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I built VeriVault using @Bubble , an enterprise-grade document portal designed to replace insecure email attachments with a secure, AES-256 encrypted 'handshake' between law firms and their clients. VeriVault integrated with Stripe to handle secure recurring billing and automated seat provisioning ,admins can manage their subscription directly from Settings & Billing dashboard.
š VeriVault targets the "Missing Middle" of legal tech.
š Value Prop: We reduce "document chasing" time by 40% through structured requests.
š Monetization: SaaS model with three tiers (Basic, Pro, Enterprise). We capture high-value leads via a dedicated "Talk to Sales" channel for customized firm-wide deployments.
participated in :January Challenge #BubbleBuildsRevenue challenge.
check out my social media post :https://x.com/DhananjayG21AI/status/2025939768111231485?s=20
Really clean execution š Curious ā what was the biggest challenge building secure document workflows in Bubble? Always interesting to see complex SaaS use-cases done well.
Love that focus. Reliability at the database + privacy-rule layer is where things get genuinely hard. Curious ā was consistency or access control the bigger challenge?
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QuoteFlow: a quote in 60 seconds, not 3 days.
Try it in 2 minutes: submit a quote on the home page (any email) and watch the AI estimate appear. Then open https://quoteflow-13124bc3.base44.app/demo to explore the owner dashboard, automations and lead timelines on sample data, no login needed.
Service businesses (mobile detailers, cleaners, landscapers) lose jobs in the gap between "can I get a quote?" and an actual number. Phone tag, forgotten follow-ups, customers who go cold. I built QuoteFlow on Base44 to close that gap automatically.
How it works:
ā¢ A customer fills one form on the public site. A backend function sends the request to Base44's InvokeLLM together with the owner's real rate card and pricing rules, and gets back an itemized estimate (SUV surcharge, pet hair add-on, travel fee, assumptions) in about 3 seconds. The AI never prices outside the rate card, and if the LLM is unavailable it falls back to the plain rate-card price and flags it.
ā¢ The customer gets a branded email with a private link and books in one click. The owner gets an alert with a private AI note (risks, upsells, questions to ask).
ā¢ A scheduled Workflow runs daily: quotes that have gone quiet for 48h get a friendly follow-up (max 2), then go stale after 7 days so the owner can call the live ones instead.
ā¢ A second Workflow emails the owner a Monday digest: leads, quotes, bookings, revenue, conversion and the most requested services.
ā¢ The owner dashboard is mobile-first: KPI tiles, a pipeline (kanban on desktop, filterable list on phones), and a full timeline per lead showing every email, automation run and status change. Settings control the rate card, pricing rules and follow-up timing.
How I built it: 3 Base44 entities with row-level security (customers never touch the Lead table, only token-scoped backend functions), 5 TypeScript backend functions, 2 scheduled Workflows created through the Base44 API, and a React + Tailwind frontend deployed with the Base44 CLI. I used Claude Code as the coding agent against Base44's official agent skills; Base44 provides hosting, auth, the LLM, email and scheduling. Verified live: real submissions priced by InvokeLLM, emails delivered, workflow runs completing on schedule for four days.
Live: https://quoteflow-13124bc3.base44.app Ā· Owner dashboard sandbox: https://quoteflow-13124bc3.base44.app/demo
ā¢ 16h
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