Launching today
Montty Finance
Make CFO-level decisions in seconds
66 followers
Make CFO-level decisions in seconds
66 followers
Our mission is to reduce financial workload and make finance clear and easy. Montty is built on three principles: holistic, human-centered, and personal. We bring multiple financial functions into one platform, offer an AI assistant that talks in natural language, and deliver insights tailored to your own data. From AI receipt capture to seamless imports, Montty gives you accounting and intelligence together, all tailored to you.
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When a founder asks whether they can afford a new hire, is the AI pulling from a pre-built financial model template in the background, or is it dynamically constructing the logic from the user's own uploaded data each time? Because those two architectures have very different accuracy ceilings
@ritesh_bhakare1 Thank you for your question—it's a very interesting one. AI systems are guided by established safety frameworks, which ensure that responses are grounded in the specific context and inputs provided by the user. At the same time, they take into account widely accepted practices within the relevant domain.
As a result, each response is tailored to the individual query rather than drawn from a fixed or prewritten source. Instead, the system relies on a structured approach to generate clear, relevant, and thoughtful answers.
Does the AI CFO retain context across sessions like if I told it last week that I'm planning a fundraise in Q3, does it factor that into this week's runway answer? Or does each conversation start cold?
When Montty gives a forecast, does it surface any confidence interval or uncertainty range like 'your runway is 14 months, but could be 11-17 depending on churn variance'? Or is it always a single point estimate? Because a false precision problem could seriously mislead a founder.
When a founder asks 'can I afford a new hire' is the AI pulling from a pre-built financial model template in the background, or is it dynamically constructing the logic from the user's own uploaded data each time? Because those two architectures have very different accuracy ceilings.