FinburgH helps VCs and AI/SaaS startups turn data into investor-ready financial models for fundraising
Be well prepared for your next move - we help you scale.
We help you become Investor-Ready
- overall we built over 50 financial models
- our clients are in Italy, Switzerland, France, Germany, Cyprus, Greece, USA
- we are expanding across Europe
- financial model in 3-4 weeks
- fundraising investor deck in 1 week
- fixed price official contracts
- CFO further retainer to scale your business
We turn your data into investor-ready financial models for fundraising
Is this you?
Is this you?
- You are raising seed/series A rounds but your current model is not fit for investors to scale?
- You need valuation and a clean raise story?
- Are you a VC with portfolio AI/SaaS startups or a founder of a AI/SaaS startup in Europe/ USA?
What you get:
- High Quality
- Investor-grade valuation models or fundraising models or project models
- Valuation and WACC calculation based on comparables
- 3 scenario cases, sensitivity analysis
- Clear defendable assumptions and investor-ready outputs
- Concise pitch deck for investors/ Board deck that corresponds the model
- a trusted CFO partner before investor review
- High professional standardsWe follow IVS (international valuation standards), all our analysts are professionally trained, certified and use FMVA / CFA methodology for the models we build
- You get Tailored Approach - we build each pack and each model ONLY for youYour business is unique and deserves a tailored approach. You will have a designated senior financial analyst who is responsible for your model and a CFO review before each release.
Book a 30' fit call
Why do most internal models fail investor review?
Internal models are often built for estimation.
Investor-ready models are built for diligence, funding, and decision-making.
Internal models are often built for estimation.
Investor-ready models are built for diligence, funding, and decision-making.
Check, if your current model has a hypothetical "top down" logic or is anchored in contract-based "bottom up" approach FinburgH mainly uses. Usually in-house models do not reflect the language the investors speak and it's hard for you to explain:
- valuation logic and WACC calculation
- monthly cash timing
- inventory DSO forecasted / working capital
- debt sizing or CapTable
- complex R&D issues
- up & downside cases and sensitivity analysis
- use-of-funds logic
- complete schedules for all parts of 3-Statement model
How the sprint works?
We always work under an official contract - our office is based in Milan, Italy and we work across Europe
You call or write to WhatsApp
You call or write to WhatsApp
We schedule a 30' fit call
At the call
At the call
We discuss your business need, determine the scope
Within 48 hrs
Within 48 hrs
We send you a proposed Scope of Work, initial data / assumptions requirements, NDA contract
Contract signature & 1st payment
Contract signature & 1st payment
Sign-off on the initial data / assumptions/ drivers/ model structure
Model Review Session & 2nd payment
Model Review Session & 2nd payment
Minor adjustments within the SOW
3rd payment
3rd payment
Complete pack, final delivery
Book a 30' fit call. You can come with a broken internal model, partial project data, or a blank sheet
Some of our cases:
Get a full control in your capital conversations. We are here to translate your vision into numbers and speak the same language with your potential investors.
We built over 50 complex financial models across Europe and USA up to investment-grade standards, including: 3-Statement Model, DCF, M&A, LBO, project models, and other.
We calculate project economics, so you can clearly understand your key parameters, monitor their dynamics, and manage them effectively.
We design not only top-down valuation models but also complex bottom-up dynamic financial models that become a copilot for your business operations, helping you identify the right mix of products and sales channels to maximize and stabilize profits.
We are here to help you scale – we also provide CFO services for selected companies.
We built over 50 complex financial models across Europe and USA up to investment-grade standards, including: 3-Statement Model, DCF, M&A, LBO, project models, and other.
We calculate project economics, so you can clearly understand your key parameters, monitor their dynamics, and manage them effectively.
We design not only top-down valuation models but also complex bottom-up dynamic financial models that become a copilot for your business operations, helping you identify the right mix of products and sales channels to maximize and stabilize profits.
We are here to help you scale – we also provide CFO services for selected companies.
DeepTech (AI/ SaaS Logistics Platform for Drone Operations), Germany | Financial Model & Valuation
Founder-led AI SaaS logistics platform for autonomous drone operations combining proprietary flight-control software, in-house R&D and production needed an investor-grade financial architecture to support fundraising and scaling.
What was wrong before: An internal model existed but lacked integrity across revenues, R&D, production, and logistics operations. It did not include valuation logic, WACC, ARR and churn metrics, or unit-economics analysis by route. Forecasts were difficult to reconcile with ERP accounting numbers, and maintaining consistent versions in the dataroom became increasingly difficult as investor questions grew.
What we delivered: A fully integrated model covering ARR build-up, churn, CAC/LTV, route-level unit economics, and scenario analysis for commercialization. R&D spending was structured with capitalization under IAS 38 (IFRS), and the model included valuation, WACC, and sensitivity of valuation to growth, margin, and risk assumptions.
Outcome: The founder moved from defending spreadsheets to controlling the narrative with faster Q&A, clean dataroom management, and a model that stayed current as accounting data updated. As a result, they unlocked PE financing.
What was wrong before: An internal model existed but lacked integrity across revenues, R&D, production, and logistics operations. It did not include valuation logic, WACC, ARR and churn metrics, or unit-economics analysis by route. Forecasts were difficult to reconcile with ERP accounting numbers, and maintaining consistent versions in the dataroom became increasingly difficult as investor questions grew.
What we delivered: A fully integrated model covering ARR build-up, churn, CAC/LTV, route-level unit economics, and scenario analysis for commercialization. R&D spending was structured with capitalization under IAS 38 (IFRS), and the model included valuation, WACC, and sensitivity of valuation to growth, margin, and risk assumptions.
Outcome: The founder moved from defending spreadsheets to controlling the narrative with faster Q&A, clean dataroom management, and a model that stayed current as accounting data updated. As a result, they unlocked PE financing.
AI/ SaaS Longevity MedTech Platform for preventive monitoring, Italy
Founder-led AI-based SaaS startup, needed CFO services to preserve their runway, establish ERP system and budgeting. We started with preparing a complete pack with several financial models for M&A, fundraising and subsequent operations in Europe.
What was wrong before: Only internal Excel files existed, built for operational use rather than institutional fundraising. They did not translate the business into core SaaS and MedTech metrics. They also could not support transaction work - no valuation logic, no merger mechanics, no post-merger integration view, and no dedicated fundraising model tied to use of proceeds.
What we delivered: Our model included cohort retention, CAC by each acquisition channel, LTV, payback period, recurring vs non-recurring revenue mix, gross margin by service layer, scaling efficiency by site type.
Outcome: The company moved from internal spreadsheets to a PE-grade capital-raising package that explained not just growth, but the quality of growth. The result was a model founders could defend, investors could diligence, and the company raised private equity capital.
What was wrong before: Only internal Excel files existed, built for operational use rather than institutional fundraising. They did not translate the business into core SaaS and MedTech metrics. They also could not support transaction work - no valuation logic, no merger mechanics, no post-merger integration view, and no dedicated fundraising model tied to use of proceeds.
What we delivered: Our model included cohort retention, CAC by each acquisition channel, LTV, payback period, recurring vs non-recurring revenue mix, gross margin by service layer, scaling efficiency by site type.
Outcome: The company moved from internal spreadsheets to a PE-grade capital-raising package that explained not just growth, but the quality of growth. The result was a model founders could defend, investors could diligence, and the company raised private equity capital.
AI/ SaaS EdTech, Italy | AI-based Career Development Platform | Financial Model & Fundraising Pack
Founder-led AI EdTech platform focused on career development, skills mapping, and employability pathways needed an investor-grade financial model to support fundraising and scaling.
What was wrong before: Internal spreadsheets existed, but they did not translate the business into core SaaS and EdTech metrics. There was no clear logic for ARR build-up, churn, CAC by acquisition channel, or revenue split between recurring subscriptions and non-recurring services. The model also lacked valuation logic and a clear view of how commercialization pace affected runway and funding needs.
What we delivered: A fully integrated model covering ARR, churn, CAC/LTV, cohort retention, payback, gross margin by service layer, and unit economics by learner / enterprise client segment. We added scenario analysis for commercialization pace, cash runway, fundraising needs, and sensitivity of valuation to growth, margin, and risk assumptions.
Outcome: The founder moved from generic planning files to an investor-ready finance pack that made the growth story measurable, defensible, and easier to explain in fundraising discussions.
What was wrong before: Internal spreadsheets existed, but they did not translate the business into core SaaS and EdTech metrics. There was no clear logic for ARR build-up, churn, CAC by acquisition channel, or revenue split between recurring subscriptions and non-recurring services. The model also lacked valuation logic and a clear view of how commercialization pace affected runway and funding needs.
What we delivered: A fully integrated model covering ARR, churn, CAC/LTV, cohort retention, payback, gross margin by service layer, and unit economics by learner / enterprise client segment. We added scenario analysis for commercialization pace, cash runway, fundraising needs, and sensitivity of valuation to growth, margin, and risk assumptions.
Outcome: The founder moved from generic planning files to an investor-ready finance pack that made the growth story measurable, defensible, and easier to explain in fundraising discussions.
Prices are within the market range. You do not want to look underprepared when investors, lenders, or partners start digging into the numbers. Get in touch!