Proof systems

Systems we built, own, and run.

Not demos. Not mockups. Live products used by real merchants and teams — built with the same operational methodology, data-first architecture, and AI integration discipline we apply for clients.

Each system starts from a real operational problem, not a feature list. The work shown here is maintained, iterated, and used to validate the approaches we recommend.

LiveEcommerce OperationsShopify AppCommerce IntelligenceMerchandising Automation

ShelfUp.app

Collection intelligence and merchandising automation for Shopify merchants. Stock depth signals, sales velocity scoring, and automated collection rules built around how ecommerce operations actually run.

  • Shopify Admin API integration with collection and product sync
  • Stock depth and velocity scoring that drives automated merchandising decisions
  • Collection rule logic managing product display, sorting, and availability

Built on the same ecommerce operations methodology Algorithems applies for clients: data first, rules explicit, automation incremental.

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The systems above came from the same process we run for every client engagement: workflow mapping, data architecture, AI integration, and incremental automation that builds operational compound value.

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Anonymized client systems

Relevant proof even when the system cannot be shown publicly.

Some client systems cannot be linked live for confidentiality reasons. We still show the operational shape of the work: challenge, architecture, automation logic, and result.

Client Operations Infrastructure

Document-Heavy Client Operations Layer

Challenge

A service business needed one place for client status, document checkpoints, approvals, and leadership visibility instead of relying on spreadsheets, shared folders, and inbox follow-ups.

System architecture

Designed a custom operating layer joining CRM records, client work queues, document state, approval rules, and role-based dashboards.

Automation logic

Structured intake, document checkpoints, reminder rules, status movement, and management reporting into one controlled flow.

Result

Manual coordination dropped, document handling became traceable, and leadership gained a live view of workload and bottlenecks.

Reporting Infrastructure

Regional Reporting Control Layer

Challenge

A multi-team operation depended on spreadsheet consolidation before weekly decisions, creating late reports and conflicting numbers across departments.

System architecture

Built a reporting core that normalized exports, regional sheets, and approval states into one monitored layer with trusted KPI definitions.

Automation logic

Validation rules flagged missing data, summaries explained variance, and reporting queues routed exceptions to the right owner.

Result

Reporting effort fell sharply and managers moved from number chasing to action review.