Better schedules, routes and prices, worked out for your business.
Solves the vehicle routing problem across your fleet with time windows, capacities, driver shifts, and live traffic to produce least-cost daily routes. Re-optimizes mid-day for new orders, cancellations, and delays, dispatching turn-by-turn sequences to drivers.
Builds staff rosters that meet forecasted demand while honoring the working-time rules you configure, contracts, skills, availability, and fairness rules. Minimizes overtime and understaffing and republishes when someone calls out.
Decides which items to mark down, by how much, and when to clear aging or seasonal stock before it loses value. Balances sell-through against recovered margin and coordinates markdowns across stores and channels.
Computes how to pack orders, pallets, and cartons into containers or trucks to maximize fill and respect weight, stacking, and fragility rules. Produces a 3D load plan and loading sequence for the warehouse.
Balances sales territories by potential, workload, and travel while assigning fair, achievable quotas aligned to company targets. Rebalances as reps join, leave, or accounts move, keeping coverage equitable.
Learns a building's thermal behavior and controls HVAC setpoints and schedules to minimize energy cost while holding comfort bands. Uses weather forecasts, occupancy, and time-of-use tariffs to pre-cool/pre-heat optimally.
Optimizes table assignments, turn times, and reservation acceptance to maximize covers and revenue across service periods. Decides which reservations to accept, how to seat walk-ins, and when to hold or release tables.
Forecasts demand by date, room type, and segment, then sets rates and length-of-stay controls to maximize RevPAR. Continuously re-prices as pickup, competitor rates, and events change, syncing to your PMS/channel manager.
Predicts the incremental lift and cannibalization of each promotion and selects the promo calendar that maximizes profit within budget and trade-spend limits. Avoids overlapping promos that steal from each other.
Forecasts inflows and outflows and recommends the timing of payments, collections, and short-term financing to avoid shortfalls at minimum cost. Optimizes payables/receivables and buffer levels against a liquidity policy.
Projects future workload and recommends how many people, with which skills, to hire, cross-train, or contract over the planning horizon. Optimizes the staffing plan against service targets and cost.
Assigns SKUs to storage locations to minimize picker travel based on velocity, affinity, and ergonomics. Recomputes slotting as demand shifts and produces re-slotting move lists for the team.
Sequences jobs across machines to minimize makespan and late orders while respecting setups, capacities, and material availability. Reschedules on breakdowns and rush orders and pushes the plan to the shop floor.
Analyzes trip demand and costs to recommend the optimal number and type of vehicles to own, lease, or retire. Balances capital, maintenance, and utilization against service levels over the planning horizon.
Predicts churn and price sensitivity per customer and selects the minimum retention incentive that keeps profitable customers. Targets only those whose behavior the offer will actually change, within budget.
Optimizes inbound/outbound dock door assignments and carrier appointment times to smooth flow and cut detention. Balances yard capacity, labor, and trailer priorities across the day.
Models willingness-to-pay across segments to design plan tiers, prices, and feature bundles that maximize long-term revenue. Simulates migrations and churn before you change packaging.
Builds course timetables assigning rooms, teachers, and time blocks with no clashes while honoring capacity, equipment, and preference constraints. Minimizes gaps and re-solves when courses or staff change.
Analyzes item profitability and popularity to reprice, reposition, or cut menu items and design combos that lift check averages. Uses ingredient costs and demand to set profit-optimal prices.
Assigns clients to the best-fit staff member based on skills, preferences, history, and workload balance. Optimizes overall satisfaction and utilization rather than first-available assignment.
Takes supplier bids with volume discounts, capacities, and quality/lead-time constraints and computes the lowest-cost sourcing split. Handles multi-item, multi-supplier awards with business rules.
Schedules EV or equipment charging and battery discharge against time-of-use tariffs, demand charges, and operational needs. Minimizes energy cost while ensuring assets are ready when required.
Mines purchase patterns to design product bundles and cross-sell offers that maximize incremental margin. Chooses bundle contents and pricing that lift attach rate without cannibalizing standalone sales.
Decides which products to stock at each store based on local demand, space, and assortment rules. Tailors range by location to lift sales per square foot while controlling SKU proliferation.
Builds low-cost duty pairings and rosters for mobile crews across multi-day trips honoring the rest, qualification and base rules you configure. Re-solves for disruptions to keep operations within your configured rules and covered.
Sets dynamic parking or space rates by time, demand, and event to maximize revenue and utilization. Predicts occupancy and adjusts pricing and allocation to avoid both empty bays and overflow.
Schedules preventive and predictive maintenance to minimize downtime and cost given failure risk, crew, and parts. Balances doing work early against running to failure using condition data.
Recommends optimal timing for harvest, planting, or production actions to maximize yield and value given weather, prices, and capacity. Balances quality windows against logistics and market conditions.
Distributes a fixed labor budget across stores and dayparts to maximize service and sales given each location's demand pattern. Sets hour targets per site and reallocates as demand shifts.
Chooses the cheapest mode and carrier per shipment that still meets the delivery deadline, consolidating loads where possible. Optimizes across LTL, FTL, parcel, and intermodal with live rates.
Selects personalized renewal offers (perks and retention discounts off one published price) that maximize retained lifetime value per member. Balances price increases against churn risk using each member's usage and tenure.
Matches and pools compatible trips or jobs to share vehicles and reduce cost while keeping detours acceptable. Continuously batches live requests into shared assignments.
Allocates trade-promotion budget across accounts, brands, and periods to maximize retailer sell-through and manufacturer profit. Optimizes the plan against measured historical ROI and constraints.
Decides how many sections of each course to open and their sizes to meet enrollment demand within faculty and room limits. Minimizes unmet demand and cost while balancing class sizes.
Decides for each returned item whether to restock, refurbish, liquidate, or scrap, and routes it to the lowest-cost, highest-recovery destination. Optimizes reverse flows across facilities.
Allocates limited ad slots and sponsorships across advertisers to maximize revenue while honoring commitments and frequency caps. Prices and schedules placements against forecasted supply.
Manages ordering and distribution of short-shelf-life stock across sites to minimize expiry and shortage. Forecasts usage and optimizes transfers so units are where they're needed before they expire.
Quotes jobs at prices that win the work and hit margin targets using predicted win-probability and cost. Learns from won/lost quotes to set the profit-optimal price for each opportunity.
Recommends where to open, relocate, or close locations to maximize coverage and revenue while minimizing cannibalization and cost. Optimizes the network against demand geography and constraints.
Forecasts contact volume by interval and computes staffing that meets service-level targets at minimum cost, then routes contacts to the best-skilled agent. Combines Erlang staffing with skills-based routing.
Sets dynamic rental rates and manages availability across locations to maximize revenue per available unit. Balances utilization, length-of-rental mix, and repositioning against demand.
Plans collection routes accounting for bin fill levels, vehicle capacity, and disposal-site constraints to cut miles and missed pickups. Uses fill sensors or predictions to skip empty stops.
Allocates shared stock across sales channels and fulfillment nodes to maximize margin and service under demand uncertainty. Decides which node ships which order to cut split shipments and stockouts.
Designs sales commission structures that drive target behaviors while capping cost and avoiding perverse incentives. Simulates rep responses to plan changes before rollout.
Detects demand spikes in real time and sets surge multipliers that balance supply, revenue, and customer acceptance, within a hard cap you set and automatically suspended during declared emergencies. Learns acceptance thresholds by segment to avoid over-surging.
Sets timed markdowns on dated perishables to maximize recovered revenue before expiry across each store. Predicts sell-through at each discount and schedules reductions per item and shelf life.
Computes cutting and nesting plans for sheet, roll, or bar stock to minimize waste for a set of orders. Optimizes layouts respecting grain, kerf, and machine constraints and outputs job sheets.
Proposes project staffing plans for your managers to approve, matching declared skills and calendar availability to deadlines to protect billable capacity and project margin. Re-proposes plans as scope and timelines shift; people are never scored on performance.
Builds multi-stop tour itineraries that maximize value within time, opening hours, and travel constraints. Sequences attractions and activities per group and re-plans for weather or closures.
Structures the optimal mix of price discount, add-ons and trade-in allowance that closes a deal at target profit (financing terms stay with your licensed lender). Uses predicted close probability and customer sensitivity to shape each offer.
Schedules irrigation zone-by-zone to minimize water and energy while meeting plant needs using soil, weather, and evapotranspiration data. Optimizes timing against tariffs and pump capacity.
Schedules interview loops assigning interviewers to candidates and slots to balance load, cover required skills, and avoid conflicts. Re-solves as candidates and interviewer availability change.
Determines the optimal number, location, and role of warehouses and flows to minimize total landed cost at target service. Optimizes sourcing, production, and distribution across the network.
Curtails and shifts flexible loads during peak events to minimize demand charges and capture demand-response payments without disrupting operations. Chooses which loads to shed and when.
Plans franchise territories and the sequence of new-unit openings to maximize network coverage and revenue while limiting cannibalization. Optimizes boundaries and rollout timing against demand geography.
Allocates shelf space and positions across categories and SKUs to maximize sales per linear foot given demand and adjacency rules. Produces optimized planograms and re-optimizes with demand shifts.
Schedules crews and heavy equipment across job sites to minimize idle time and mobilization cost while meeting project deadlines. Sequences tasks with dependencies and shares scarce equipment across sites.
For companies buying the same things from many suppliers. The AI groups your spend by what was really bought and shows where different teams pay different prices, with a plan to consolidate.
For businesses offered early-payment discounts by suppliers. Each payment run the engine checks your cash and each discount and lists exactly which invoices to pay early.
For service firms whose workload depends on sales. We turn your expected sales and current utilisation into a plan of how many people you need by role and location and when, with what-if scenarios.
For businesses selling rooms, seats or time slots that are worth nothing once the date passes. The AI forecasts bookings for each date and customer type, then sets prices, availability and safe overbooking limits so you fill more of your capacity and turn fewer people away.
For marketplaces where both supply and demand swing during the day, like equipment rental, delivery capacity or local services. The AI forecasts the next few hours of supply and demand and sets prices so both sides keep using your platform.
For carshare, bike, scooter or rental equipment fleets. The AI forecasts where demand will outstrip vehicles and creates move jobs for your crews so vehicles are in the right places before customers arrive.
For airports and ground handlers juggling gates and crews. The planner assigns gates and ground resources against the live flight schedule, and re-plans when delays hit, following your size, turnaround and neighbour rules.
For builders whose schedules break when crews or equipment are double-booked. The AI re-levels your project schedule against real crews and equipment, and forecasts which activities are likely to slip.
For internet providers and network operators who find congestion only when customers complain. The AI forecasts traffic on each link from your network telemetry and recommends capacity and routing changes before peaks hit, pushing them to your network controller only after your engineers approve.
For software companies paying for cloud servers that sit half empty. The AI forecasts how much computing power and memory each of your services really needs, then recommends server sizes and where each service should run, keeping response times on target while trimming the bill.
For R&D teams chasing a target property through endless trial and error. After each round of results the AI proposes the next batch of experiments most likely to get you there and puts them straight into your lab notebook.
For R&D teams who know the properties they need but not the recipe. The AI generates new candidate formulations or molecules aimed at your targets, scores them and queues the best shortlist for your chemists.
For plants wanting better quality and yield without risking equipment. The AI reads your live plant data and suggests better temperature, pressure and feed settings within your safe limits, shown to operators to accept or decline.
For testing labs where samples wait while instruments sit idle. The planner reads your sample queue and staff calendars and builds the best run order for your shared instruments.
For R&D leaders with more projects than lab time. The AI weighs what each project could still learn and suggests how to split experiments and instrument hours between them, updating as results come in.
For chemical makers whose plant batches don't match the pilot. The AI learns from your paired pilot and plant runs and recommends adjusted settings so the first full-scale run matches the pilot quality.
For plants losing money to off-spec batches. The AI watches live process data for patterns that came before past bad batches, warns operators and ranks the most likely cause with a suggested fix.
For chemistry teams planning how to make a target molecule. The AI proposes and ranks step-by-step routes using your own reaction history and checks which reagents you already have in stock.
We look at your sales and staff costs hour by hour at each location and suggest opening hours that make you more money, then check whether the change worked.
We study how your shoppers react to shipping costs and find the free-shipping amount and fees that bring in the most profit, then test it carefully in your shop.
We learn which services customers book on which days and times and redesign your weekly appointment grid so your chairs, rooms or bays earn more.
When customers check out, we decide which delivery times to show and what to charge for each, so your drivers' routes stay tight and nothing is wasted.
We test-pack your past orders on a computer to find the handful of box sizes worth buying, and how many of each, so you pay less for shipping air and packaging.
We decide which batches go to which customers so every customer gets the shelf life they require and less of your stock passes its date in the warehouse.
We spot stock that won't sell in time and, for each product, pick the best way to turn it into money: discount, bundle, sell elsewhere, send back or donate.
We find the cheapest mix of ingredients that still meets every requirement of your product, and suggest a new mix whenever ingredient prices change.
If you visit customers on a regular schedule, we work out the best day for each one so every van's day is short and evenly loaded, and keep the plan up to date.
When something in an order is out of stock, your picker sees the best replacements for that customer, based on what they and similar shoppers have accepted before.
We create your season's fixtures and pitch bookings so teams, venues and referees all fit, keep it fair, and redo it when games are postponed.
We take your scenes, locations, cast and crew availability and work out the shooting order that needs the fewest days and moves, and update the plan when things change.
Customers book a type of room, pitch or space; we decide which exact one each booking gets so there are fewer awkward gaps and every request is respected.
We work out how much to raise prices for each type of customer, and when, so the extra revenue outweighs anyone who leaves, then track whether it worked.
Before each wholesale car auction we go through every car listed, predict what it would sell for on your lot and how fast, and give you a ranked list with the most you should bid.
We track which creators actually drove sales from your gifts and decide who gets what next time, within your product and budget limits.
We combine your incoming print jobs onto shared sheets and choose the run order so you waste less paper and do fewer setups, while every job is ready on time.
Each night we predict what every stop on your routes needs, decide which ones to visit tomorrow and give your warehouse a load list for each van.
We learn where and when you sell best, add the weather and local events, and tell you each day which spot will earn the most.
We predict how much cash and which notes and coins each till needs and tell managers how much change to order and when to bank.
We watch how busy your kitchen is and, just before it gets overloaded, automatically lengthen delivery times or pause delivery apps for a few minutes, then switch back.
We work out the latest time customers can order and still have it shipped today, carrier by carrier, and show it on your site, updating it when your staffing or order volume changes.
We estimate how full each customer's tank is from the weather and their past use, predict when it will run low and plan your deliveries so no one runs out and trucks run full.
We predict how many people each film will draw at each time and build your weekly schedule so screens are filled while meeting your film contracts.
After the first weeks of a season we re-forecast every product and tell you what to reorder and which orders to cut before each supplier's deadline.
We study how each customer uses your API and what each call costs you, then set usage limits that protect your servers without blocking customers who are paying.
We work out from your sales how fast each shelf is emptying and give staff a live list of which shelves to refill next, so busy periods never see bare shelves.
We predict how many people will come to each talk and put each one in a room that fits, avoiding clashes, and adjust later days using actual check-ins.
When a supplier stops making a part you rely on, we work out how many you'll need for the rest of its life and prepare the final order.
While a sale is running we watch how much it's costing you and, if it's heading over budget, automatically tighten it, so you never get a nasty surprise at the end.
We look at what customers ask for and what you turn away, and work out the best mix of unit sizes, table sizes or room types for your space.
We decide for each of your products whether it's better to keep it in stock or make it when ordered, and how much buffer to hold, and update it monthly.
When you have more work than capacity, we decide which jobs to send to outside partners and which to keep, so orders are on time at the lowest cost.
We forecast how many people will end up booked on each tour, class or workshop and, at your deadline, recommend running it, merging it or cancelling, and help move customers to another date.
Each day we look at what in your kitchen is about to expire and suggest specials and prices that use it up and still make money, then put them in your till.
When your storage space is limited, we decide how much of each product to keep so the space goes to the stock that makes the most money.
When a group asks for a block of rooms or seats, we work out what you'd lose by turning away regular customers on those dates and tell you the lowest rate worth accepting.
We learn which parts your technicians actually use and pick the best stock for each van so more jobs get finished on the first visit, and tell you what to restock each night.
We plan where each crop sits in your greenhouse or nursery each week as it grows, so you fit more in and everything is ready when customers need it.
We plan when each supplier should deliver to your site so materials arrive just before they're needed, the storage area doesn't overflow and the crane isn't double-booked.
We group your orders into machine loads that go together, so each run is full and every order is still ready on time.
We measure how your deposit, cancellation and return rules affect bookings and cancellations, recommend better ones and test them carefully.
We look at how buyers in each country respond to your prices and set a price for each one that brings in the most, while stopping people faking their location to get a cheaper price.
If you can't afford every reorder this week, we decide which ones to place first so you lose the least sales and margin, and prepare those orders.
When part of an order isn't in stock, we decide whether to send what's ready now or wait for the rest, based on cost and how likely the customer is to cancel.