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LogiGreen

LogiGreen AI Apps

AI tools for the people on the floor.

Voice, vision and language models put to work on the jobs that still run on printed sheets. Built for operators in warehouses, factories and trucks.

A suite of lightweight, mobile-first tools that digitalize everyday operations in warehouses, factories and trucks. Built by continuous improvement engineers to fill the gaps where enterprise software falls short. They run in any smartphone browser, with no installation.

Digitalize manual processes

Cycle counts, order preparation and repacking still run on printed spreadsheets in most operations. These tools replace the paper.

Automate operator reporting

Damage reports and proof of delivery are administrative load on people with productivity targets. The app produces the document.

Multimodal, not another screen

Voice recognition, image analysis and natural language in one app, so operators keep their hands on the goods.

Open the demo→

4 tools, free demo mode, nothing to install

The tools

Each one replaces a specific piece of paper

Inventory Cycle Count

Voice-guided counting that fills the spreadsheet for you

Teams print count sheets, walk the aisles comparing system quantity against what is on the shelf, then key the results back in. The printing and the re-keying are both waste, and both introduce errors.

  • The app routes the operator to the next location to check
  • They speak the result out loud, for example "Location K5, 12 units"
  • Voice recognition records it and the sheet fills automatically
  • The grid updates live: green for counted, red for still open
  • A completion summary lists every discrepancy against system stock
Try it→
Cycle count tool: warehouse grid, completion summary and discrepancy list
Warehouse Picking

Hands-free picking on a standard smartphone

Traditional voice picking needs proprietary headsets at $2,000 to $5,000 per operator and six-figure licensing, which puts it out of reach for mid-market sites.

  • The app speaks each instruction aloud through ElevenLabs text to speech
  • The operator walks, picks, then confirms by voice without touching a screen
  • Issues can be reported by voice on any line
  • A live grid shows the current pick, pending tasks and stock
  • Manual mode stays available for noisy environments
Try it→
Warehouse picking app: pick instruction, warehouse grid and pick list
AI Damage Inspector

A structured damage report in under 30 seconds

When damaged goods arrive, receiving stops. Damages must be documented in detail with photographs, and for operators measured on boxes per hour that paperwork is unmanageable.

  • The operator photographs the damaged pallet
  • They scan the barcode and tap Generate Report
  • The model assesses packaging, pallet and product condition
  • It returns a severity rating and recommended actions
  • The quality team receives a standardized report, not a free-text note
Try it→
Damage report generator: photo upload, confirmation and the generated report
Workforce Planning Optimizer

Weekly staffing that respects the labor constraints

Shift plans are built in spreadsheets, so rest days and consecutive-work limits get checked by hand and the true FTE requirement is guesswork.

  • Enter daily demand, work days, rest days and consecutive work limits
  • The optimizer returns the total FTE required
  • It proposes shift patterns that satisfy every constraint
  • A demand against supply chart shows where the plan is tight
Try it→
Proof of DeliveryComing soon

Delivery evidence captured at the door

Paper PODs get lost, arrive late, and rarely carry enough evidence to settle a dispute.

  • Photographs captured at the point of delivery
  • GPS coordinates and timestamp attached automatically
  • The document is generated without back-office work

Why voice picking is suddenly affordable

Voice picking has been proven for decades, but the economics locked it to large sites. Running speech through general-purpose AI models on hardware operators already carry changes the arithmetic.

Read the case study→
TraditionalLogiGreen AI Apps
Hardware per operator$2,000 to $5,000 proprietary headset$0, existing smartphone and any headset
Software licensing$10,000 to $50,000 per yearAround $50 per month in API usage
Deployment time3 to 6 monthsDays to weeks
Languages supportedLimited, retraining per language29+, no retraining
Voice qualityRobotic, template basedNatural, contextual
Best suited forLarge warehouses, 500+ picks a dayMid-market, multi-site, diverse workforce
Operator to web app to backend, with text to speech and speech recognition services

Runs on what your teams already carry

A browser app on any smartphone talks to a small backend that handles the picking logic, the inventory database and the speech services. There is no dedicated hardware to buy, no client to install and no rollout project.

Voice picking flow: instruction, walk to location, pick, confirm by voice, next pick

Try them on your own process

Every tool runs in demo mode with sample data, so you can walk the full workflow before talking to anyone.

Open the demo→Talk to us about your site