Fallom

Fallom represents the next evolutionary stage in AI operations, an observability platform built from the ground up for the age of intelligent agents. It is designed for AI developers and enterprise teams who have moved beyond initial experimentation and are now scaling complex LLM and agent workloads in production. As these systems grow from simple prompts to intricate, multi-step workflows involving tools, databases, and conditional logic, traditional monitoring tools fall short. Fallom fills this critical gap by providing a comprehensive, real-time window into every LLM interaction. It captures the full spectrum of data—prompts, outputs, tool calls, token usage, latency, and costs—transforming opaque AI operations into a transparent, manageable, and optimizable system. Its core value proposition is enabling businesses to progress from merely deploying AI to mastering it, ensuring reliability, controlling spend, and maintaining compliance as their AI initiatives mature and evolve.

End-to-End LLM Tracing

Fallom provides complete, OpenTelemetry-native tracing for every LLM call and agent action. This goes beyond simple logging to deliver a visual, interconnected map of your AI workflows. You can see the exact sequence of events, from the initial user prompt through intermediate tool calls and reasoning steps to the final response. This granular visibility is essential for debugging complex issues, understanding the "why" behind an agent's behavior, and optimizing the entire chain for performance and cost-efficiency.

Real-Time Cost Attribution & Analytics

Gain precise financial control over your AI spend with Fallom's detailed cost attribution engine. The platform automatically breaks down expenses by model, individual API call, user, team, or even specific customer sessions. This transparency is crucial for teams progressing from project-based budgets to company-wide AI rollouts, enabling accurate chargebacks, forecasting, and identifying optimization opportunities to ensure your AI investment delivers maximum return.

Compliance-Ready Audit Trails

Built for regulated industries, Fallom ensures your AI operations evolve without compliance risk. It maintains immutable, detailed audit logs of every interaction, including full input/output logging, model versioning, and user consent tracking. These features are foundational for adhering to frameworks like the EU AI Act, GDPR, and SOC 2, providing the evidence and control needed to scale AI responsibly and with full accountability.

Advanced Debugging with Tool & Session Context

Debugging agents requires understanding context. Fallom groups related traces into user or customer sessions, providing a holistic view of interactions over time. Furthermore, it offers deep visibility into every tool and function your agents call, displaying arguments and results in detail. This combination of session-level context and tool call visibility turns debugging from a frustrating hunt into a streamlined, efficient process.

Scaling Enterprise AI Agent Deployments

For enterprises transitioning AI agents from pilot programs to core business operations, Fallom provides the operational backbone. It allows platform teams to monitor the health, performance, and cost of hundreds of concurrent agent workflows, ensuring reliability for end-users and providing the data needed to justify further investment and expansion of AI capabilities across the organization.

Optimizing Cost and Performance of LLM Workloads

Development teams use Fallom to move from a "set and forget" model deployment to a continuous optimization cycle. By analyzing latency waterfalls, token usage patterns, and cost-per-call data, engineers can experiment with different models, prompt structures, and architectures. This data-driven approach leads to faster, cheaper, and more reliable AI features, directly improving the product's bottom line and user experience.

Ensuring Regulatory Compliance for AI Applications

Companies in finance, healthcare, or legal services use Fallom to build and audit compliant AI applications. The platform's detailed audit trails, consent tracking, and privacy controls provide the necessary documentation for internal reviews and external regulators. This enables these companies to innovate with AI while systematically managing risk and upholding their legal and ethical obligations.

Improving Customer Support with AI Analytics

Product and customer success teams leverage Fallom's session tracking and customer analytics to understand how users interact with AI features. They can identify power users, spot common failure points in conversations, and attribute support costs to specific clients. These insights guide product improvements, training data collection, and customer-specific model fine-tuning, evolving the AI from a generic tool to a tailored asset.

How quickly can I integrate Fallom into my existing application?

Integration is designed for rapid progression from setup to insight. With its single, OpenTelemetry-native SDK, you can typically instrument your LLM calls and start seeing traces in your Fallom dashboard in under five minutes. The platform works alongside your existing code, requiring minimal changes to begin collecting comprehensive observability data.

Does Fallom support all major LLM providers?

Yes, Fallom is built on open standards to prevent vendor lock-in and support your AI evolution. It is compatible with all major LLM providers, including OpenAI, Anthropic, Google Gemini, and open-source models. This means you can use a unified observability platform regardless of how your model strategy changes or expands over time.

How does Fallom handle sensitive or private user data?

Fallom includes enterprise-grade privacy controls for regulated environments. You can enable Privacy Mode, which allows you to capture full telemetry and trace data while redacting or disabling the logging of actual prompt and response content. This lets you maintain operational visibility and compliance auditing without storing sensitive information.

Can I use Fallom for testing and evaluating my LLM prompts?

Absolutely. Fallom includes features for running evaluations on LLM outputs, allowing you to track metrics like accuracy, relevance, and hallucination rates. Coupled with its Prompt Store for version control and A/B testing, it creates a robust framework for continuously improving your prompts and catching regressions before they impact production users.