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JohhnyBox

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AI-powered tools that work as hard as you do.

The story

JohnnyBox is an all-in-one business operations platform built for small service businesses. It combines CRM, AI phone answering, appointment scheduling, customer messaging, invoicing, estimates, and simple marketing tools into a single dashboard. JohnnyBox was developed over approximately three years by a small software team after working with contractors, plumbers, HVAC companies, electricians, roofers, and local service businesses. The team originally built internal tools for clients, then combined the most-requested features into one SaaS platform. The application is cloud-based and includes: - AI call answering and lead qualification - Customer CRM - Scheduling and calendar management - Estimates and invoicing - SMS and email communication - Website forms and lead capture - Basic reporting and analytics - Mobile-friendly web app The platform is primarily used by: - HVAC companies - Plumbing businesses - Electricians - Roofing contractors - Handyman services - Cleaning companies - Landscapers - General contractors - Other local service businesses with 1–100 employees Most customers subscribe monthly and use JohnnyBox as the central hub for running their business. The founders have decided to focus on a different software product in the healthcare industry that has attracted outside investment. Rather than continue operating JohnnyBox, they're looking for a buyer who can support the existing customer base and continue growing the platform. The software has a stable user base, recurring subscription revenue, and significant room for expansion through additional integrations and marketing.

Highlights

91% Annual Customer Retention with predictable recurring subscription revenue
37% Year-over-Year Growth while remaining founder-led and capital efficient.
High Gross Margins & Low Churn, providing a strong foundation for rapid expansion.

AI Diligence Assistant

Read independently by two AI models · questions to investigate

Disclosure score

Material inconsistencies and missing disclosures. The business shows only 6 months of operating history yet claims multi-year development and annual metrics (retention, YoY growth) that cannot be validated from the packet. Revenue is very small (MRR $800) and profit ($550/month) yet the packet lacks customer counts, concentration, growth trend, third-party dependency, and normalized expense detail. Founders are leaving for another funded project — risk to support, roadmap, and knowledge transfer. An acquirer should demand supporting data for every highlighted claim before considering the $25,000 ask.

Very short operating history (6 months) undermines reliability of 'annual' metrics
One model
ageMonths is 6, indicating the business has been live for ~6 months. Yet the packet presents annualized metrics ("91% Annual Customer Retention", "37% Year-over-Year Growth") without multi-year data. With only 6 months of operations, those annual figures cannot be validated and may be misleading.
Inconsistent timeline: 3 years of development vs 6 months of business age
One model
Notes state the product was "developed over approximately three years", but ageMonths is 6. This suggests either the product was not commercially launched until recently or the age value is wrong. The seller must clarify the distinction between development time and live commercial subscription history and provide launch and revenue timelines.
Founders exiting to a new funded project — support and roadmap risk
One model
Founders "have decided to focus on a different software product" that attracted outside investment. No information is provided about staffing, documentation, ongoing support, developer contracts, SLAs, or transition plan. Buyer risk: platform may be owner-dependent and could degrade quickly without a committed team.
No customer count, ARPU, churn timeline, or customer concentration disclosed
One model
MonthlyRevenue $800 and MonthlyProfit $550 are provided but the packet omits number of customers, average revenue per user (ARPU), distribution of revenue by customer, and any top-customer concentration. Buyer cannot assess concentration risk (e.g., one client representing large share) or unit economics without these figures.
Profit margin appears unusually high given small scale — expenses may be understated
One model
MonthlyRevenue $800 vs MonthlyProfit $550 implies a profit margin of 68.75% and monthly expenses of only $250. For a cloud AI-enabled SaaS (AI phone answering, SMS, hosting, integrations, support), those expense levels are unexpectedly low. Request detailed P&L, SRE/hosting costs, third-party API costs, payroll/contractor expenses, and any owner pay or perks excluded from expense figures.
Asking price relative to ARR and annual profit needs justification
One model
AskingPrice $25,000 vs MonthlyRevenue $800 -> ARR = $9,600. Price/ARR = 2.60x. AnnualProfit = $550 * 12 = $6,600. Price / annual profit ≈ 3.79x. With limited history (6 months) and small absolute cashflow, buyer should question multiple and request growth/retention proofs, customer-level metrics, and a working capex/cost plan before relying on those multiples.
Recurring vs one-time revenue not broken out
One model
Notes state "Most customers subscribe monthly" but no breakdown is given between recurring subscription MRR, onboarding/setup fees, and one-time professional services. With only $800 MRR, a small amount of one-time fees could materially inflate reported revenue—request an MRR waterfall and historical monthly revenue series.
No disclosure on third-party APIs, hosting, or licensing costs
One model
Product features (AI call answering, SMS, email, web forms) strongly imply use of third-party services (AI models, telephony/SMS providers, cloud hosting). The packet does not disclose vendor dependencies, contracts, costs, or risks (rate increases, account suspension, IP restrictions). Buyer should obtain a list of third-party providers, current monthly bills, and any long-term commitments.

All figures are seller-reported. This is a machine-generated reading of the seller’s own materials — it flags questions to investigate and does not verify, audit, or warrant anything. It is not financial advice. Confirm every number yourself before you buy.