1. No more “legacy assumptions” (a.k.a. data carryover errors) from past deal templates or linking errors from overworked juniors. The algorithm executes the exact same way each time from a blank slate. No Excel file can do this.

2. Layer on special situations on-demand – no more searching for the right template with the necessary components (e.g., M&A, dividend recaps, tax shields, etc.).

3. Junior deal team’s mindshare shifts from thinking about 50,000+ Excel formulas to thinking about the business you’re about to buy.

4. Mosaic models are saved in a standardized schema allowing for rich data analytics across a firm’s deals over time.

Faster – that’s how.

At private equity firms, the expectation is that incoming Associates know the foundations of modeling before they start – that’s why many firms have a modeling test or case study as part of the recruiting process.

The only way to learn modeling is to start from cell A1 of Book1. That’s not how Associates build models on the job – they typically do it from a past deal template forwarded to them by an Associate in the class above them.

What’s wrong with that? No one has accountability for the quality of that template. That template contains data and functionality from a previous deal that has nothing to do with the current deal you’re looking at.

The ideal way (with infinite time) would be to build each model from A1, Book1 – which is exactly how Mosaic does it each and every time.

Our philosophy at Mosaic is that on-the-job learning happens by being exposed to a volume of deals for different businesses. By thoughtfully selecting critical assumptions (revenue growth, exit multiple, etc.) and internalizing the impact on returns. You’re only an Associate in Excel for a couple of years – but you’re learning like this through a 30+ year career inside and outside of Excel.

Mosaic speeds up learning by reducing friction to building a model – meaning our investors analyze more situations per unit of time than investors without Mosaic would.

Our special situations library also serves as a reference tool for ongoing learning and development. Never learned how to model an IPO exit? Turn it on in Mosaic, and see exactly how the pros do it within the Excel download.

Finally, we believe our approach levels the playing field for candidates with diverse professional backgrounds and technical skillsets (e.g., consultants, lawyers, operators) to round out investment teams.

We agree – but it’s worth asking, why do we model to begin with? We’d argue it’s to learn “what we need to believe” from a forecast perspective to make a deal exciting to us. Sophisticated investors add complex structure at advanced stages to protect downside and / or share the upside – but this financial engineering is often (a) not relevant until the later stages of a deal and (b) rarely impacts returns around an investor's Base Case.

When the deal is advanced enough to warrant bespoke financial engineering, all Mosaic models are downloadable to Excel with linked formulas – meaning any final structuring can be added after Mosaic gets you to the 10-yard line.

Yes - and definitely more so than on a shared drive (or in an Excel attachment to an intern’s Reply-all email)!

Your data in Mosaic lives on Amazon Web Services’ servers (“AWS”). AWS is in our opinion the best provider of cloud infrastructure – meaning it would be hard to improve upon Mosaic’s security of the cloud (i.e., the infrastructure itself).

With respect to security in the cloud (i.e., what our team does to configure AWS such that we follow best-in-class security, availability and confidentiality practices), Mosaic has taken a security-first approach since Day-1 and has been SOC2 compliant since our first year of operation. Our SOC2 compliance and controls are audited regularly by a world-class audit firm, and we would be pleased to share our SOC2 Type 2 report with you upon request.