Fallom

Fallom is the AI-native observability platform that's taking the industry by storm, built from the ground up for the era of Large Language Models (LLMs) and autonomous agents. It solves the critical "black box" problem for engineering and product teams deploying AI in production. While traditional monitoring tools fall short, Fallom provides granular, end-to-end visibility into every single LLM call, tool invocation, and multi-step workflow. Imagine seeing a real-time dashboard of every AI interaction—prompts, outputs, tokens, latency, and exact costs—allowing you to instantly debug a failing agent, optimize a slow chain, or explain a cost spike. Trusted by fast-moving startups and global enterprises alike, Fallom is essential for anyone serious about building reliable, cost-effective, and compliant AI applications. Its unique value lies in unifying cost attribution, performance debugging, and compliance auditing into a single, OpenTelemetry-native platform that you can integrate in under five minutes, finally giving teams the control they need over their AI operations.

Real-Time LLM Call Tracing

See every interaction as it happens with a live, queryable trace table. Drill down into individual calls to inspect the exact prompt, model response, tool calls with arguments, token usage, latency, and per-call cost. This granular visibility is the foundation for debugging complex agent failures and understanding exactly what your AI is doing in production, turning opaque processes into transparent, actionable data.

Granular Cost Attribution & Analytics

Move beyond vague cloud bills. Fallom automatically breaks down your AI spend by model, user, team, session, or even specific customer. Visual dashboards show you exactly where every dollar is going—whether it's GPT-4o, Claude, or Gemini—enabling precise budgeting, showback/chargeback, and data-driven decisions to optimize for cost-performance without sacrificing quality.

Enterprise Compliance & Audit Trails

Built for regulated industries, Fallom provides immutable, complete audit trails of all AI activity. It logs inputs, outputs, model versions, and user consent, directly supporting requirements for GDPR, the EU AI Act, and SOC 2. Features like configurable privacy mode allow you to redact sensitive data while maintaining full telemetry, ensuring you can deploy AI with confidence.

Advanced Workflow Debugging Tools

Debug complex, multi-step agentic workflows with ease. The timing waterfall visualization breaks down latency across LLM calls and tool executions to pinpoint bottlenecks. Simultaneously, full tool call visibility lets you inspect every function call, its arguments, and returned results, making it simple to identify logic errors or external API failures in intricate chains.

Optimizing AI Agent Performance & Reliability

Engineering teams use Fallom to monitor live AI agents handling customer support, data analysis, or booking tasks. By analyzing latency waterfalls and tool call success rates, they can quickly identify and fix performance bottlenecks, reduce error rates, and ensure a reliable user experience, leading to higher customer satisfaction and trust in their AI products.

Controlling and Forecasting AI Operational Costs

Finance and engineering leaders leverage Fallom's cost attribution dashboards to gain full transparency into unpredictable AI spending. They track costs per project, team, or feature, forecast budgets accurately, implement chargebacks, and identify opportunities to switch models for less expensive calls without impacting output quality, directly improving unit economics.

Ensuring Regulatory Compliance for AI Deployments

Legal and compliance teams in healthcare, finance, and enterprise software rely on Fallom to generate the necessary audit trails for AI governance. The platform logs all required data—prompts, responses, model versions, and user consent—providing a verifiable record to demonstrate adherence to GDPR, AI Act, and internal policy requirements during audits.

Improving AI Products with Data-Driven Insights

Product managers and developers use Fallom's session tracking and customer analytics to understand how users interact with AI features. They identify power users, analyze common query patterns, and A/B test different prompts or models using the integrated prompt store and traffic splitting, using real data to iterate and improve product offerings.

How quickly can I integrate Fallom into my existing application?

Integration is famously quick. With the single, OpenTelemetry-native SDK, most teams are sending their first traces and seeing data in the Fallom dashboard in under 5 minutes. There's no need to rip and replace your existing infrastructure; it layers seamlessly on top of your current LLM calls and agent frameworks.

Does Fallom support all major LLM providers and frameworks?

Absolutely. Fallom is provider-agnostic and works with every major provider, including OpenAI (GPT), Anthropic (Claude), Google (Gemini), Cohere, and open-source models. It also integrates with popular agent frameworks like LangChain and LlamaIndex. The OpenTelemetry foundation ensures zero vendor lock-in.

How does Fallom handle sensitive or private user data?

Fallom is built with enterprise-grade privacy controls. You can enable "Privacy Mode" to disable full content capture, logging only metadata like token counts and latency. For more granular control, configurable redaction rules allow you to strip specific PII or sensitive keywords, ensuring compliance with strict data handling policies.

Can I use Fallom to A/B test different models or prompts?

Yes, Fallom includes first-class support for experimentation. You can split traffic between different models (like GPT-4o and Claude 3.5) or different versions of prompts stored in the Prompt Store. The dashboard then lets you compare their performance, cost, and quality metrics side-by-side to make informed, data-driven deployment decisions.