
WANILE TECHNOLOGIESAn operations platform rebuild —
a unified, intelligent system for production, distribution and accounting.
Organised in four movements — the why, the what, the how, and the who. Every decision flows from a single intent: build a platform District Bagel can grow into for the next decade.
District Bagel has built something rare: a working operational backbone that has scaled the business across multiple locations and customer types. The current Laravel-based system functions, but it has aged out of the speed, intelligence, and flexibility your operation now demands.
This proposal outlines a complete rebuild of that platform, designed not as a copy of what exists today, but as a foundation for what District Bagel will become over the next five to ten years. A system architected to add new employees, new cities, new countries, and new business functions without rewriting the core.
The new platform will unify seven distinct user roles, a native mobile application for drivers, an AI-powered ordering intelligence engine, and clean integrations with your existing Recipe Cost Calculator and QuickBooks Desktop workflow. Every decision in this document has been made with one goal: build it strong, build it once, and let it grow with you.
We will deliver a production-grade system that replaces your current Laravel platform end-to-end, eliminates the manual workflows slowing down your team today, and gives you the AI intelligence to make smarter ordering decisions every single day. Built by a senior team, deployed in phases, owned entirely by you.
Before scoping any technical solution, we want to reflect back what we heard during our discussion to make sure we're building toward the right outcome.
Your current system works, but it's slow, dated, and lacks the intelligence layer that modern operations require. Logging in takes too long. Reports take too long to load. The QuickBooks bridge is manual, requiring your secretary to enter invoice numbers by hand. There is no system suggesting what to order based on weather, holidays, or store-specific patterns. You are essentially driving a 2010 vehicle when a 2026 vehicle exists.
This isn't just a rebuild. It's the foundation for a multi-location, multi-country District Bagel operation where every employee, in every city, has a tailored interface for their role. Drivers in one country, kitchen managers in another, accounting staff working across time zones. The platform we build now must be the platform that supports that future without architectural rewrites.
You explained it perfectly during our call: when a snowstorm is coming, certain items sell less. When a Jewish holiday approaches, kosher locations need different production volumes. When the weather forecast shows two excellent days ahead, certain stores need more inventory. Today, this knowledge lives in the heads of your experienced drivers and kitchen managers. The new system will capture that intelligence, learn from your historical data, and make it available to every team member at every location, every day.
During our call you mentioned a 1.56% return ratio for the month, with individual stores hitting 0.47%. These are exceptional numbers in the food distribution industry. The new system is designed to protect those numbers, surface the outliers (like the location showing 4.15%), and help you investigate why specific items underperform at specific locations. Your operational excellence becomes measurable, repeatable, and improvable.
The new District Bagel platform is composed of seven interconnected modules, a native mobile application, an AI intelligence layer, and integration bridges to your existing third-party tools. Each module is purpose-built for a specific role in your operation, while sharing a unified database, authentication system, and business logic core.
Before a single line of code is written, we commit to these six principles. They are the filters every design, schema and feature decision must pass through during the entire build.
Every module is designed assuming you will eventually add more employees, more locations, more countries. The database schema, permission system, and API layer are all multi-tenant ready.
Every AI recommendation comes with an explanation and an override. Your team always has the final say. The system learns from those overrides to get smarter over time.
Drivers get a native mobile app with offline capability, push notifications, and camera access. Other roles get responsive web interfaces optimized for their primary device.
Wherever your current system requires manual entry (like QuickBooks invoice numbers), the new system will automate or eliminate that step entirely.
Login should take under one second. Reports should load instantly. No more waiting for the database to think. Performance is non-negotiable.
Code, documentation, architecture notes and deployment pipelines — you own all of it. No lock-in to us, to obscure tools, or to bespoke frameworks.
Each module below corresponds to a distinct user role in your operation. Modules share data and workflows where needed, but each interface is purpose-built for the person using it. No more forcing managers to wade through admin screens or drivers to navigate desktop interfaces.
All seven modules share a single authentication layer, a single product catalog, a single audit trail, and a single permission matrix. Change a price once — and every tier, portal and module reflects it within the same heartbeat.
The driver app is the most operationally critical piece of this system. It runs on phones and tablets in the field, often in spotty network conditions, and supports two completely distinct workflows: afternoon route planning and morning delivery. Because of these requirements, this is built as a true native mobile application rather than a responsive web view.
Drivers get notified when orders are ready, when customers request changes, or when their route is updated.
Built-in signature pad and camera access for delivery proof. No browser permission prompts, no friction.
Drivers can plan orders and capture deliveries even when network drops. Data syncs when connection returns.
School deliveries with the 'left at side' option automatically tag GPS coordinates as proof of delivery.
Native apps load instantly and respond instantly. No browser overhead during a busy delivery shift.
One codebase, both form factors — the same driver can switch from phone to tablet without learning a new layout.
The driver walks each store on their route, checks shelf inventory, and submits a pre-order plan for the next morning's production.
The driver loads the truck with what the kitchen packed, delivers to each location, and closes the loop on every order.
Schools have their own delivery flow with kid counts, standard extras, and unique edge cases.
Drivers have access to their own performance data: shipping totals, return ratios, and product-level statistics by location, product, date range, and driver. Exportable to PDF for personal tracking or sharing with management.
This is the intelligence layer that transforms District Bagel from a reactive operation into a predictive one. The AI engine continuously learns from your historical data, weather patterns, and calendar events to make ordering recommendations that get smarter every week.
We are not adding AI for the sake of saying we have AI. Every recommendation the system makes will be tied to real data, with a visible explanation, and an easy override. Your drivers and managers always have the final say. The system learns from those overrides, getting more accurate over time.
| Historical sales data | 4-week rolling window per product per location, with extended trend analysis going back further as data accumulates. |
| Weather forecasts | Real-time weather API integration. Rain, snow, heat waves, and ideal weather all affect bagel sales differently. The system learns these patterns per location. |
| Jewish Calendar | Holiday master tied to the Jewish Calendar API. Production volumes shift before and after major holidays in ways that experienced drivers know intuitively. The system captures that knowledge. |
| Civic events | Local school holidays, public holidays, and major community events that affect demand patterns. |
| Driver overrides | Every time a driver overrides an AI recommendation, the system logs it and learns. This feedback loop is what makes the AI useful in your specific business. |
| Return ratios | If returns spike for an item at a specific location, the AI factors that into future recommendations to reduce waste. |
Pre-filled order based on the manager's 4-week history plus relevant signals. They confirm in seconds.
After capturing on-shelf counts, the AI suggests how much to deliver tomorrow. Driver reviews and submits.
When a location's return ratio jumps unusually high (like the 4.15% you mentioned during our call), the system flags it for investigation.
Aggregated view of expected demand for the next 24-48 hours, helping plan ingredient prep and staffing.
As you mentioned during our call, you understand the AI needs time to learn. Here is the realistic maturity curve we expect.
Rule-based recommendations using your historical data + holiday/weather signals.
System has learned from real driver overrides and seasonal patterns.
Full pattern recognition across locations, products, weather, and calendar.
AI surfaces insights you didn't know to ask for: emerging trends, optimal pricing windows, expansion opportunities.
Your existing Recipe Cost Calculator platform holds all your recipes, ingredient costs, and cost breakdowns. Rebuilding this from scratch would cost tens of thousands of dollars and provide no immediate value. Instead, we will build a clean API integration layer that pulls relevant cost data into the District Bagel platform on demand.
Today, your secretary manually enters QB invoice numbers into the system after creating invoices in QuickBooks Desktop. This is exactly the kind of manual work the new platform should eliminate.
Our QB Desktop bridge automates this in two phases:
Both the kitchen auto-print and driver receipt printing require professional cloud print integration. We will use a service like PrintNode or similar, which connects any USB or network printer to the cloud and allows the platform to send print jobs from anywhere with no manual intervention.
The AI engine consumes data from established, reliable APIs:
The technology choices below have been made for one reason: long-term maintainability and scalability. Every layer of the stack is industry-standard, well-documented, and supported by large developer communities. This protects you from being locked into obscure tools or unable to find developers in the future.
| Layer | Technology | Why this choice |
|---|---|---|
| Web Frontend | React 18 · Next.js 14 · TypeScript | Industry standard, fast, SEO-friendly, massive talent pool. |
| Mobile App | React Native (iOS + Android) | Single codebase for both platforms, native performance, easy maintenance. |
| Backend API | Node.js · Express · TypeScript | JavaScript across the entire stack, fast iteration, well-supported. |
| Database | PostgreSQL with Prisma ORM | Reliable, scalable, enterprise-grade. Multi-tenant ready for future growth. |
| AI Layer | OpenAI API (GPT-4o / latest) + rule engine | Hybrid approach: deterministic rules for predictable logic, LLM for nuanced reasoning. |
| Authentication | JWT + role-based access control | Secure, stateless, supports the 7-role permission system natively. |
| File Storage | AWS S3 or DigitalOcean Spaces | Cost-effective, reliable, automatic backups. |
| PDF Generation | Puppeteer + custom templates | Pixel-perfect PDFs for school planners, receipts, and reports. |
| Hosting | AWS or DigitalOcean (your choice) | Auto-scaling, automated backups, 99.9% uptime SLA. |
| Monitoring | Sentry + Datadog or similar | Real-time error tracking and performance monitoring. |
This project is structured into five clear phases over six months. Each phase produces a working, deployable deliverable. You will see real progress every two to three weeks, not just at the end. Phased delivery also means you can begin using parts of the system before the entire build is complete, easing the transition off your current Laravel platform.
| Phase | Duration | Deliverables |
|---|---|---|
| 01 · Discovery & Design | Weeks 1 – 3 | Final requirements doc, complete UI/UX designs for all 7 modules + mobile app, database schema, API specification, project plan. |
| 02 · Core Foundation | Weeks 4 – 9 | Auth + role system, admin module, product catalog with multi-tier pricing, location manager module, basic order workflow. |
| 03 · Kitchen & Wholesale | Weeks 10 – 14 | Kitchen production module, kitchen manager module, wholesale store portal, approval workflows, reporting foundation. |
| 04 · Driver Mobile App + AI | Weeks 15 – 21 | Native iOS + Android driver app, AI ordering engine v1, weather + calendar integrations, school module, signature + print. |
| 05 · Accounting + Polish + Launch | Weeks 22 – 26 | Accounting module, QuickBooks bridge, all reports, data migration from current system, UAT, training, production launch. |
The investment for this complete rebuild reflects the scope, the seniority of the team assigned, and the long-term value the platform will deliver. We've structured it to balance your need for predictability with our need to deliver quality without rushing.
Comparable platforms quoted by US or European agencies typically range from $60,000 – $120,000 for the same scope. Our rate reflects the cost advantage of operating from Pakistan combined with the seniority and quality of our team. You get senior-level work at a fraction of Western agency rates.
Payments are tied to deliverables, not calendar dates. You only pay as the project progresses and you see real value delivered.
| Milestone | % | Amount (USD) |
|---|---|---|
| Project kickoff Signed agreement | 20% | $5,000 |
| Phase 1 complete Designs + architecture approved | 15% | $3,750 |
| Phase 2 complete Admin + manager modules live | 20% | $5,000 |
| Phase 3 complete Kitchen + wholesale modules live | 15% | $3,750 |
| Phase 4 complete Driver app + AI engine live | 20% | $5,000 |
| Phase 5 complete Accounting + final launch | 10% | $2,500 |
If you want the platform live sooner, we can compress the delivery timeline by allocating a larger team and running parallel development tracks. Same scope, same quality, faster delivery.
Given that you mentioned during our call that you're not in a rush and have a working system today, we recommend the Standard Pace option. It saves you $4,000 and gives the team room to build the AI engine carefully rather than rushing the most strategic part of the platform.
We know you're comparing bids. You will see quotes in the $8,000 – $15,000 range from freelancers and small shops. We want to be direct about what a lower price usually means on a project of this shape: a seven-module platform with native mobile, AI, data migration off Laravel, and a live QuickBooks bridge is not a small project dressed up — it is a real production system. Cheap builds typically skip the design phase, staff junior developers, cut QA, write no documentation, leave integrations half-wired, and disappear at launch. The rebuild cost is paid by you, six months later, in lost orders, unexplained waste, and a kitchen team that stops trusting the system. In food operations, an "almost working" platform is more expensive than the platform itself.
Our $25,000 reflects a senior team, a real design phase, a tested QuickBooks bridge, a migrated dataset, five months of post-launch support, full documentation, and source-code ownership. It is priced to be accessible — not to be the cheapest option on your desk.
Your platform handles customer records, school kid counts, pricing tiers, and financial data flowing to QuickBooks. Every layer is built with that responsibility in mind: TLS 1.3 in transit, AES-256 encryption at rest, role-based access control enforced at the API, audit trails on every mutation, automated daily backups with point-in-time recovery, and the option to host in a Canadian data region for local data residency. Access to production is limited to named engineers on your approved list, with revocable keys and logged sessions.
Wanile Technologies is a software development agency operating from the United Kingdom and Pakistan, with a team of 28 engineers, designers, and product specialists. We build production-grade software for clients across the US, UK, Europe, Canada, and the Middle East.
Our specialization is full-stack web development, AI/ML integration, mobile applications, and SaaS platforms. We work across verticals including fintech, legaltech, healthtech, edtech, and eCommerce.
Built an AI-powered board intelligence platform used by Porsche board members to analyze meeting materials and competitive landscape. Delivered to enterprise standards with strict security and confidentiality requirements.
Compliance automation platform for the New York operations of ICBC, one of the world's largest banking institutions. Multi-tenant architecture, role-based permissions, document AI extraction, and audit trail.
Full-featured legal-tech SaaS platform with document automation, AI legal research, and client management. Built and continues to be maintained by our team.
Multiple SaaS platforms across food distribution, property management, and logistics — including marketplaces with multi-role dashboards similar to your District Bagel scope. Full case studies available on request.
You mentioned during our call that you're comparing several developers and that direction matters as much as price. Here's our honest case for why we should be the team that builds this.
During our call, we didn't just take notes on features. We understood why the 1.56% return ratio matters to you, why the AI needs to factor weather and Jewish holidays specifically, and why your wholesale stores can't see the kitchen feed. The technical decisions in this proposal flow from understanding your operation, not just your feature list.
The work we've done for Porsche board members and ICBC New York held to enterprise standards: security audits, role-based permissions, audit trails, and reliable performance under load. We bring that same engineering discipline to every project, regardless of size.
Most overseas developers will quote you a low price and then disappear into vague status updates for six months. We built our agency around the opposite: weekly demos, daily updates, direct messaging access, and proactive communication. You'll always know where the project stands.
You said it yourself: this is the foundation for adding more employees, more cities, more countries, and more business functions. Every architectural choice in this proposal has been made with that future in mind. Multi-tenant database design, modular service architecture, scalable infrastructure. When you're ready to expand, the platform is ready too.
After launch, we don't disappear. The 5 months of free maintenance is just the beginning. Most of our clients become long-term technology partners, with us continuing to ship new features, integrations, and improvements year after year. We'd love District Bagel to be that kind of relationship.
If this proposal aligns with what you're looking to build, here's how we move forward.
Take your time reviewing this document. Compare it to other proposals you receive. Note any questions or concerns. We're available anytime to jump on a call to walk through anything that needs more detail.
A 30-minute call to confirm scope, finalize the timeline, and answer any remaining questions. We can also discuss any specific customizations or scope adjustments you want.
We'll send a formal services agreement covering scope, deliverables, timeline, payment terms, and IP ownership. Once signed and the kickoff payment is processed, we begin Phase 1 within 48 hours.
Within 21 days of kickoff, you'll have complete UI/UX designs for every interface, finalized database architecture, full API specification, and a detailed week-by-week project plan. From there, we build.
Pick a 30-minute slot — we'll walk through any open questions and talk kickoff.
Looking forward to the next conversation — and to handing District Bagel the platform it deserves.