Drivetrain
AI-native FP&A with an MCP server for finance: autonomous forecasting and plain-English answers on live data.
About
Drivetrain is an AI-native business planning platform for finance teams that want autonomous FP&A rather than another reporting layer. It connects ERP, CRM, HRIS, and billing data through 800+ integrations, centralizes metric logic in its own modeling language, and runs AI features on top: an AI Analyst that answers plain-English questions with charts and variance breakdowns, an AI Model Generator that builds a baseline model from your systems, and anomaly detection across revenue, spend, cash, and headcount.
In October 2026 it launched the first MCP server for finance, letting AI agents like Claude work against governed finance data with policy guardrails. Founded in 2021, it serves companies in 17+ countries and holds a 4.8/5 G2 rating. The tradeoff is scope: it can be overkill for teams with simple models, pricing is quote-based, and the platform is closed, so you live inside its modeling world once adopted.
What it can do
- AI Analyst answering finance questions in plain English with charts and variance breakdowns
- AI Model Generator building baseline models from ERP, CRM, HRIS, and billing data
- First MCP server for finance with policy-driven guardrails (Oct 2026)
- Continuous anomaly detection on revenue, spend, cash, and headcount
- Multi-dimensional modeling with DTML and multi-entity consolidation
Setup
Connect ERP, CRM, HRIS, and billing via 800+ integrations; the AI Model Generator builds your baseline financial model automatically.
Prerequisites
Use cases
Works with
Trust score — 7/10
Scored 7/10 (verified tier, metrics-v1). Evidence: founded 2021; 800+ integrations; customers in 17+ countries; 4.8/5 on G2; launched the first MCP server for finance (Oct 2026). Strengths: genuinely AI-native with agentic tooling, broad integration coverage, Excel-like modeling interface. Docked for: (1) closed platform; (2) quote-based pricing; (3) overkill for teams with simple models. License: proprietary.
How the trust score is built
Full methodology →- Adoption · stars/downloads, log-scaled vs peers
- 7.0/10
- Maintenance · recency, releases, issue load
- 8.0/10
- Openness · license + docs
- 5.0/10
- Manual review · sanity read + red-flag check
- 7.0/10
- · Founded 2021; 800+ integrations; customers in 17+ countries; 4.8/5 on G2
- · Launched first MCP server for finance (Oct 2026) with policy guardrails
- · AI Analyst, AI Model Generator, anomaly detection on revenue/spend/cash/headcount
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.