Cifra
AI Cash-Flow Intelligence for Multi-Entity Retail
Cash-flow management for a multi-entity retail operation: five Excel sources consolidated into a 38-category model, with an AI agent on top.
- Cash-flow categories
- 38
- Group entities
- 5
- Real records tested
- 27K+
The problem
A multi-entity group's cash flow lives scattered across spreadsheets — daily sales, domestic and international payables, purchase projections, bank statements — and consolidating it by hand arrives too late to decide with.
How it works
Cifra ingests the five source file types and consolidates them into a 38-category cash-flow model — operating, investing, financing — across the group's entities. On top, a conversational agent with seven specialized tools and what-if scenario simulation. Tested with 27,000+ real Yáneken records.
What it does
- 01
Automatic consolidation
Five Excel sources in; one 38-category model out, entity by entity.
- 02
Conversational agent
Seven specialized tools for querying the cash flow in natural language.
- 03
What-if scenarios
Scenario simulation on the model, before committing real cash.
Limits
Built and tested against 27,000+ real Yáneken records, not deployed as a system of record. Consolidation depends on the five source files keeping their format.
Related projects
- ChispezaVoice AI for Retail Hiring and Sales Training
- DraperAI Customer Decisioning for Omnichannel Retail
- IRISMultimodal AI for Retail Store Operations
Status and figures: August 2026
If you recognize this problem in your business, let’s talk. For an implementation with my team, the advisory work lives at Menlo & Oak.