BKT Chooses Stage Intelligence to Transform Guadalajara’s Bike Share Scheme with Artificial Intelligence

Stage Intelligence has partnered with BKT bicipública to simplify and accelerate Bike Share Scheme management in Guadalajara, Mexico. 


LONDON, 7 February 2018 – Stage Intelligence, the leading provider of Bike Share Scheme management solutions, has been selected by BKT bicipública, a leading Central American Bike Share operator, to deploy its BICO Bike Share management platform. BKT operates the MIBICI system in Guadalajara and will use the Artificial Intelligence-based platform to offer citizens an optimised rider experience and grow their scheme.


Stage’s deployment with BKT is the first time AI will be used in a Bike Share Scheme in Mexico. BICO will enable BKT to rapidly and efficiently distribute cycles across the city and ensure that riders have bikes and docks available when and where they need them.


“BKT and Stage have a shared vision for simple, efficient and user-centric transportation. Together, we are bringing innovation to Guadalajara’s Bike Share Scheme and using AI to give riders the best possible Bike Share experience,” said Tom Nutley, Head of Operations at Stage Intelligence. “AI makes it simple to grow a Bike Share Scheme and provide services that create life-long riders. This is a great opportunity for Guadalajara to innovate in clean and sustainable transportation.”


The Guadalajara Bike Share Scheme is the second largest and the most important Bike Share Scheme in Mexico serving estimated population of over five million people.


“The rebalancing is one of our biggest challenges in the operation of the public bicycle system in Guadalajara. BICO has allowed us to take better advantage of our resources to improve our service. We focus our efforts on achieving user satisfaction. BICO is an essential part to provide a better service and now satisfaction is also for our staff,” said Noé Santana, Operation Manager at BKT bicipública.


Stage’s AI-based BICO platform uses citywide data and the leading AI-technology to provide actionable insights for operators and addresses some of the biggest challenges in Bike Share. Stage recently implemented its internationalisation process that enables the BICO platform to be easily deployed in cities like Guadalajara and cater to the specific needs of its citizens.


“BICO has been very useful for the improvement of our services, the performance of our staff and the understanding of the system. We are very happy to have integrated it into our tools for the operation” said Mario Delgado, Director at BKT bicipública.


The talks between BKT and Stage kicked off as part of the i-Mobility Week in 2017. The Department of International Trade (DIT) in Mexico facilitated the trip to Mexico and helped organise the talks with BKT. The DIT enables UK companies to trade overseas and supports new innovations abroad. It was critical in setting up initial meetings with MIBICI operators and providing guidance throughout the contract process.


“The partnership between Stage Intelligence and BKT demonstrates how organisations in the UK and Mexico can collaborate to create greener cities and happier citizens. Thanks to the support of the British Embassy in Mexico, Stage and BKT have shown that innovation doesn’t have borders. We are very proud to have joined this partnership and we look forward to Stage and BKT growing their partnership and enabling each other’s success in the long term,” said Manuel Mandujano, Trade and Investment Officer at British Embassy Mexico.




About Stage Intelligence

Stage Intelligence specialises in developing Artificial Intelligence solutions for the transport and logistics industry. Its flagship solution, the BICO recommendation engine, delivers real-time intelligence for the management of bikeshare schemes. BICO enables precise and optimal decision making and has been purpose-built to remove the complexity from managing resources within a bikeshare scheme. Customers choose Stage Intelligence because our solutions increase their agility, adaptability and enable them to move beyond traditional manual processes. We collaborate with customers to solve complex problems and deliver solutions that have a lasting impact on their operations.


About BKT bicipública

BKT bicipública is a leading bike share operator across Latin America that finds integral solutions for implementing public bicycle systems within cities. It has been working on city projects for over 10 years to support the development and execution of their plans. BKT uses the most robust technology in the market and manages more than 50,000 bicycles, 3,900 stations and 160 million trips around the world. It currently operates the MIBICI system in the Metropolitan Area of ​​Guadalajara, its second largest and most important scheme in Mexico.


Artificial Intelligence for Modern Transport Operators

With an AI-based management platform, transport operators benefit from utilising a variety of data sources. For Bike Share Schemes, the platform can give insights as to where bikes are required and instantly inform distribution trucks about where bikes need to be picked up and dropped off. When information is being processed instantly and communicated to drivers, there is no lag between new demand emerging and that demand being served.

The value of AI is its ability to process vasts amount of data across a Smart City and make it useful for operators. Citizens get the resources they need and that supports the long-term sustainable growth of public transport.

As a form of modern transport, AI platforms simplify the management of Bike Share Schemes and deliver unique benefits to operators:


User Satisfaction

Increased user satisfaction by ensuring bikes and docking points are available when and where required


Cost Reductions

Improved operational efficiency and reduced requirement of operational resources


Remove Unnecessary Processes

Move away from traditional schedule or dispatch-based approaches and eliminate wasted journeys


New Visibility

Real-time truck locations, colour coded station status and station clustering as well as access to advanced analytics and actionable reports via a single dashboard


Increased Autonomy

Drivers receive direct communications often via a mobile app, allowing them to work independently of each other and the back office with less wasted time


Greater Control

Autonomous operation of a Bike Share Scheme that reflects real time conditions, offers consistent delivery instruction and a detailed overview of the scheme


Scenario Simulation

The simulation engine in such management platforms offers the ability to see responses to “what if” scenarios, allowing improved and more efficient resource planning


Scale Up

Increase the size of a Bike Share Scheme without the need to simultaneously increase available resource to maintain operation levels


The demand for public transport is growing with more citizens turning to Bike Share Schemes as a viable mode of transport. In a growing and competitive Bike Share market, AI could be the key to success for many operators. It has already proven its value to some of the largest schemes in the world and will continue to be at the heart of modern transportation in the future.


To find out more about the advantages of utilising AI in transportation read our full whitepaper on ‘How to Grow a Smart City Bike Share Scheme’.

Solving Distribution Challenges in Bike Share Schemes

Effective distribution, in some of the best Bike Share Schemes, require immense amounts of citywide data to be captured, processed and used. Increasingly, schemes around the world are using city data to not only optimise its redistribution but to also show complete visibility to its users as to where the bikes are on its system map.

It’s how Bike Share Schemes use this data that drives value for operators, riders and cities. Bike Share Scheme operators are often familiar with rider statistics and patterns but the challenge is to use this data to accelerate growth within a scheme.

Tracking growth and stimulating growth are often two very different things. At the heart of new growth is rider experience. Bike Share Schemes are challenged to offer a consistent rider experience across a city while ensuring that using a Bike Share Scheme is easy, convenient and enjoyable for the rider. A positive and consistent Bike Share Scheme begins and ends with two questions:


  1. “Can I get a bike where I want one?”
  2. “Can I dock my bike at the end of my journey?”


If a Bike Share Scheme can guarantee these two things, it is likely that a rider will have a positive riding experience. When a rider can borrow a bike and dock it, they are more likely to use the scheme again and make it part of their routine.

That’s good for the Bike Share Scheme as it will help to grow overall ridership and new people will experience the city using shared bikes. A Bike Share Scheme with an active and growing ridership is able to invest and expand its schemes.

The data available in a city can be used to ensure that riders can access bikes and docks where and when they want them. Different days of the week, weather, events, seasons, local conditions and scenarios, and a whole range of criteria can shape how a Bike Share Scheme is used.

On a rare rainy day in Los Angeles, people may not cycle at all. In Amsterdam, there may only be a slight variance in usage patterns. At the same time, different events can be connected like a sunny day in a city, matched with a train drivers strike and major sporting event being held in one area of the city. All of these factors can influence how a scheme is functioning and where more or less bikes are needed.

Artificial Intelligence (AI) can be an excellent tool for simplifying Bike Share Scheme operations while using the power of data to drive decision making. AI can process a variety of data both historically and in real-time
to deliver actionable insights for Bike Share Scheme operators. Operators gain visibility into all of the criteria shaping a cityscape and benefit from useful insights to optimise bike distribution to match changing conditions.

AI accelerates how decisions are made by operators while taking the guess work out of bike distribution. The AI technology can predict peak times up to 12 hours in advance, enabling operators to manage supply and meet requirements in those areas. This ultimately leads to bikes and docks being available and riders getting a better Bike Share experience.


To find out more about the role data and AI has on a Bike Share Scheme, read our full whitepaper on ‘How to Grow a Smart City Bike Share Scheme’