Slashboard is a real-time cost tracking and analytics platform designed for monitoring expenses associated with large language model (LLM) applications. It functions as an observability tool that aggregates cost data across models, teams, and individual requests into a single dashboard. The platform is built to provide immediate visibility into AI spending, allowing users to see cost breakdowns by various dimensions such as model type, team, feature, or user. It operates on a hosted SaaS model, requiring no local infrastructure, and users can begin sending data by making a single POST request to an API endpoint. The platform offers several key features for managing LLM spend. It provides real-time spend tracking with updates within seconds of a call being made. Users can set budgets and receive alerts via Slack or email when spending approaches predefined limits. The system includes built-in attribution, allowing requests to be tagged by team, feature, user, or environment for granular cost analysis. Slashboard also features a server-side cost calculation using a maintained price catalogue. Importantly, the platform is designed to be PII-safe by default, storing only metadata and cost data, with prompt and response bodies being strictly opt-in. Typical use cases involve engineering teams and financial stakeholders who need to monitor and control the costs of deployed AI applications. The workflow begins with signing up for the service and obtaining an API key. Users then integrate Slashboard by making a single HTTP POST call to its ingest endpoint for each LLM request, or by using a callback file for LiteLLM integrations. Once data is flowing, users can explore the dashboard to see aggregated spend, drill down from a cost spike to the specific requests that caused it, and set up budgets to prevent overspending. The platform is designed to work with any LLM provider and can be integrated without installing an additional SDK.