AI Solutions (Logistics)

Warehouse Intelligence AI—Smarter Slotting, Pick Paths, and Labor Inside the DC

Teenva AI & Digital Ventures builds warehouse intelligence AI for ecommerce fulfillment centers, 3PL DCs, and FMCG distributors from Bangalore, India. Teenva optimizes SKU slotting, pick paths, wave release, and labor shifts inside your facility—using pick history, demand forecasts, and WMS constraints—integrated with your custom WMS or via API integration services.

Static slotting goes stale after assortment changes; pickers walk miles on bad paths. Teenva reduces travel time per order, dock congestion, and mis-picks—then hands off outbound timing to route optimization and customer questions to logistics tracking chatbot.

Warehouse intelligence AI for DC operations by Teenva AI

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Warehouse intelligence AI—slotting, pick paths, waves, and labor planning on your WMS.

Hub: AI solutions · Domain: Logistics

sales@teenvaai.com · +91 9572020107

Inside-the-DC problems we improve

ProblemAI / optimization output
SlottingWhich SKU belongs in golden zone vs bulk reserve
Pick pathShortest walk sequence per batch/wave
Putaway (scoped)Suggested bin after inbound receipt
Wave planningWhich orders release when to balance lanes
Labor forecastPickers/packers needed by shift from outbound forecast
Congestion (scoped)Stagger fast-mover replen to aisle peaks
Inventory health (scoped)Slow mover relocation, dead stock flags
Cross-dock (scoped)Direct staging vs putaway decision

Outputs feed WMS tasks—location moves, pick lists, labor plans—not generic chat advice.

How intelligence is generated

ComponentRole
Velocity scoringPick frequency, cube, weight from WMS history
Affinity (scoped)SKUs often picked together → adjacent slots
Forecast linkDemand forecasting lifts pre-positioning
Layout graphAisle distances, one-way rules, equipment type
SolverSlotting MIP/heuristics; TSP-style pick sequencing
Simulation (scoped)Compare km/order before/after slot change
FeedbackActual pick times refine travel estimates
Warehouse intelligence slotting map pick heatmap dashboard UI mockup

Features we implement

  • Slotting recommendations API

    Move list with ROI estimate (km saved)
  • Pick path optimizer

    Batch/cart pick sequence for released waves
  • Wave engine hooks (scoped)

    Priority rules + capacity caps
  • Labor planning dashboard

    Headcount by shift from forecast + productivity
  • Heatmaps

    Pick density, congestion aisles, SLA risk orders
  • What-if

    New SKU introduction slot; aisle closure impact
  • WMS integration

    Task export: relocation, pick route, pack station queue
  • KPI tracking

    Lines/hour, km/pick, cut-off miss rate vs baseline
  • Vision assist (scoped)

    Cycle count anomaly from camera/RPA feed
Pick path optimization aisle map

Architecture

  1. WMS events (picks, putaway, inventory, orders)

  2. Data lake / feature store (SKU velocity, layout graph)

  3. Forecast ingest (optional) + business rules

  4. Slotting + pick-path + labor optimizers

  5. Recommendations API → WMS task queue / supervisor UI

  6. Execution feedback → retrain travel times & velocity

Warehouse intelligence AI architecture diagram WMS optimization
  • Not LLM-operated forklifts — Deterministic optimization + ML features
  • Deployment — Batch nightly slotting; real-time pick sequence at wave release

Use cases by facility type

FacilityFocus
Ecommerce multi-SKU DCGolden zone slotting, batch pick paths
Quick commerce dark store (scoped)Micro-slotting, high-frequency replen
3PL multi-client (scoped)Client-specific zones, shared labor model
FMCG bulk + pick (scoped)Pallet reserve vs forward pick face
Cold chain (scoped)Minimize door-open time via pick sequence
Returns processing (scoped)Restock putaway rules
Warehouse intelligence use cases ecommerce 3PL FMCG fulfillment center

Integrations

SystemRole
Custom WMSInventory locations via custom software development
Demand forecastingVolume by SKU from demand forecasting AI
Route optimizationDispatch cut-off via route optimization AI (scoped)
API integration servicesERP/OMS via API integration services
Mobile pick appPick sequence on mobile pick app (scoped)
Supply chain analyticsDC KPI rollup via supply chain analytics AI (scoped)

WMS defaults don't know your pick heatmap.

We model your aisles, velocities, and cut-offs—and quantify km and labor saved before you move a pallet.

Warehouse intelligence vs other logistics AI

ProductFocus
Warehouse intelligence AIInside DC: slotting, picks, labor
Demand forecasting AIHow much volume coming
Route optimization AIOutside DC: vehicle routes
Logistics tracking chatbotCustomer shipment status FAQ
Supply chain analytics AINetwork-wide KPIs and scenarios

Why Teenva AI

  • WMS + optimization team

    Not analytics slides only—we ship task integrations
  • Ecommerce DC reality

    High SKU count, promo spikes, cut-off pressure
  • Measurable ROI

    km/pick and lines/hour before/after
  • Phased rollout

    Pilot one zone before full relayout
  • Ops

    Managed IT support when WMS exports change
Why Teenva AI for warehouse intelligence

Managed IT support when WMS exports change. Outbound timing via route optimization.

Delivery process

Warehouse intelligence AI implementation process
  1. Discovery

    DC layout, WMS, pick modes (single/batch/wave), KPIs

  2. Data extract

    Pick history, locations, order lines (anonymized)

  3. Baseline

    Current km/order, lines/hour, cut-off miss %

  4. Layout digital twin

    Aisle graph and constraints

  5. Slotting v1

    Top velocity SKUs; move list for supervisor approval

  1. Pick path pilot

    One wave type; compare walk time

  2. Labor model (scoped)

    Shift plan from forecast + productivity

  3. WMS task automation

    Export relocations and pick sequences

  4. Monitor & refresh

    Monthly slotting refresh; seasonal pre-slot

Frequently asked questions

No—we integrate; intelligence layer sends recommendations and tasks to existing WMS.

Monthly or after major assortment change; fast movers reviewed weekly (configurable).

No—pick paths use optimization solvers on your layout graph.

Works with manual and mechanized DCs; robotics integration scoped separately.

Zone-level slotting per client contract (scoped) with shared labor view.

Yes—forecast drives pre-slot and labor shifts.

km per pick, lines per labor hour, same-day ship rate, cut-off misses.

Pick sequence minimizes door time (scoped) with temperature zone rules.

Lightweight slotting + pick sort still valuable; scope reduced.

10–12 weeks MVP (slotting recommendations + pick path for one pick mode) with WMS data export.

Build your warehouse intelligence layer

Build your AI solution with us—slotting, pick paths, waves, and labor planning on your WMS.

Build your AI solution with us

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