Teenva AI & Digital Ventures builds route optimization AI for 3PLs, ecommerce couriers, FMCG distributors, and field service teams from Bangalore, India. Given stops, vehicles, and constraints, Teenva computes efficient routes—minimizing distance, fuel, and missed time windows—and pushes turn-by-turn plans to driver mobile apps integrated with your TMS / dispatch software.
Multi-stop VRP with capacity and time windows—dispatcher dashboard and driver app. Manual route planning breaks when order volume spikes or traffic shifts.
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Route optimization AI—VRP, last-mile, and dynamic re-routing for your fleet and constraints.
Problems we optimize
| Problem type | Typical constraints |
|---|---|
| Last-mile delivery | Stop sequence, SLA windows, proof of delivery |
| Multi-depot VRP | Which hub serves which pin code |
| Capacity routing | Weight/volume per van, bike, or truck |
| Time windows | Customer deliver between 2–5 PM |
| Driver shifts | Max hours, break rules, territory familiarity (scoped) |
| Pickup + delivery | Milk-run collections and drops same route |
| Field service (scoped) | Technician skills, appointment slots |
| Dynamic inserts | New order while driver en route—minimal disruption |
Output: ordered stop list, ETA per stop, polyline map, load per vehicle.
Alongside demand forecasting for capacity planning and logistics tracking chatbot for customer ETA questions. Hub: AI solutions.
How optimization works
| Component | Role |
|---|---|
| Distance / duration matrix | Road network via map provider or OSRM (scoped) |
| VRP solver | OR-Tools, heuristics, metaheuristics for 50–5,000+ stops |
| ML ETA model (optional) | Predict leg duration from time-of-day, weather, city (scoped) |
| Constraint engine | Hard vs soft windows, priority customers |
| Re-optimization | Re-solve subset when cancellations or rush orders |
| Human override | Dispatcher drag-drop; lock stops; re-run |
This is operations research + ML—not an LLM drawing routes on a map.
Features we implement
Planning API
POST jobs + fleet → routes JSON in minutes (scoped by size)Dispatcher dashboard
Map, unassigned queue, manual edits, exportDriver app hooks
Stop sequence, navigation deep link, status callbacksGeocoding pipeline
Address cleanup for Indian pincodes and landmarksTerritory zones
Pin code / polygon assignment to hubsWhat-if
Add vehicle, compare cost vs current planKPI tracking
km/stop, on-time %, utilization vs manual baselineWebhook events
Route published, driver started, stop completedIntegration
OMS/WMS via API integration services
OMS/WMS via API integration services.
Architecture
Orders / jobs (OMS, WMS, CSV, API)
Geocode + validate addresses
Duration matrix (map service + ML adjustments)
VRP solver + business constraints
Routes → dispatcher UI + driver mobile app
GPS feedback → ETA refresh + dynamic re-opt (scoped)
Analytics vs planned (km, time, SLA)
Scale — cluster large metros; parallel solve per zone
SLA — nightly batch for next day + intraday re-run for same-day
Use cases by industry
| Industry | Route profile |
|---|---|
| Ecommerce / quick commerce | High stop count, tight windows, bike fleets |
| FMCG / distributor | Bulk to retailers; weight-capacity trucks |
| Pharma / cold chain (scoped) | Time + temperature chain handoff points |
| B2B spare parts | Field service + parts van same day |
| Waste / recycling (scoped) | Fixed pickup schedules + dynamic loads |
| Hyperlocal (scoped) | Sub-2 km clusters, walker/bike mix |
Pairs with ecommerce fulfillment operations when you own last-mile (scoped). Ecommerce fulfillment.
Integrations
| System | Role |
|---|---|
| Custom TMS / dispatch | Job ingest and route publish |
| Mobile driver app | Stop list, POD, GPS ping |
| Map / routing API (scoped) | Distance matrix, turn-by-turn link-out |
| Warehouse intelligence AI | Pick-ready time → departure window |
| Zoho CRM | Field visit scheduling (scoped) |
| WhatsApp API | ETA SMS/WhatsApp (scoped) |
Google Maps stop order is not fleet optimization. We solve capacity, multi-vehicle, and time windows at scale—and prove savings against your current manual plan.
Route optimization vs other logistics AI
| Product | Focus |
|---|---|
| Route optimization AI (this page) | Where should each vehicle go, in what order? |
| Demand forecasting AI | How much volume tomorrow by lane/hub? |
| Warehouse intelligence AI | Pick paths and slotting inside DC |
| Logistics tracking chatbot | Customer/dispatcher FAQ on shipment status |
| Supply chain analytics AI | Network KPIs and scenario planning |
Together: forecast volume → plan routes → warehouse pick timing → customer ETA bot.
Why Teenva AI
Logistics product team
Solver + mobile app + dispatch UIIndia urban density
Pin codes, one-ways, bike vs van assumptionsMeasurable ROI
km and stop-time reduction vs baseline routesOwn the engine
API in your cloud, not per-driver SaaS tax forever (optional hybrid)Ops
Managed IT support when map or OMS APIs change
Solver + mobile app + dispatch UI. Ops via managed IT support.
Our delivery process
Discovery
Fleet size, stops/day, constraints, current planning tool
Data sample
Historical routes, addresses, SLA outcomes
Baseline
Measure manual plan km and on-time %
Geocoding cleanup
Fix bad addresses in sample
Solver tuning
Constraints modelled; test on past days
Dispatcher UI
Map and edit workflow
Driver pilot
One hub or shift; GPS feedback (scoped)
Dynamic re-opt (scoped)
Intraday insert rules
Rollout
All hubs; monitor KPIs weekly
Frequently asked questions
We build custom or integrate—you own logic for your constraints and pricing model.
100–2,000+ per zone depending on solver time budget; cluster metros for scale.
Matrix refresh + ML ETA (scoped); full live traffic re-opt every minute is costly—usually periodic.
Separate speed profiles, capacity units, and road restrictions in model.
No—VRP uses deterministic solvers; LLM may assist address parsing only (scoped).
We build pin code + landmark cleanup and manual geocode override in dispatcher UI.
Re-optimize remaining stops with locked completed legs (scoped).
Driver app POD hooks integrate with your OMS—not part of solver core.
API deploys in your AWS/GCP/Azure; map tiles per your vendor contract.
10–12 weeks MVP (batch daily routes + dispatcher map) with job API and sample fleet.
Build your route optimization engine
VRP, last-mile delivery, time windows, and driver apps—for fleets and 3PL in India.
Build your AI solution with us
Ready to take your business to the next level?