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SELECTED WORK / REPRESENTATIVE

From messy brief to operating system.

These case studies are deliberately presented as representative, anonymized engagement models. The delivery patterns, architecture, timelines and metrics are realistic planning examples, not claims that BARSPAN achieved the figures shown for a named client.

01 / ENGAGEMENT MAP

Four markets.
Four different problems.

The point of a case study is to show how the work is actually delivered: discovery, architecture, build, integration, security, launch and measured operations.

USA · Atlas / LogisticsUSA · Meridian / AICanada · Northstar / CommerceNetherlands · Helix / Cloud
Operations platform architecture visual
USA · REPRESENTATIVEPROJECT ATLAS / OPERATIONS

Operations platform for a North American logistics operator.

A mid-market logistics business was running dispatch, exception handling, customer updates and reporting across spreadsheets, email and several disconnected systems.

Product engineeringCloud & DevOpsData & integrations

01 / Situation

Operations teams had no single view of an order exception. A dispatcher could spend 8 to 12 minutes reconstructing status from multiple systems, while customer-service staff manually copied updates into tickets.

02 / Architecture & delivery

BARSPAN would start with a two-week process and integration audit, then establish a canonical order model, API gateway, role-based operations console, event queue and audit trail. The build would run in three increments: exception workflow, operational reporting, then customer-facing status APIs. Production would use staged releases, automated tests, observability and rollback paths.

delivery window16 weeks
core integrations5
transaction volume model12k/day
availability target99.95%

03 / Delivery sequence

DiscoveryDomain modelCore workflowsIntegrationsProduction hardening

04 / System shape

Web operations console → API layer → event queue → TMS/WMS/CRM connectors → PostgreSQL reporting store → cloud observability → role and audit controls.

05 / Outcome model

Illustrative planning model: 20 to 30% fewer manual exception touches, 25 to 35% faster exception resolution and materially better traceability. Delivery model: 1 engagement lead, 1 solution architect, 2 to 3 product engineers, 1 QA engineer and shared DevOps support across the 16-week program. These ranges are deliberately conservative compared with published logistics modernization examples, where public AWS customer stories report larger cost and performance changes.

AI knowledge architecture visual
USA · REPRESENTATIVEPROJECT MERIDIAN / AI

Governed knowledge assistant for a regulated professional-services group.

A distributed services organization had policies, proposals, SOPs and project documents spread across SharePoint, PDFs and internal folders, making retrieval slow and inconsistent.

AI & RAGAutomationSecurity architecture

01 / Situation

Employees were spending significant time finding the latest approved document and asking subject-matter experts questions that had already been answered elsewhere. The organization also needed access controls and citations rather than an open-ended chatbot.

02 / Architecture & delivery

BARSPAN would build a permission-aware retrieval layer with document ingestion, metadata extraction, chunking, embeddings, hybrid search, citation enforcement, prompt policies, feedback capture and an evaluation set. The system would refuse unsupported answers and log retrieval and answer quality signals for continuous improvement.

pilot delivery14 weeks
documents indexed38k
potential users1,200
grounded-answer target93%+

03 / Delivery sequence

Source auditKnowledge modelRAG pilotSecurity reviewUser rollout

04 / System shape

Identity provider → document connectors → ingestion pipeline → vector + keyword index → policy engine → LLM gateway → cited assistant → evaluation and audit store.

05 / Outcome model

Illustrative planning model: 25 to 35% less time spent locating internal information, 30% fewer repetitive internal requests and a 93%+ grounded-answer target on the approved evaluation set. Delivery model: 1 AI architect, 1 product lead, 2 engineers, 1 data/ML engineer and shared security review across the 14-week pilot. These are target metrics for a comparable engagement, not a BARSPAN client result.

Commerce experience architecture visual
CANADA · REPRESENTATIVEPROJECT NORTHSTAR / COMMERCE

Commerce replatform and experience redesign for a Canadian consumer brand.

A growing retailer needed a faster storefront, cleaner product discovery and a platform that could support merchandising without waiting on engineering for every change.

Digital experienceCommerceAPIs & analytics

01 / Situation

The existing storefront had slow category pages, duplicated content, inconsistent mobile journeys and a fragile integration layer connecting ERP, inventory, payments and marketing tools.

02 / Architecture & delivery

BARSPAN would establish a component-based experience system, migrate catalog and content with reconciliation checks, introduce structured product data, rebuild search and filtering, connect inventory and order services through APIs, then run a staged cutover with analytics baselines and rollback.

migration window18 weeks
SKU model18k
key integrations6
conversion target+8 to 15%

03 / Delivery sequence

UX auditDesign systemCatalog migrationIntegration buildA/B launch

04 / System shape

CDN → experience layer → commerce platform → search → ERP/inventory → payment gateway → CRM/marketing → analytics and experimentation.

05 / Outcome model

Illustrative planning model: 20 to 35% faster key page interactions, 5 to 15% conversion-rate improvement and 8 to 12% higher average order value where merchandising and checkout changes support the result. Delivery model: 1 product lead, 1 UX lead, 2 engineers, 1 commerce/integration engineer, 1 QA and shared DevOps support across the 18-week migration. Public Shopify case studies show that double-digit conversion and order improvements are plausible in successful replatforming programs, but those published results belong to other companies and are not BARSPAN claims.

Cloud and security architecture visual
NETHERLANDS · REPRESENTATIVEPROJECT HELIX / CLOUD & SECURITY

Cloud modernization and security foundation for a Dutch industrial technology company.

A multi-site engineering organization had aging workloads, inconsistent monitoring and separate security practices across business units.

Cloud modernizationDevOpsCybersecurity

01 / Situation

The environment had mixed virtual machines, legacy applications, manual deployments and limited centralized visibility. The priority was not a blind migration: critical workloads needed dependency mapping, resilience planning and security controls first.

02 / Architecture & delivery

BARSPAN would inventory workloads, classify migration paths, build landing-zone controls, standardize identity and logging, containerize suitable services, automate infrastructure and migrate in waves with performance and rollback gates. FinOps dashboards would track unit cost before and after each wave.

migration program20 weeks
workloads assessed68
cloud regions modeled3
cost target30%

03 / Delivery sequence

AssessmentLanding zonePilot workloadsWave migrationOperate & optimize

04 / System shape

Cloud landing zone → identity → network segmentation → compute/container layer → CI/CD → observability → SIEM/security controls → cost governance.

05 / Outcome model

Illustrative planning model: 20 to 30% infrastructure-cost improvement, 30 to 50% faster deployment workflows and a 99.95% availability target for production services. Delivery model: 1 cloud architect, 2 cloud/platform engineers, 1 security engineer, 1 QA/automation engineer and shared program management across the 20-week migration. Public AWS migration case studies show that materially larger savings can occur in some environments, but those figures are not BARSPAN results.

How to read these numbers: all metrics on this page are illustrative planning benchmarks calibrated against public technology case-study ranges. They are included to show the depth and measurement discipline of a BARSPAN engagement. They must not be presented as historical BARSPAN client results until the underlying engagement, permission and measurement evidence has been verified.
02 / DELIVERY STANDARD

No hand-off theatre.
One engineering thread.

Discovery, architecture, engineering, QA, security, deployment and optimization stay connected. That is how a project becomes an operating system instead of another isolated application.