Date: 16.01.2026 (2026-01-16)
Monica Todor (16.01.2026) Context: • https://www.linkedin.com/in/monica-todor-5ab54a72/ • VP of Finance & Legal at AVOW GmbH (75 ppl) • Berlin now; from Cluj (Romania) • My message: • I came across your profile because I saw your post about AI from 3 months ago - so I am assuming you are testing AI for Finance as well. • • We are currently at a crossroads regarding our product roadmap and are looking for a "view from the field." • Specifically, we’re weighing where AI will provide the most long-term ROI for finance teams: supporting monthly close & financial closing, or in procurement & purchasing (transparency, cost savings, supplier management)? • • For context: We’ve built technology that automates Accounts Payable with minimal human intervention. The system only flags ambiguous cases for manual approval, providing the full context needed to resolve them instantly. • Reply: • Sure, i am glad to help, if my input could be of value. This week is quite packed, but i could find a time to connect next week. Would you like to share a calendar from which i can choose a slot?
Notes: • Notes: • • Automation: • • Biggest objections / challenges in his daily life? • Data accuracy is the biggest problem • They work in adtech • Data is very fragmented to go into BI tool -> having it correct and in one system • Data: • Top line: Revenue and Cost of Sales • Both is covered by invoices • Problem: invoices show a total - not line item basis • Line item basis data is coming via APIs or also sometimes CSV uploads • They are 80 people - owned by founders that are inhouse • There are always exceptions to processes • C-Level always does exceptions • E.g. travel budgets are defined; person has to go higher; management says we do exceptions; • E.g. Bonuses for people • Approvals: • Example: they want a new tool -> manager approves -> manager sends email to billing -> then approval in email thread -> then VCC (Moss) • They have Steuerberater outsourced -> they are always a bit late • AI currently used: • Legal side: she uses it a lot • She uses it for tax topics -> they have a lot of different countries -> understand the situation • She used it for creating reports - e.g. CLV - results was mixed (they use paid version of Gemini) • AI potential: • Reporting analytics, Forecasting • AR side: • Overdue follow ups - that already exists already there - always the basic -> fixed template and time • -> improving it • When there is non response, somebody has to check and check the contract to see if they can charge interest • Different tone - also based on country: tone for IND and China also chat on WeChat • Most valuable flows for him? • • Context: team setup? internal and external? • • Which tasks are the biggest pain? With magic wand -> what would he solve? • • Which tasks would he focus on? • • Do they already have automations? Which ones? How well do they work? • • Which companies would he target? • • General feedback to pitch? •