM call, database query, or custom function, allowing you to pinpoint and resolve latency bottlenecks that degrade user experience.

Use Cases of Fallom

Proactive Production Monitoring & Incident Response

Teams must monitor their AI applications live to prevent minor issues from becoming major outages. Fallom's real-time dashboard allows engineers to watch LLM traffic, spot anomalies like latency spikes or error rate increases, and drill down into specific problematic traces immediately. This enables proactive intervention and faster mean-time-to-resolution (MTTR) for any production incidents involving AI components.

Optimizing AI Agent Performance & Reliability

Developing reliable, multi-step AI agents requires deep insight into their internal decision-making. Fallom allows developers to trace through complex agent sessions, review every tool call and LLM reasoning step, and analyze timing waterfalls. This is essential for refining prompts, improving tool orchestration, and eliminating inefficiencies or errors that cause agents to fail or provide poor results.

Enforcing Governance and Regulatory Compliance

For organizations in finance, healthcare, or any regulated industry, demonstrating control over AI systems is mandatory. Fallom provides the complete audit trail required to prove how AI models are used, what data they process, and that appropriate safeguards are in place. It supports compliance reviews and helps fulfill obligations under regulations concerning algorithmic transparency and data privacy.

Managing and Forecasting AI Operational Costs

Without visibility, AI costs can quickly become a major and unpredictable line item. Fallom gives finance and engineering leaders the tools to track spend per project, department, or product feature. This data is critical for forecasting budgets, implementing showback/chargeback models, and making informed decisions about model selection (e.g., choosing between GPT-4o and a more cost-effective model for certain tasks).

Frequently Asked Questions

How difficult is it to integrate Fallom into my existing application?

Integration is designed to be straightforward and fast. Fallom uses a single, OpenTelemetry-native SDK that can instrument your LLM calls in under five minutes. It works with all major LLM providers (OpenAI, Anthropic, Google, etc.) and frameworks, meaning you can add comprehensive observability without vendor lock-in or significant code changes.

Does Fallom store or have access to my sensitive prompt and response data?

Fallom offers robust privacy controls to meet different security needs. You can run the platform in a full "Privacy Mode" that disables content capture for sensitive data, logging only metadata like token counts and latency. Alternatively, you can use configurable content redaction rules. You maintain full control over what data is sent and stored.

Can Fallom help me test and improve my prompts and models?

Yes, absolutely. Fallom includes features for evaluation and testing, allowing you to run automated checks on LLM outputs for metrics like accuracy, relevance, and hallucination rates. Coupled with the Prompt Store for versioning and A/B testing different prompt variations, it provides a necessary framework for continuously improving your AI application's quality and reliability.

Is Fallom suitable for large-scale enterprise deployments?

Fallom is built specifically for enterprise-scale and compliance-focused requirements. It offers the security features, audit capabilities, and reliable data handling that regulated industries demand. The platform can handle high-volume traffic, provides detailed per-customer analytics, and supports the complex cost attribution needs of large organizations.

Top Alternatives to Fallom

TrafficClaw

Talk to your SEO & Analytics data - it finally talks back

Requestly

Requestly is the essential git-based API client that requires no login and instantly imports from Postman.

OpenMark AI

OpenMark AI benchmarks over 100 LLMs for your specific tasks, providing quick insights on cost, speed, quality, and stability without any setup.

OGimagen

Create stunning Open Graph images effortlessly with OGimagen's AI, optimized for all major social platforms and ready-to-use meta tags.

Fusedash

Fusedash transforms raw data into insightful dashboards and charts, empowering teams to act on insights instantly.

qtrl.ai

qtrl.ai empowers QA teams to scale testing with AI agents while ensuring complete control and governance throughout.

echoloc

Echoloc uncovers hidden buying signals in job posts, empowering sales teams to target ready-to-buy accounts effectively.

GrowPanel

GrowPanel delivers real-time subscription analytics to optimize MRR, churn, and LTV for high-growth SaaS businesses.

Compare with Fallom