Finance teams
A shared AI agent for analysts building a model
Vrittara gives analysts one AI agent session to build a model together. The agent lays out an assumptions table with sources, the formulas and each scenario in the open, teammates correct inputs as it runs, and totals must be recomputed independently before the model is approved.
The problem with models nobody can trace
A model built in a private chat arrives as numbers with no trail. Reviewers cannot tell which figures came from the data room, which came from a colleague and which the AI assumed, so they either rebuild it or trust it blindly.
How the team builds the model together
Start from Build a model and attach the exports you have. PDF, Word, PowerPoint and Excel files are read on upload, with page and slide numbers kept. Every figure is either from a supplied file, from a teammate's note or marked as an assumption, and units and periods stay explicit.
Build a model
A forecast or model with every assumption on show.
Before anyone can approve the result, a reviewer confirms:
- Every assumption traces to a source or is marked as an assumption
- Totals were recomputed independently and match
- Units and periods are consistent throughout
More on shared agents
Common questions
- Can the agent read our spreadsheets and reports?
- Yes. PDF, Word, PowerPoint, Excel, text and CSV files are read on upload, and each step reads the passages relevant to what it is working on.
- How do we know an assumption is sourced?
- Before approval a reviewer must confirm every assumption traces to a source or is marked as an assumption, totals were recomputed independently, and units and periods are consistent.