Date: 06.11.2025 (2025-11-06)
Andre Schneider (06.11.2025) • https://www.linkedin.com/in/andrevelososchneider/ • Head of Finance at Superchat (80ppl) • WA Automations
Notes: • Biggest challenges? • Setup: • Vorbereitende Buchhaltung -> 1 FTE -> then Steuerberater • Buchhaltungsthemen (he hears also from many other startups) • Pre-Accounting is super manual • CC: Moss, Amex und payments via bank konto • Datev Belege erfassen und reconciliation -> super painful • You have to do it via Moss and Datev • Moss has matching function -> works in 80% of cases • In Datev again stuff with Steuerkanzlei • Datev is super manual -> automated matching is not really good • Reconciliation • Sachen hinterher laufen • He wants an AI agent that does the pre-accounting • Put as many as possible out of Datev • At the end to Datev would be really good • Tax advisor work • Two big areas • 1 FTE that does vorbereitende Buchhaltung -> connect to Slack • AP Flow: • Person buys something via CC -> put the invoice • Accruals und Reconciliation is important -> I told him version 1.1 • AR is not a big topic because it is very automated • Tools: • Chargebee for billing • AR runs over that - they have a AR product but dont use it because it is expensive (dunning oder so haben sie inkludiert) • Hubspot as CRM • Stripe for payment • Qonto & Deutsche Bank • Pathway • Datev • Steuerkanzlei (they do not do Lohnbuchhaltung because it is complex) • Small in BER • Lohnbuchhaltungskanzlei • Debtist for Inkasso • He is interested how good it will work • Reconciliation is important • Important that it really covers 90%+; most platforms are promising • He talked to a lot of people who tried ChatGPT etc. -> search for a simple industry -> SaaS (their area) is super simple • When our solution is working we can notify him • Super interested that you can integrate all systems (plug and play) natively • Budgeting • They are VC backed -> what do VCs wants to see • internal budget -> inward looking • He looks a lot on historic data -> in startups not really belastbar -> e.g. they increased their marketing spend 4x this year • Helpful: benchmark with other startups that are ahead and similar • Deep Research is powerful but insights are limited - because data is not really available • He talked to people from other companies to learn from their experience -> a lot of assumptions • They think about market size, competition etc. • ChatGPT und Googlen is • Automation: • • Biggest objections / challenges in his daily life? • • 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? •