Clustering before routing
Employees are grouped by pickup density along the corridor they actually live on, then routed — so a Sarjapur employee is not appended to a Hebbal run because the seat happened to be free.
Employee transport software · Bengaluru, Karnataka
No Indian city concentrates night-shift employee transport like Bengaluru, and none punishes a bad route plan faster. The tech corridors sit on opposite edges of the city, so a roster that ignores geography puts people in a cab for two hours before their shift starts.
Where it runs
Routing is planned around these rather than across a city-wide average.
What breaks a schedule in Bengaluru
These are the local problems a generic routing engine does not know it has.
East-to-west crossings eat the roster
An employee in Electronic City rostered onto a Whitefield route crosses the whole city twice a day. Without a clustering step that respects the corridor, allocation quietly builds these trips and nobody sees it until the ride-time complaints arrive.
ORR congestion is not uniform
The Outer Ring Road behaves like several different roads depending on the hour and the stretch. A single city-wide traffic assumption produces pickup times that are early on one leg and late on the next.
Night-shift escort compliance at volume
With a large night-shift population, escort rules for women on first pickup and last drop have to be enforced at the moment of allocation. Auditing them after the fact tells you about a breach you have already had.
How taSki answers them
Employees are grouped by pickup density along the corridor they actually live on, then routed — so a Sarjapur employee is not appended to a Hebbal run because the seat happened to be free.
Travel-time multipliers are configured by city and by hour rather than assumed, so the 9pm plan and the 6am plan are not built on the same numbers.
No-first-no-last-drop logic and escort assignment are applied when the route is generated, with a timestamped record for the compliance report.
The platform
The same modules run in every city; the routing model is what adapts.
Shift rosters, ad-hoc requests and attendance in one place, so the transport plan is built from who is actually coming in.
Clustering by pickup density, then routing against real road networks — with ride-time ceilings and vehicle capacity as constraints rather than preferences.
Trips are allocated across your operator panel by coverage, rate card and compliance status, with double-assignment blocked at source.
GPS tracking against the planned route, escort compliance, and an in-app SOS that reaches the transport desk rather than a call centre.
Trips, rate cards and vendor invoices reconciled automatically, so disputes are evidenced rather than argued.
Every allocation, escort assignment and exception timestamped and exportable for statutory or internal compliance reporting.
Questions
Still unanswered? Our solutions team replies within one business day.
Talk to the team →No. taSki is software and owns no vehicles. Your existing transport operators run the trips on the platform. Where you would rather contract once, taSki can also be your transport vendor — in which case taSki holds the agreements with the empanelled operators and you contract only with taSki.
Yes, and most programmes do. Operators onboard onto the Partner Suite in days, usually without changing their commercials. There is no supply lock-in, and no requirement to retender before you can use the software.
One site first. A single Bengaluru location, one shift pattern and one roster is modelled against your current spend, so the business case uses your data rather than a benchmark. Most programmes run four weeks from first site to steady state.
Escort assignment, no-first-no-last-drop logic, driver vetting and in-app SOS are enforced when the route is generated rather than reviewed afterwards, and every decision carries a timestamped record for statutory and internal reporting.
See it on your Bengaluru roster
A 30-minute review using your own roster and rates, not a generic benchmark.
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