Features
Everything you need to audit Excel financial models, build leveraged buy-out structures from assumptions, visualise cashflows and waterfalls, and keep deal data secure—with AI and Python powering the workflow in LBOstack.
Open the app- Audit Excel financial models
- Build leveraged buy-out models from assumptions
- Flex scenarios and sensitivity in seconds
- Visualise cashflows and waterfall graphs
- AI and Python under the hood

One platform for audit, build, and outputs
LBOstack connects Excel upload, structured assumptions, LBO modelling, and visual reporting—so your team does not jump between disconnected spreadsheets and slide decks.
Use AI-assisted review to catch issues early, flex scenarios and sensitivity on key drivers, and publish cashflow and waterfall views your team can take straight into deal team review and lender materials.
See financial models
Built for the full deal workflow

Audit and assumptions. Upload Excel, validate structure and drivers, and build from a clear assumptions base before you extend debt and equity schedules.

LBO model and visuals. Construct leveraged buy-out models and visualise cashflow statements, sweeps, and waterfall graphs for deal team review and lender materials.

Scenarios, sensitivity, and AI. Flex scenarios and sensitivity tables in seconds, with AI and Python accelerating review and repeatable calculations behind the scenes.

What LBOstack includes
Six core capabilities—from Excel audit through LBO build, assumptions, visualisation, flex scenarios and sensitivity, and AI with Python.
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Audit an Excel financial model
Upload workbooks and run structured checks on assumptions, formula links, circularities, and key outputs. Findings trace back to cells so reviewers can fix issues before deal team or lender sign-off.

Build a leveraged buy-out model
Work with specialised LBO layouts—senior and subordinated debt, cash sweeps, equity waterfalls, and exit-driven returns—structured the way deal teams expect.

Build from basic model assumptions
Start from a clear assumptions tab: revenue drivers, margins, capex, working capital, and financing inputs flow through to statements without hiding logic in one-off cells.

Visualise cashflows and waterfall graphs
See period-by-period cashflow statements, debt paydown, and distribution waterfalls in charts and tables suited to memos, deal team review, lender materials, and working-group updates.

Powered by AI and Python
AI assists extraction, review, and model extension; Python supports heavier data work and repeatable calculations behind the scenes—Excel remains your source of truth.

Flex scenarios and sensitivity in seconds
Spin up base, upside, and downside cases without rebuilding the workbook, then stress growth, margins, leverage, rates, and exit multiples to see IRR, MOIC, and covenant headroom update fast enough for live deal team and lender conversations.
Version control and secure storage
Keep every upload, model run, and output traceable per project and organisation—so deal teams know what changed, when, and who can access it.

Version control
Track model versions and review runs over time so teams know which workbook, assumptions, and outputs were used for each decision, deal team review, or lender pack.

Secure storage of uploaded data
Project-scoped, organisation-bound storage for uploaded files and outputs—built for teams that need traceability, access control, and encrypted handling of deal data.
Start auditing and building in LBOstack
Upload your workbook, run audit checks, build from assumptions, and share cashflow and waterfall outputs—with version history and secure storage for your organisation.

How teams use it
1
Upload securely
Store Excel models and supporting files in project-scoped, organisation-bound storage with access control.
2
Audit and build
Run audit on the workbook, refine assumptions, and extend leveraged buy-out schedules with AI-assisted workflows.
3
Visualise and version
Generate cashflow and waterfall views, track versions over time, and export outputs for deal team review and lender materials.




