The founder was still sending fuel prices by text. His company had grown from five locations toward 50, and the daily instructions that once held everything together were becoming a liability. Competitor checks were irregular. Updates arrived at different speeds. Knowing whether a price had actually reached a pump was its own little mystery.
That anonymous retailer, described in a Kalibrate customer account, offers a useful entrance to a company whose work usually stays out of sight. Kalibrate sells software, data and analytical services for two decisions that physical businesses keep making: where to operate and how to price. One can commit capital for years. The other can change before lunch.
The inbox gives out before the ambition
The retailer installed Kalibrate Fuel Pricing, replacing messages with a central workflow and an audit trail. According to the account, the founder eventually left daily pricing to three trained analysts. At 250 stores, a competitive review included four vendors and pilots with two. The company stayed with Kalibrate, citing confidence in competitive data and support.
The lesson is wonderfully unglamorous. Expansion had exposed a coordination problem before it exposed a shortage of sophisticated mathematics. Someone needed to know what had been decided, what had been sent and what had happened. Automating a daily instruction created room for people to examine the instruction itself.
reach the pump?
A decision only becomes useful when the organization can execute it and check the result.
The price still belongs to the retailer
EG America had a different version of the same headache. Acquisitions between 2018 and 2020 left it with several pricing systems. Its case study describes consolidating more than 1,600 sites, across 10 banners and 31 states, onto Kalibrate. Cumberland Farms’ experience with the software helped persuade the wider business.
Rules handled routine decisions. Analysts could concentrate on exceptions and use two-way data connections for additional reporting in Power BI. Joseph Margres, its retail petroleum pricing manager, drew an unusually careful boundary around the result.
“I can’t say that volume has gone up because of Kalibrate”
Joseph Margres · EG America
His point was that the retailer’s strategy drove volume; the software helped implement it. That distinction makes the account more useful than a floating percentage promising prosperity. Kalibrate’s value here is the machinery for carrying out decisions consistently and seeing where they need attention.
The fuel pricing product combines configurable rules, demand modeling, reporting and connections to operational systems. Recommendations can be reviewed, modified or rejected. Retailers can automate prices that satisfy their chosen validations and concentrate human attention on the awkward cases.
Breakfast needs a map and a clock
Across the business, another team is asking where a store should exist in the first place. Kalibrate Location Intelligence, usually shortened to KLI, brings location information, customer data and forecasts into a shared planning environment. It supports decisions about openings, closures, relocations and the effects of nearby sister stores.
Bojangles makes the work pleasantly concrete. In its customer interview, real estate analysis director Mark Hughes describes starting with the number of restaurants a market can support, then narrowing down trade areas and individual sites. Breakfast is a substantial part of its business, so traffic timing matters to the choice.
A road can be busy without being busy in the way a breakfast restaurant needs. That observation explains why a traffic count alone cannot settle a lease decision. The company needs to understand when people pass, where they are going and how the proposed restaurant fits into the wider network.
Kalibrate’s analytical services also address cannibalization: the sales a new location takes from an existing one. A store can meet its own revenue target while adding disappointingly little to the group. Looking at the portfolio changes the question from “Will this store sell?” to “What does opening it add?”
Two family trees, one decision business
The business has an academic ancestor. Knowledge Support Systems emerged from the University of Manchester Institute of Science and Technology in 1993. Professor Madan G. Singh, whose research concerned industrial decision-making, is identified as its founder in his contemporary academic biography. KSS later concentrated on fuel pricing and adopted the Kalibrate name in 2013.
The longer history runs through Market Planning Solutions Inc., founded in Tulsa in 1970 and acquired by KSS Fuels in 2011. That explains the apparent calendar trick behind a 1993 business advertising more than 50 years of experience. Different branches of the group started at different times.
Hanover Investors took Kalibrate private in 2017. The announced offer valued the issued equity at approximately £29 million. Later acquisitions added Canadian fuel data from Kent Group, software from Trade Area Systems and eSite, and predictive expertise from Intalytics. KLI arrived in 2022. The IMST acquisition, announced in September 2024, expanded forecasting across convenience stores and fuel sites.
This history helps explain the product mix. Kalibrate assembled a business around related decisions rather than a single kind of map. Its expertise includes collecting market observations, estimating demand, evaluating sites and helping operators act on the results.
What the buyer is really paying for
Kalibrate sells a combination of software access, licensed data and analytical work. Its KLI pricing explanation names three variables: third-party datasets, user seats and whether analytics are included. The purchase is therefore a scope decision. Which markets, which people and which questions need coverage?
The company reports more than 1,000 clients. Its customer base extends from fuel and convenience businesses to restaurants, retailers, healthcare organizations and financial services. Its careers page describes more than 300 employees, hybrid offices, flexible hours and regular learning activities. Support and domain knowledge are part of what customers are buying alongside the interface.
For a buyer, the cost question should extend beyond the license. A useful evaluation would ask who prepares the internal data, which external datasets cover the intended markets, how often those observations are refreshed and who will maintain the resulting workflow. A planning team should bring an actual rejected site as well as an attractive prospect to a demonstration. Can the analysis explain both? A pricing team should bring an exception that currently consumes an afternoon. Can the proposed process resolve it, document it and leave the analyst able to explain the decision? Those are more revealing tests than a tour of dashboards.
Alternatives depend on the job. PDI Fuel Pricing also supports the execution of retailer-defined strategies. Esri’s ArcGIS Business Analyst offers geographic market analysis, customer profiling and site selection. An organization with its own analysts may assemble a workflow around GIS tools and data suppliers.
Kalibrate’s particular pitch is the combination of retail modeling, operational pricing and specialist services. That does not make every component exclusive. It does give a buyer a way to connect questions that otherwise land with different vendors. The sensible comparison is a live business problem, tested with the buyer’s own data.
A new store’s sales are not all new sales.
An AI companion walks into the planning meeting
The July 29, 2026 KLI release notes describe a rebuilt k.ai Companion, which helps users question reports, compare results and return to earlier conversations. Hotspot Analysis lets teams combine chosen variables and weights into a reusable view of market suitability. A refreshed mobile experience takes the work into the field.
An April 2025 announcement had already introduced Microsoft Azure AI Foundry capabilities. The direction is clear: make specialized analysis easier to interrogate. A colleague can ask why a location scores well without first becoming an expert in every menu.
There is still physical work underneath. Kalibrate says its Fuel Planning data collection uses on-site surveys in many markets and third parties in others. That product can simulate openings, closures, additional pumps and changes to convenience retail. A conversational interface sits above observations that someone still has to gather.
Electric vehicles extend the pricing business into another operating routine. Kalibrate’s charger software supports peak, off-peak and event-based rules, with integrations for distributing updates. The commercial problem is familiar: keep a growing network’s prices organized while accounting for local circumstances and changing energy costs.
The pricing question reaches court
There is also a public-interest question behind the pump display. A proposed class action filed June 22, 2026 in federal court in California alleges that Kalibrate and fuel retailers used algorithmic pricing to coordinate and inflate gasoline prices. The complaint challenges the competitive effects of shared pricing technology. These are allegations, not established findings.
Kalibrate’s published position says customer data is kept separate, optimization models are trained exclusively for each customer and retailers retain control of their prices. That policy should be read as the company’s account of how its products work, not as an adjudication of the lawsuit.
The dispute puts a sharper edge on the distinction Margres made. Software that helps a business execute prices has consequences for the people paying them. Questions about inputs, control and competitive independence belong beside questions about efficiency.
The useful habit: make the decision testable
The practical idea to copy is the sequence. Define the decision, assemble relevant observations, record the assumptions, then compare the outcome with the expectation. For a new store, count transferred sales. For a pricing team, confirm execution before crediting an apparent improvement to the model.
Those habits also describe the conditions the software needs. Stale observations, a poorly chosen objective or a team that never revisits its assumptions can produce a polished answer to yesterday’s question. Kalibrate itself says proprietary site data must correlate with performance to support Fuel Planning models; otherwise it may serve only an informational purpose.
A forecast earns its place when it can be questioned. A pricing process earns its place when it can be checked. Behind the maps, the rules and the chat window, Kalibrate’s everyday proposition is that retailers can make those expensive decisions more deliberately.