#fintech Startups & Tools
Discover the best fintech startups, tools, and products on SellWithBoost.
Multifamily deal analysis has a speed problem. Syndicators managing active pipelines routinely invest 40 hours normalizing broker packets, cleaning rent rolls, and building underwriting models for a single deal. KeptDo Multifamily Deal Analyzer Pro attacks this bottleneck by automating the grunt work and compressing that analysis into a two-hour workflow. The platform targets syndicators and operators underwriting more than 30 deals annually and managing between $5 million and $200 million in assets. The value proposition is straightforward: take a broker offering memorandum, T-12, T-3, and rent roll, upload them, and receive a production-ready underwriting package including returns models, sensitivity analysis, market comparables, and even a drafted letter of intent. What distinguishes KeptDo is that it was built by Manny Del Val, a syndicator and IT professional with 25 years of technology experience, rather than by software engineers unfamiliar with multifamily operations. This pedigree shows in the product's workflow. It normalizes data across disparate sources, flags inconsistencies and discrepancies, generates five-year projections, and produces investor pitch decks—the entire stack of deliverables deal sponsors need. The system recognizes that speed matters in competitive deal environments. When twenty operators are reviewing the same offering memorandum, the ones who can present a defensible LOI Wednesday afternoon outmaneuver those still formatting tabs Thursday night. The platform is already in use by operators across Arizona, California, Florida, Tennessee, Kentucky, South Carolina, and Texas. Pricing starts at $99 monthly, with a 14-day free trial available to prospective customers. The company, founded in 2026 and based in Satellite Beach, Florida, plans to expand its offering with additional tools for multifamily operators. KeptDo addresses a real pain point in commercial real estate—the conversion of raw broker data into actionable underwriting. By automating data normalization and model construction, it removes a major friction point from the deal pipeline, freeing operators to focus on strategic decision-making rather than spreadsheet hygiene.