Inventory sync and management portal for a Riga fashion boutique
Illustrative · Retail · Physical store + WooCommerce
A women's clothing boutique managing stock entirely in Excel — staff updated it manually after each sale, independently, which meant it was constantly wrong. The result: online orders for items that weren't in stock, angry customers, and hours every week reconciling discrepancies. They'd looked at off-the-shelf solutions but none handled their specific combination well, and the monthly SaaS fees added up.
What we'd build
A Full System: a purpose-built SQL Server database, web-based stock management portal, and integration with their existing WooCommerce store.
- SQL Server database: products, variants (size/colour), stock levels, supplier records, sales history, customer records
- Web-based management portal (browser-based, works on tablets at the counter) for stock intake, counts, and adjustments
- WooCommerce sync: stock updates automatically within 60 seconds of an online sale
- Low-stock alerts emailed when any variant drops below a configurable threshold
- Supplier purchase orders: create POs in the portal, receive stock against them, automatic stock uplift on receipt
- Daily sales report emailed automatically each morning: top sellers, margin by category, stock health
C# .NET
SQL Server
WooCommerce API
ASP.NET Core
Dapper
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Patient management system for a 3-location dental clinic
Illustrative · Healthcare · 3 locations, Riga region
Patient records on paper at each clinic. Appointments in a shared Outlook calendar that three receptionists edited simultaneously — double-bookings were a recurring problem. Billing in Excel, invoiced manually, reconciled at month-end. Enterprise dental software would mean a five-figure quote plus a per-seat licence that grows every year — built for 50-location chains, not three.
What we'd build
A web-based patient management system shared across all three locations in real time, with role-based access for reception, dentists, and management.
- Central SQL Server database: patients, appointments, treatments, invoices, and staff across all three locations
- Patient records module: medical history, contact details, treatment notes, photo attachments, GDPR-compliant
- Appointment scheduler: calendar view per dentist per location, conflict detection, SMS/email reminders
- Billing module: treatment-linked invoices, payment recording, outstanding balance tracking, monthly revenue reports
- Role-based access: receptionists see scheduling and billing; dentists see patient records; management sees everything
- Runs in a browser — no software installation, works on existing computers at each clinic
C# .NET
SQL Server
ASP.NET Core
Multi-location
GDPR
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Supplier pricing automation for a Baltic import company
Illustrative · Distribution · Baltic region
A company importing goods from 14 European suppliers was drowning in price lists — each sent differently: Excel, PDF, CSV, embedded in emails. A staff member spent 3+ days every month downloading, reformatting, comparing, and manually entering prices. Mistakes were common. Margin decisions were made on data that was weeks old.
What we'd build
An automated supplier price management platform that ingests price lists in any format, normalises them, and delivers clean margin data to the sales team.
- SQL Server database: suppliers, product catalogue, price history, exchange rates, margin rules
- Price import engine (C#): handles Excel (.xlsx/.xls), CSV, and structured PDFs — each supplier's format configured once, then automated
- Normalisation layer: maps each supplier's column names to a standard product catalogue across different SKUs and packaging sizes
- Price comparison dashboard: current price vs. previous price per supplier — highlights changes above configurable thresholds
- Margin calculator: applies exchange rates, import costs, and margin targets to produce suggested retail prices
- Historical price charts: 24-month trend per product per supplier
C# .NET
SQL Server
Excel/CSV/PDF parsing
Data pipeline
Dapper
Live job board for a Riga auto service center
Illustrative · Workshops & repair shops · Riga region
A repair shop tracked every job on a whiteboard in the back office — invisible from the front desk, invisible to a technician mid-job in another bay. Parts on order for one car were only discovered missing when the customer arrived to collect it. Nobody had a single view of what was actually blocking the floor.
What we'd build
A shared, browser-based job board every workstation can see, with a shop-wide view of exactly what's blocking active work.
- SQL Server database: jobs, customers, vehicles, technicians, parts requirements, job history
- Live kanban board: Intake → Diagnosis → Awaiting Parts → In Progress → Ready for Pickup, updating instantly for everyone looking at it
- Automatic routing: a job only enters "Awaiting Parts" if it actually needs a part that isn't in stock — no manual flagging
- Shop-wide parts view: every part blocking any active job, aggregated in one place, with which jobs are waiting on it
- New-job intake from any workstation — front desk, phone, or the bay itself
- Runs in a browser on the machines the shop already has — no software installation, works on a tablet at the counter
C# .NET
SQL Server
ASP.NET Core
Real-time UI
Blazor
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What a Quick Check finds on a five-year-old order-processing database
Illustrative · Diagnostic preview · Any SQL Server-backed system
Unlike the other scenarios on this page, this isn't software we'd build for a client — it's a preview of the audit itself. The named tiers on our services page (Quick Check / Standard Audit / Deep Dive) are otherwise just labels until you've been through one. This makes them concrete.
How it works
Pick a sample database profile, run the check, and watch six real rules evaluate it — not a scripted animation. Two of the numbers are yours to adjust; findings recompute live so you can see the engine actually respond, not just replay a fixed result.
- Missing/inadequate indexing on the busiest table, scored against its actual row count
- Index fragmentation, using the same 10%/30% reorganize/rebuild bands Microsoft documents
- Backup coverage — automated vs. manual, and how stale a "successful" job has quietly gone
- Slow reports and queries, with the actual runtime that's costing someone time daily
- Schema staleness — years since a real end-to-end review, not just incremental patching
- Concurrency risk from table scans piling up under real simultaneous usage
- A plain-English "how this scoring works" panel showing the exact thresholds used
C# .NET
SQL Server
Diagnostic rules engine
Blazor
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