- Corporate finance and FP&A teams running monthly close, forecasts, and board reporting
- Operators and GMs who need quick answers to “one more question” from leadership
- RevOps and analytics teams that want depth without spinning up new dashboards every time
- Analyze – Chat with your financial data, drill into drivers, and iterate quickly
- Report – Turn numbers into narratives with AI-generated commentary you can edit and reuse
- Forecast – Run scenarios and projections on live data so decisions are grounded in reality
How Concourse is different from traditional BI
Traditional BI tools are great for static dashboards and pre-defined metrics. They are slow at:- Answering new questions that do not fit existing dashboards
- Explaining the “why” behind a number
- Helping you ship board narratives or close packages on a tight deadline
- Freeform questions and follow-ups (“what changed and why?”, “show this by cohort”, “add a forecast”)
- Fast narrative generation for close reviews, board decks, and investor updates
- Direct ownership by finance and operators, without needing a dedicated analytics engineer for every change
How Concourse is different from generic chatbots / OOTB LLMs
Generic chatbots are not connected to your systems of record. They do not know your chart of accounts, metrics, or business model, and they often hallucinate numbers. Instead of relying on a generic chatbot, Concourse stacks domain expertise on top of the best foundation models. We layer finance and operator‑specific knowledge, schemas, and workflows on top of state‑of‑the‑art LLMs so the AI:- Understands common finance and FP&A patterns out of the box
- Knows how to work with real-world data structures from ERPs, CRMs, and warehouses
- Prioritizes correctness and clarity over “creative” answers
Transparent by design
Most AI tools answer in a black box. Concourse is built to show its work. When you ask a question, Concourse:- Surfaces the agent’s reasoning steps so you can see how it approached the problem
- Exposes the exact SQL queries it runs against your data sources
- Lets you inspect and rerun those queries so you can validate numbers and tweak the analysis
- Numbers tie back to trusted systems and auditable logic
- You can always trace a chart or narrative back to the underlying data and query
- Disagreements turn into concrete edits to logic or assumptions, not arguments with a black box