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Bridge Town is AI-native financial planning software. AI is not a feature layered on top of an existing tool — it is the primary interface for building and maintaining financial models. FP&A teams describe planning logic in plain English; Bridge Town's AI agent writes the Python, connects the data, and runs the model. This page explains what AI-native means in financial planning and how it differs from tools that have added AI features.
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AI-native (Bridge Town)
Describe your planning model
An FP&A analyst writes a plain-English description of the model they need. For example: "Build a revenue forecast that takes monthly bookings by segment, applies a churn rate, and outputs ARR and net new ARR for the next 18 months."
AI writes and runs the model
Bridge Town's AI agent produces the Python model logic, connects the input data, and runs the model in a sandboxed compute environment. The analyst sees the output alongside the code that produced it.
Review, adjust, and iterate
The analyst reviews outputs, asks for adjustments in plain language ("change the churn rate assumption to 2% for the enterprise segment"), and the AI updates the model. Each change is committed to the project history.
Publish the versioned model
Once the model is approved, the analyst publishes it. The final version, its full history, and all run outputs are stored in the project. Team members can review the model, re-run it with updated data, or branch it for scenario analysis.
AI-native means AI is the primary interface for creating and modifying financial models — not a feature added on top of an existing spreadsheet or formula tool. In AI-native financial planning software, analysts describe what they want in plain language, and an AI agent produces the model logic, connects the data, and runs the model. The AI is not optional or supplementary; it is the core authoring layer.
Most financial planning tools with AI features use AI to suggest formulas, auto-complete entries, or generate natural-language summaries of existing data. The underlying model is still created and maintained by the user. Bridge Town inverts this: the AI agent creates and maintains the model based on the analyst's description. The analyst reviews, adjusts, and publishes — rather than building the model cell by cell.
Bridge Town is designed for FP&A teams at growth-stage and mid-market companies that need to build, maintain, and iterate on planning models without large engineering or specialist resources. Analysts with strong finance domain knowledge but limited coding experience can use Bridge Town because the AI handles the Python. Teams that want faster model iteration, cleaner audit trails, and fewer spreadsheet-maintenance cycles benefit most.
No. The AI agent in Bridge Town authors model logic — it writes Python code based on what the analyst describes. Business assumptions, planning judgment, and final model approval remain with the finance team. The AI handles the implementation layer; analysts provide the domain knowledge and review every output before it is published.
Bridge Town supports headcount and compensation modeling, revenue forecasting, cost and expense planning, budget-to-actual variance analysis, and multi-scenario analysis. Analysts can describe any of these in natural language and receive a running model that can be refined, versioned, and shared with the team.
Bridge Town is free to start. Describe your planning workflow in plain English and get a running model in your first session.
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