01An unexplained gap
Every rupee of the gap, split into causes with owners.
- Volume plus rate equals the total gap — exactly, by construction
- Each cause has an owner and a Monday action
The review ends with five decisions
EnterpriseFreightPlan · transport cost planning & actuals
Budget the freight bill. Then explain every rupee it moved.
For logistics heads who move product from plants to depots through many carriers. An optimiser picks the cheapest feasible plan — plant, carrier and truck for every depot — and at month-end the gap between plan and actual is split into causes, each with an owner and the action for Monday.
- 13.7% below lane-by-lane planning
- 5 causes behind every rate overrun
- Google OR-Tools whole-truck optimiser
Optimised budget₹4.01 Cr · saves ₹63.4 L
Biggest causeEmpty truck space · +₹18.8 L
SolverWithin 1% of optimal · 13 s
WhySound familiar?
Three things we hear in every first conversation.
From logistics heads and CFOs. Composite quotes from discovery calls — the problems are real; the names are left out.
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“Freight went ₹45 lakh over budget. Nobody can say why.”
Volume, rates, carriers, spot trucks — everyone has a theory and nobody has a number.
CFOA gap with no owner
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“Every lane is planned on its own.”
Each depot gets its usual plant and carrier, so the network as a whole is never the cheapest.
Head of logisticsPaying more than the network needs
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“Our rate cards live in eight spreadsheets.”
One bad row breaks the model, so the plan is always last month’s plan.
Logistics analystDays lost to data, not decisions
HowWhat changes with FreightPlan
The same three problems, on the screens that solve them.
Product screens with illustrative data. In your walkthrough we load your own lanes, plants, outlets or SKUs.
02Lane-by-lane planning
The cheapest feasible plan for the whole network.
- Plant, carrier and truck for every depot, in whole trucks, within 1% of optimal
- Every plan checked against six written rules, including carrier-share policy
13.7% below lane-by-lane planning
03Spreadsheet chaos
Eight datasets, validated row by row.
- A bad row is rejected with the reason and the fix; the rest of the file loads
- Every upload is kept in the audit trail
This month’s plan on this month’s data
FieldFreightPlan in the field
The people, the phone, the place.
The workplace it runs in, the person who uses it on a phone, the team at the desk and the detail it reads.
Photographs are illustrative — real customer sites are not shown.
- ₹63.4 LSaved a monthvs nearest plant + cheapest quote
- 1,045Trips instead of 1,463bigger trucks, fuller loads
- +₹48 LRate variance explainedsplit into 5 causes, residual ₹0.01 L
- 13 sTo a provable planwithin 1% of optimal
- 8CSV datasetsvalidated row by row
- 9Screensthis month · act on it · reference
01Open FreightPlan
See where ₹45 L went. Then see what fixes it.
Click through it. The budget bridge, the five causes and their owners, the optimised network against the naive one, a carrier-share policy priced live, the solver pruning its search, and a CSV that loads without failing on bad rows.
autowhat · FreightPlan / What happened
Illustrative data
Illustrative network and sample-month figures — not customer data. In your walkthrough, these are your plants, depots, carriers and rate cards.
02What the optimiser decides
For every depot: which plant, which carrier, which truck.
Minimise landed cost, subject to six rules written down once and checked on every plan. Unserved demand is a penalised slack — so you always get a plan back, plus the exact shortfall.
minimise Σ trips × landed cost per trip + Σ unserved × penalty landed max(load, min billable) × rate × (1 + fuel%) + toll + handling × load
- DemandEvery depot gets its tonnage — or the shortfall is reported, never hidden.
Σ trips × load + unserved ≥ demand - Plant outputNo plant ships more than it makes this month.
Σ trips × load ≤ monthly output - Fleet, in truck-daysA truck on a long lane completes fewer trips than one on a short shuttle.
Σ trips × round-trip days ≤ trucks × days × utilisation - Carrier shareNo single carrier takes more than its cap of any depot.
volume[carrier, depot] ≤ max share × demand - CommitmentsContracted minimum volumes are honoured.
Σ volume[carrier] ≥ minimum commitment - Whole trucksYou can’t dispatch two-thirds of a truck.
trips ∈ ℤ⁺
03Plan to actual
Eight steps. One number nobody argues about.
The same landed-cost formula prices the plan and the actuals, so they can never drift apart. Volume plus rate equals the total gap — exactly, by construction.
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01
Load the masters
CSV · 8 datasets
Plants, depots, lanes, carriers, fleet, rate cards, demand — validated row by row.
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02
Price every option
Landed cost per trip
Rate, fuel surcharge, toll, handling and the minimum billable tonnage, in one formula.
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03
Solve the network
Google OR-Tools · SCIP
Plant, carrier and truck type for every depot, in whole trucks, within 1% of optimal.
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04
Publish the budget
Plan per lane
What each lane should cost this month — and what your sourcing policies cost.
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05
Load the trip log
Actuals
Every dispatch, its load, freight bill, detention and on-time status.
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06
Split the gap
Volume vs rate
“We moved more” versus “each tonne cost more” — exactly, by construction.
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07
Name the causes
Driver ladder
Five causes, five owners: empty space, rate card, unplanned trips, detention, service.
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08
Act on Monday
Findings ranked by ₹
Each finding comes with its owner and a link that filters straight to the evidence.
04Built to be trusted
Colour follows the outcome. Never the sign.
Every table sorts, searches and exports; every row opens; every finding links to filtered evidence. Direction is shown four ways — glyph, sign, word and colour — so it survives a printout.
This month · 3
- What happened · budget bridge
- Where it went · lane, carrier, trip
- Outcome flags
Act on it · 3
- Savings available · rate cards
- Plan next month
- Policy what-if
Reference · 3
- How it works · 16 steps
- Live branch-and-bound trace
- Data & uploads
Multi-tenant
Every dataset scoped to its company; nothing shared across tenants.
Staged uploads
Row counts, missing columns and the effect of upsert vs replace shown first.
Reconciled
Volume + rate = actual − plan, and the five causes sum to the rate gap.
Your cloud
Runs on your infrastructure, with your rate cards and trip logs.
FAQQuestions we get about FreightPlan
Straight answers, before the call.
FreightPlan is an OR-Tools optimiser for the freight budget — plant, carrier and truck for every depot, in whole trucks, within 1% of optimal — and every rupee of overrun split into causes with owners. Short, factual answers for buyers, procurement and the assistants people ask first.
In short. FreightPlan is an OR-Tools optimiser for the freight budget — plant, carrier and truck for every depot, in whole trucks, within 1% of optimal — and every rupee of overrun split into causes with owners. It is built for logistics heads and CFOs. It exists to remove the problems those teams describe in almost every first conversation: a budget gap with no owner; depot-by-depot habits that cost the network; and plans that are always last month's, because one bad row broke the model. With FreightPlan, teams get volume plus rate equals the total gap — exactly, by construction, the cheapest feasible plan for the whole network, and eight datasets validated row by row, with the fix named. It connects to OR-Tools, Rate cards & contracts, Volume forecasts and Variance analysis, is used by Logistics · finance, and runs on web. Like every Autowhat AI product, FreightPlan goes live on one site, lane or process first, usually within weeks, on managed cloud, in your own VPC or on-premises, and shares one operational record with the other products, so the second deployment reuses the data and integrations of the first.
Who is FreightPlan for?
Logistics heads and CFOs. An OR-Tools optimiser for the freight budget — plant, carrier and truck for every depot, in whole trucks, within 1% of optimal — and every rupee of overrun split into causes with owners.
What problems does FreightPlan remove?
a budget gap with no owner; depot-by-depot habits that cost the network; plans that are always last month's, because one bad row broke the model.
What do we get with FreightPlan?
volume plus rate equals the total gap — exactly, by construction; the cheapest feasible plan for the whole network; eight datasets validated row by row, with the fix named.
What does FreightPlan connect to, and who uses it?
It connects to OR-Tools, Rate cards & contracts, Volume forecasts, Variance analysis. Users: Logistics · finance. Channel: Web.
How do we start with FreightPlan?
With a 30-minute working session on your own data — an engineer from the relevant sector, not a sales queue. The first wave is scoped in that call; most products go live on one site, lane or process within weeks and then scale.
Where does FreightPlan run, and who owns the data?
On managed cloud, in your own VPC (AWS, Azure or GCP) or on-premises, with your keys. SOC 2 Type II and ISO 27001 controls, India data residency when required, and local or open-weight models when policy demands it. The data stays yours.
05Walkthrough
Bring last month’s rate cards and trip log. We’ll show you where the money went.
A working session with the engineers who build it: your network loaded, next month’s budget solved, and last month’s overrun split into causes with owners.