AI Open Innovation Challenge

BACKGROUND OF THE PROBLEM

In the hospitality industry, creating personalised and seamless guest experiences is key to fostering loyalty and increasing customer satisfaction. As a PARKROYAL COLLECTION hotel we seek to improve operational efficiency and provide guests with a personalised experience and we believe technology such as facial recognition offers a compelling opportunity. Facial recognition can streamline check-in processes, enhance personalised greetings, and help staff anticipate guest needs by identifying them upon arrival.

This challenge seeks a solution that leverages facial recognition technology to optimise guest interactions, while ensuring compliance with data privacy laws and easy integration with our existing hotel management systems such as Opera and (mobile) check-in platforms. The right solution would not only improve guest satisfaction but also reduce operational burden on staff, offering a more streamlined, cost-effective, and personalised hotel experience.

We are looking for a solution that can be deployed at the following critical touchpoints:

• Hotel Reception: Receptionists able to greet guests by their last name upon arrival.
• Restaurant: Food & Beverage personnel able to greet guests and identify breakfast entitlement, be aware of allergies and dietary restriction of our guests.
• Club lounge, Spa and Wellness: Personnel able to greet guests, guest access and eligibility to be known upon arrival based on membership level of our loyalty programs or booking information.

We are looking for a solution that respects the data privacy of our guests and doesn’t store more information than strictly necessary, integrates with legacy systems and is cost-effective. Identification, of course, needs to be real-time and be able to extract data from multiple systems such as the reception- and mobile check-in systems, loyalty program database, passport scanner, and others.

Currently, no off-the-shelf solution fully meets our needs. Existing systems either lack the accuracy, necessary integration capabilities or fail to comply with stringent data privacy regulations.

TECHNICAL REQUIREMENTS / PERFORMANCE CRITERIA

Technical Requirements:

• Facial Recognition Accuracy: The system must be able to accurately identify guests upon arrival with minimal errors, even in high-traffic areas.
• Integration with Existing Systems: The solution must integrate seamlessly with systems like Opera (hotel management) and mobile check-in platforms, enabling automatic updates of guest data.
• Data Privacy and Security: The solution must ensure compliance with local privacy regulations, such as PDPA, by collecting minimal guest data (e.g., last name, photo, eligibility, allergies) and securely storing or processing this information, preferably using on-premise systems. If cloud based solutions are used, they must be secure.
• Operational Efficiency: The system should reduce the need for manual data entry and help staff serve guests faster by automatically pulling up relevant guest information.

Performance Requirements:

• Guest experience: The main driver for this challenge is to improve the guest experience. Solutions will therefore be evaluated based on their impact on the experience as evidenced by being mentioned in guest reviews (for example, mentioning the greetings by last name at check in and dietary awareness) as well as an uptick in review scores from our guests.
• Cost effectiveness: Please see below section.

COST TARGET

Cost targets will be determined on a case-by-case basis. In general we evaluate solutions based on their return on investment but the specific target will depend on the solution. Separate from the investment needed for the system we have a cost target of S$10,000 per year, per hotel for operational expenses.

TIMEFRAME FOR DEVELOPMENT

Phase 1: POC development: Q2- Q3 2025 at our ParkRoyal COLLECTION Pickering hotel in Singapore.

Phase 2: Commercial roll-out: to be determined on a case-by-case basis.

POTENTIAL MARKET / BUSINESS OPPORTUNITY

If the solution is successful, PARKROYAL COLLECTION Pickering, Singapore is willing to support a further roll-out across other locations in Singapore. Furthermore PARKROYAL COLLECTION Pickering, Singapore is part of the Pan Pacific Hotels Group with about 50 hotels in our portfolio where the solution can also be implemented.

Additionally, we are open for solution providers to deploy their solution with other players.

RESOURCES

OTHER CONSIDERATIONS

We are looking for SMEs and startups with solutions that can be implemented in a relatively short time frame (TRL of 5 and higher).

For Background IP (BIP), both parties will retain their respective IPs brought into the project. In the event of new Foreground IP (FIP) creation, ParkRoyal is agreeable to the FIP being retained by the solution provider.

BACKGROUND OF THE PROBLEM

As a leading global brand, Coach seeks to expand its retail operations efficiently across various markets. Since store expansion is one of our biggest investments, we need to make the right decision on the location and visual of new stores to maximise returns. Currently, store expansion decisions are made by triangulating diverse data sources. These decisions are often made 12-18 months in advance, and goal is to maximize better short-term and long-term planning.

Coach is therefore inviting solution providers to propose innovative, proprietary solutions to utilising Artificial Intelligence (AI), Generative AI, Large Language Models (LLMs) and other disruptive technologies to automate decision-making on crucial store expansion criteria such as location, store type, and layout.

The data sources we currently use to make these decisions include (but are not limited to):

• Competitor information
• The average footfall in existing stores
• Per square foot productivity
• Conversation or targeted conversion
• Medium income of the surrounding area
• Demographics of the particular city or region
• General macro-economic factors

We have not attempted any solutions similar to this challenge statement before, and welcome solution providers to propose suitable solutions.

Coach understands that in order to develop the solution, solution providers might need access to our data set(s). We are willing to discuss this in a case-by-case basis depending on the needs of the solution provided and subject to review by our legal team.

TECHNICAL REQUIREMENTS / PERFORMANCE CRITERIA

Technical Requirements:

• The solution should have the following basic features:
  1. In POC phase: the model will only be trained on public and/or dummy data. We hope to see a first version of the model to be able to predict some (not all) of the output parameters mentioned before.
  2. Initial output parameters desired include: Expansion location suggestions, projected footfall, footfall heatmap, etc.
  3. Desktop interface deployable on cloud and over mobile.
  4. Ability to prime the model using natural language to ensure the output is as desired.

• We target the solution to have an accuracy of 85%.
• We target the solution to significantly reduce planning time for the opening of a new location (Currently it is between 6 months to 1 year).

COST TARGET

Cost targets will be determined on a case-by-case basis.

TIMEFRAME FOR DEVELOPMENT

Phase 1: POC development: Q1 2025.

Phase 2: Commercial roll-out: to be determined on a case-by-case basis, target implementation by Q2 2025.

POTENTIAL MARKET / BUSINESS OPPORTUNITY

Coach is willing to support further pilot implementations across locations in SEA and ANZ, including both distributor and direct models. This could involve implementing in over 20-30 locations.

RESOURCES

OTHER CONSIDERATIONS

We are looking for SMEs and startups with solutions that can be implemented in a relatively short time frame (TRL of 5 and higher).

For Background IP (BIP), both parties will retain their respective IPs brought into the project. In the event of new Foreground IP (FIP) creation, potential ownership will be determined on a case-by-case basis depending on the contributions of each party.

BACKGROUND OF THE PROBLEM

As an EPC company, for Seatrium, tracking what is going on in our construction sides is important since it helps us to monitor key safety, productivity and efficiency parameters. Currently, Seatrium works with many different large contractors in different yards across the world. These contractors can include many different parties such as welders, cable layers etc. Currently, we have an existing practice where our safety managers and or project managers will conduct weekly (or sometimes daily) walkarounds to ensure work is done in compliance with the relevant safety, productivity and efficiency requirements and standards. While doing these manual checks can be sometimes useful, there are several limitations to their effectiveness including:

• Consistency and Accuracy: Supervisors can be inconsistent in their detection abilities, leading to variability in results. Factors like fatigue, attention, and experience can affect accuracy.
• Scalability: As the volume of workforce to be detected is very large, manual methods become impractical. Automated systems can handle large datasets more efficiently.
• Subjectivity: Manual detection can be subjective, with different people potentially interpreting or detecting things in different ways.
• Labour Costs: Relying on Safety/QA/Ops manpower for detection tasks can be expensive and resource-intensive compared to automated solutions. 

• Track if workers wear their PPE vests and helmets
• People counting
• Checking the productivity and general presence of workers
• Checking the occurrence of sparks or flames when welding
• etc

TECHNICAL REQUIREMENTS / PERFORMANCE CRITERIA:

1. Yard activities – grinding, welding, cutting, cable pulling, scaffolding etc
2. Yard Safety risk – drop objects, tripping, sparks, flame, fire, wet surface
3. Productivity evidence – Weldment defects and completion, tag recognition, pressure recorder and gauge, sensor reading
4. Of the aforementioned use cases, we would expect a solution provider to be able to implement at least 3-4 use cases
5. Ideally, the solution would also provide an integration with LLM’s so that our staff can interact with the system by using natural language
6. We would expect the system to be able to provide real-time intervention for certain (safety related) use cases
7. Ideally, the solution should include a dashboard to monitor key KPI’s for safety, quality and productivity. If this is not feasible, we are open for this to be included in a further commercial rollout post POC
8. The solution should eventually be able to be deployed on a variety of IOT devices such as smart glasses, robot docs, smart cameras etc
9. The data source of these are from the various IOT devices such as smart glass, robot dogs or smart cameras. The AI detection must be able to provide analytic insights for process improvements
10. We are looking for a solution that can provide us operational insights to improve our operations

• We are looking for an efficiency gain of 20% more in terms of productivity increase
• We would be looking to save approximately S$100-200K on personnel doing ad-hoc patrolling

COST TARGET

Cost targets will be determined on a case-by-case basis.

TIMEFRAME FOR DEVELOPMENT

Phase 1: POC development: Q3-Q4 2024.

Phase 2: Commercial roll-out: to be determined on a case-by-case basis, target implementation by Q1 2025.

POTENTIAL MARKET / BUSINESS OPPORTUNITY

If the solution is successful, Seatrium is willing to support further deployment across other yards worldwide. Seatrium has businesses all over the globe. Seatrium main customers include major energy companies, vessel owners and operators, shipping companies, and cruise and ferry operators. Seatrium operates shipyards, engineering & technology centres and facilities in Singapore, Brazil, China, India, Indonesia, Japan, Malaysia, the Philippines, Norway, the United Arab Emirates, the United Kingdom and the United States.

RESOURCES

OTHER CONSIDERATIONS

We are looking for SMEs and startups with solutions that can be implemented in a relatively short-time frame (TRL of 5 and higher). For Background IP (BIP), both parties will retain their respective IPs bought into the project. In the event of a new Foreground IP (FIP) creation, FIP ownership will be discussed on a case-by-case basis.

BACKGROUND OF THE PROBLEM

TECHNICAL REQUIREMENTS / PERFORMANCE CRITERIA

Technical Requirements:

• We are looking for a decrease in damages and incidents of 20% or more.
• We are looking for a productivity gain of 10% or more for the packaging line (speed / reduction in wrong packaging resulting in reduction of redelivery)
  

COST TARGET

Cost targets will be determined on a case-by-case basis.

In a post proof-of-concept phase and a solution that is implemented over several of our warehouses, we are looking for a cost target of not more than S$50 per video stream per site for a total of S$2500 per month cost (running cost).

TIMEFRAME FOR DEVELOPMENT

Phase 1: POC development: Q2- Q3 2025.

Phase 2:  Commercial roll-out: to be determined on a case-by-case basis

POTENTIAL MARKET / BUSINESS OPPORTUNITY

If the solution is successful, Toyota Tsusho is willing to support a further roll-out across our 100-200 sites in the Asia-Oceania region. Additionally, we are open for solution providers to deploy its solution with other players.

RESOURCES

OTHER CONSIDERATIONS

We are looking for SMEs and startups with solutions that can be implemented in a relatively short time frame (TRL of 5 and higher). 

For Background IP (BIP), both parties will retain their respective IPs bought into the project. In the event of new Foreground IP (FIP) creation, Toyota Tsusho is agreeable to the FIP being retained by the solution provider.

BACKGROUND OF THE PROBLEM

HomesToLife is a home furnishing brand selling a range of furniture from sofas to dining tables. We are looking for an end-to-end 3D visualisation system to speed up the furniture customisation process, thus shortening sales cycles and increasing conversion.

Customers make purchasing decisions based on different factors, including price, furniture aesthetics, and (primarily) space constraints. This causes delays in their purchasing decision

Our goal is to facilitate customers’ decision-making process to increase the number of conversions when the customers receive their quotations. Our current rate from closing to quotation is about 80%, meaning 20% of our customers do not make a purchasing decision after receiving a quotation. We would like to increase this conversion percentage by implementing an end-to-end 3D visualisation system. We believe significant efficiency gains can be achieved by allowing customers to understand how the particular piece of furniture they are interested in fits into their floor plan.

We are therefore looking for an end-to-end system that can be used both in-store and online, where customers would upload their floor plans and a generative AI system automatically configures the furniture inside their homes.

Our current customer journey can be expressed as follows:

1. Customers visit and determine if they like a particular furniture. They will be able to see different variations in our retail store.
2. Sales team will note down a customer’s preferences on variables including size and colour.
3. A quotation will be provided including price, customisation and a visualisation of the layout and floor plan (through a regular picture).
4. The quotation will be provided immediately, or alternatively it will be shared later via WhatsApp or email

• Instagram stickers of our furniture paired with pictures taken by customers to show what integration might look like.
• home 3D solutions. We opted against implementing such solutions as they often rely on existing floor plan templates rather than allowing for direct visualisation of the customer’s floor plan.

TECHNICAL REQUIREMENTS / PERFORMANCE CRITERIA

Technical Requirements:

• The solution should be able to integrate with our Sage CRM system to automatically populate the floor plan based on the quotation and specific piece of furniture the customer has selected.
• The solution needs to be integrated into the HomesToLife website as a login member-only feature (accessible after logging in).
• The solution should be deployable via laptop.
• The solution should include a login and account function.
• The solution should enable customers to upload floor plans or photos of their homes.
• The solution should be fully integrated with the HomesToLife database of furniture (CAD-drawings can be made available).
• The solution should automatically configure possible layouts using generative AI, giving customers 3 different options for what the furniture would like inside their homes.
• The solution should also allow for manual configuration too so that our sales team can edit the configuration if needed.
• The solution should be integrated with our quotation system so automatic quotations can be provided.
• We are open for integrations with open-source LLMs for image generation, prompting and questioning.
• We are looking for integration with an AI assistant that can guide the customers by providing feedback (on material and style choices, discounts etc.) throughout the process.

• The solution should enable an increase to the overall number of quotations by about 20%.
• The solution should increase our conversion rates by at least 10% (from 80% currently, to 90%).

COST TARGET

Cost targets will be determined on a case-by-case basis. 

TIMEFRAME FOR DEVELOPMENT

Phase 1: POC development: Q1 2025

Phase 2: Commercial roll-out: to be determined on a case-by-case basis, target implementation by Q21 2025.

POTENTIAL MARKET / BUSINESS OPPORTUNITY

If the solution is successful, HomesToLife is willing to support a further roll-out across other stores. We have existing premises in China (300 stores) India (18 stores), Singapore (6 stores) as well as Taiwan, Philippines, Korea and Japan (4 stores).

Additionally, we are open for solution providers to deploy their solution in other non-competing market segments.

RESOURCES

OTHER CONSIDERATIONS

We are looking for SMEs and startups with solutions that can be implemented in a relatively short time frame (TRL of 5 and higher).

For Background IP (BIP), both parties will retain their respective IPs brought into the project. In the event of new Foreground IP (FIP) creation, HomesToLife is agreeable to FIP being retained by the solution provider.

BACKGROUND OF THE PROBLEM

Rémy Cointreau operates many Global Travel Retail (GTR) stores, notably in places like airports. In these competitive retail environments where many brands are represented, meeting retailers’ expectations for brand exposure, including brand space, visibility and presentation can be very challenging. Many brands are displayed on standard wall bays, gondola fixtures, endcaps or generic shelves with routine Point of Sales Materials (POSM). Moreover, each Retail Service Associate has limited time (on average only 3 minutes) to engage with customers, making it difficult to engage customers to ultimately increase customer conversion.

To address this, we are seeking innovative solutions to create novel retail experiences to enhance customer engagement and drive sales. We believe an immersive brand experience can be created through elements such as tasting, education and/or discovery of products without the presence of a Service Associate.

Many brands have tried different approaches, including scented notes, digital screens, self-discovery touch screens, QR codes for information, digital cocktail recipes. Whilst these tools are digital and sustainable, they lack real attraction and immersion.

Rémy Cointreau welcomes all solutions for new product interactions and enhanced customer experiences. The solution must be pragmatic and consider space and time constraints, as travellers have limited time to engage.

TECHNICAL REQUIREMENTS / PERFORMANCE CRITERIA

Technical Requirements:

• The solution should have the following basic features:
  1. The solution needs to fit into the gondola and wall bays to be used during activations.
  2. The solution needs to fit the following indicative dimensions (in case it is a physical piece):
     • Height: 320 mm
     • Width: 275 mm
     • Base length: 400 mm
• The solution cannot have a short expiry date (at least three months).
• The solution must be sustainable (sustainability is a key strategic focus of the group).
• The solution must be accessible to customers (without support from sales representatives).
• The solution must follow the standard approval requirements of airport retailers.
• The solution should integrate with different pre-existing loyalty programmes (these programmes are brand-specific)

Performance Requirements:

• We target the solution to increase our conversion rate (current average rate at 30%).
• We target the solution to increase the number of items purchased.
• We target the solution to monitor the engagement (e.g. how many customers are engaging with the activation).
  

COST TARGET

Cost targets will be determined on a case-by-case basis.

TIMEFRAME FOR DEVELOPMENT

Phase 1: POC development: Q1 2025.

Phase 2: Commercial roll-out: to be determined on a case-by-case basis, target implementation by Q2 2025.

POTENTIAL MARKET / BUSINESS OPPORTUNITY

If the solution is implemented successfully, Rémy Cointreau is willing to explore further roll-out and development in up to 30 stores and 50 activations. Additionally, we are looking to use the solution exclusively for the first year after implementation.

RESOURCES

• Up to S$30,000 to support the pilot development.
• Proposals will be evaluated on a case-by-case basis depending on the quality and feasibility of the proposed solutions.
• Disbursement of incentives will only be upon achievement of agreed-upon milestones.

• Mentorship and support for solution development.
• Access to relevant datasets, and pilot site(s).

• Up to S$20,000 grant support from EnterpriseSG.

OTHER CONSIDERATIONS

We are looking for SMEs and startups with solutions that can be implemented in a relatively short time frame (TRL of 5 and higher). For Background IP (BIP), both parties will retain their respective IPs brought into the project. In the event of new Foreground IP (FIP) creation, Rémy Cointreau is agreeable to FIP being retained by the solution provider.