AI Automation in Practice
The work is real. Client identities are anonymised by agreement — full case studies with system diagrams and data are available on request.
Industries: B2B distribution · Aviation training · Ecommerce operations
B2B distributors live on catalogue accuracy. When product data updates arrive daily across dozens of suppliers in inconsistent formats, manual ops cannot keep up — and errors reach the ERP before anyone catches them.
B2B Textile Distribution
6 weeks AI Automation PipelinesCatalogue Automation for a European Textile Distributor
Measured result
3 days -> 14 min per supplier cycle
Delivered system
Production pipeline with ERP handoff, exception queue, and operator runbook.
Challenge
Supplier catalogue updates — 300+ changes per day, across multiple formats — consumed 4 hours of manual ops per day and still produced data errors in the ERP.
Approach
Built an ingestion pipeline that normalizes supplier feeds (PDF, CSV, API), runs AI translation (FR↔EN), enriches with category tags, and pushes to ERP via a structured QA gate. Edge cases surface for human review; routine updates process automatically.
Outcome
Manual processing reduced to a 5-minute daily exception review. Zero data-entry errors since deployment. Ops team capacity redirected to vendor negotiation and supplier relations.
Running a distribution operation with supplier data volume?
See if this applies to your operation →What the client received
- Supplier feed ingestion across PDF, CSV, and API sources
- FR/EN translation and category enrichment flow
- Human QA gate for edge cases before ERP push
- Daily exception review workflow and handover documentation
Aviation training organizations operate under strict regulatory documentation requirements. Instructors spend the majority of their prep time extracting and reformatting content from regulatory PDFs — time that should go to classroom delivery.
Aviation Training, North America
8 weeks AI Automation Pipelines + Production Agent SystemsCourse Content Pipeline for an Aviation Training School
Measured result
5× faster content production
Delivered system
Document-to-course pipeline with instructor approval gates and module consistency checks.
Challenge
8 instructors each spending 4–6 hours producing course materials from regulatory PDFs and documentation. Inconsistent formatting across 30+ module backlog.
Approach
Built a content extraction and generation pipeline on top of regulatory document libraries. Agents draft structured lesson content and surface approved images; instructors approve via a lightweight review interface. No content goes live without instructor sign-off.
Outcome
Course material production 5× faster. Instructor time redirected to classroom delivery. Content consistency across all modules. Backlog cleared in 3 weeks.
Building course content from regulatory or technical documents?
Talk about a content pipeline →What the client received
- Regulatory document extraction and lesson draft generator
- Instructor approval interface before publication
- Course formatting rules for consistent modules
- Backlog clearing plan and content QA checklist
Multi-store ecommerce operators face a content and coordination problem at scale: keeping product pages, SEO metadata, and inventory accurate across multiple storefronts requires either a large team or a system that runs the routine.
Ecommerce Operations
10 weeks + ongoing AI-Led Operations + Production Agent SystemsAI Operating System for a Multi-Store Ecommerce Operator
Measured result
15 -> 150 content pages per week
Delivered system
Multi-agent operating layer with publishing gates, daily brief, and escalation routing.
Challenge
Running 5 niche ecommerce stores simultaneously required content, QA, and coordination that manual operations couldn't scale to — without proportional headcount costs.
Approach
Built a multi-agent operating layer: content agents per store, QA gate before publication, routing for escalations. Human gates on payment and SEO changes. Monitoring and daily brief generated automatically.
Outcome
5 stores maintained simultaneously without proportional headcount increase. Content published at scale. Payment and publishing operations fully human-gated.
Managing multiple storefronts or content at scale?
See what an operating layer looks like →What the client received
- Content agents for each store and product family
- Human QA gate before SEO, payment, or publishing changes
- Daily operations brief with blockers and decisions
- Monitoring dashboard and escalation rules
Working on something similar?
A 30-minute call is enough to know if AI automation fits your situation.