Cordel Group — Railtech play with scalable potential

Cordel Group is a UK technology company that provides end-to-end data management for automated rail infrastructure monitoring, with a focus on creating safer, more efficient, sustainable railroads globally. The group’s proprietary platform processes and centralises fragmented data, enabling near real-time monitoring to identify risks proactively, supported by artificial intelligence (AI). This smart approach, which detects problems early to limit disruptions before they become costly issues, has been key to major wins like Network Rail, Amtrak and Australia Rail Track Corporation (ARTC). As a turnkey solution provider, Cordel provides lidar/front-facing video hardware to supply new data or replace legacy data. To process this data into actionable insights, the group provides sophisticated AI software, which is constantly evolving, with new capabilities key to further upselling. The initial product focus has been on clearances, ensuring train and tunnel/platform compatibility, an ongoing concern with varying freight dimensions and new rolling stock (trains). Other use cases are earlier in the commercialisation stage but could accelerate with market demand. For example, investment in unmanned geometry hardware related to a recent deal with Angel Trains accelerated following Network Rail’s planned £36m investment in such technologies.

Cordel employs a land and expand strategy, starting with trials to build trust that can lead to long-term, scalable contracts. Interoperable hardware and software create stickiness, elevating net retention as contracts grow via track miles or use cases. Covering 30,000 of 360,000 addressable miles indicates substantial room to grow, particularly by increasing the value per mile by deploying multiple use cases. The company’s highly customisable end-to-end solutions enable it to become a data management beachhead, a key strength versus competitors in the expansive yet fragmented smart rail market.

Cordel’s business model centres on converting trials to long-term managed services, transitioning clients from hardware installation and setup to long-term high-margin recurring service revenues. Contracts have three main elements that customers can utilise as required:

As the business has matured, management has won increasingly valuable contracts, with recent highlights being:

In H124, revenue grew 108% y-o-y to £2.0m with momentum across regions (US up 16x and UK up 58.5%). We expect momentum to continue in H2, forecasting 30.3% y-o-y growth in the half and a 54% increase for FY24, to £4.7m. Historically the stronger half, H2 should also benefit from a full-period contribution from Amtrak, as well as from contracts won at the end of H1. H1 gross margins declined due to Angel-related hardware investments, but we expect this to revert to over 70% for the full year on higher revenue and no-foreseeable low-margin hardware revenue in H2. Investments in future sales and delivery led to an EBITDA loss of £574k in H124, which we see continuing to end-FY24 before this investment drives operationally geared growth in FY25. For FY25, we forecast a 49% increase in revenue, to £7.0m, and a move to a small EBITDA profit. Growth levers include new customer wins from executing on its US-focused pipeline, upselling new use cases and cross-selling across departments within the business. Beyond FY25, maturing contracts and recurring revenue should enable steadier growth and higher margins, with management targeting £10m in recurring revenue, which seems achievable through existing customers and the pipeline.

In our view, Cordel’s current valuation does not reflect its long-term growth potential, overlooking opportunities to expand with tier one clients like Network Rail, Amtrak and ARTC. Key milestones that could catalyse a re-rating include demonstrating demand for additional use cases, upselling existing contracts and acquiring new clients, particularly in the US where there is a higher likelihood of securing seven-figure annual contracts. Despite faster forecast revenue growth than peers, Cordel trades at a discount on EV/sales multiples, signalling upside potential as the company grows and transitions to a higher mix of recurring DaaS revenues. On CY25e EV/EBITDA, an 11% premium to peers reflects early stage profitability. In the mid-term, delivering on management’s goal of £10m in recurring revenue on a diversified customer base with its current cost structure could provide the strongest validation of the group’s technology and strategy. We note that while the company is currently solely focused on exploiting the potential of the rail vertical, its software can be applied to any linear-recorded dataset, providing scope to expand into new verticals in the longer term.

Cordel’s growth and margins depend on expanding its US presence, reliant on the new US team to execute. Delivering on its land and expand strategy also relies on deploying new use cases beyond rail clearances, currently the sole use case. Lack of demand for other use cases in early pipeline stages could limit expansion and revenue growth. Diversifying beyond the top three clients mitigates risk, but still requires demonstrating additional use case viability, especially in the US market where Cordel is focused.

Cordel Group is a UK technology company focused on building safer, more efficient and sustainable railways across the globe. The company partners with major rail operators like Network Rail, Amtrak and ARTC to provide an end-to-end automated data management solution that optimises the monitoring of tracks and surrounding environments (together: rail corridors).

Rail networks may suffer from fragmented legacy data that is decentralised, largely unusable and not formatted specifically for the rail industry. At its core, Cordel’s proprietary platform processes, centralises and unlocks value from this data by enabling near real-time insights through AI. This not only reduces the costs and inefficiencies of manual track surveillance, but also proactively mitigates risks before they become expensive problems. Cordel’s technology also helps operators maintain compliance; for example, most of the US rail network is legally required to implement automated Positive Train Control (PTC) systems to ensure safe, human error-free travel. Cordel offers services such as automated asset mapping and change management to support these systems.

Once deployed, Cordel upsells contracts in two ways: 1) by covering more track miles, and 2) by adding new use cases that substantially expand the contract value. The group’s clearance solution has been key to securing contract wins by providing a quick and effective way to assess compatibility issues. Clearances examples include seeing if new rolling stock (trains) is compatible with existing tracks or if freight trains can safely pass through tunnels, under bridges and alongside other trains based on their varying loads. For Amtrak, having a near real-time clearances solution is also vital for its expansion into freight.

With its core platform and AI now developed, management believes the group can rapidly build applications for new use cases to meet emerging customer needs by reprocessing existing data in slightly different ways. While relatively straightforward, adding a new use case can potentially double the annual value of a contract, providing a powerful mechanism for operationally geared growth.

Cordel’s solution is sticky, embedding deeper within customers’ infrastructures with the more hardware it deploys and use cases it addresses. Currently, these are the other use cases the company seeks to address, with all of them earlier in the development pipeline than the clearances solution:

While these sound simple to manage, certain factors can create ongoing small changes to the shape and size of the rail infrastructure, creating long-term costs and risks if not addressed early. For example, extreme droughts can cause ground subsidence, rails can sink into the ground from soil erosion and hot/cold weather can change the shape of the metal in the track. To help mitigate these risks, rail operators need to regularly inspect infrastructure and track geometry, making adjustments and maintenance fixes when necessary. These issues are globally recognised, with Network Rail budgeting c £36m for unmanned geometry technologies in its next budget cycle starting 1 April 2024 (Control Period 7). This has motivated Cordel to accelerate its investment in geometry by extending its existing partnership with Angel Trains, a rolling stock provider, to equip its trains with new unmanned geometry units in H124, in line with its strategy of demand-driven development. The alternative to Cordel’s real-time solution is manual measurement, potentially leading to larger development work and creating potential risks if not managed properly.

Cordel can also deploy its light detection and ranging (lidar)/front-facing video hardware when networks do not have their own sensors or have incomplete datasets. Incomplete datasets are often highlighted through Cordel’s data processing capabilities, where for example it might highlight that there is a missing platform or signal in the existing, potentially stale data. The more hardware deployed, the greater the real-time comprehension of the network, underpinning another upsell opportunity.

In addition to working with tier one rail infrastructure organisations, Cordel partners with rolling stock and engineering firms to integrate its hardware and software, thereby broadening its potential reach, as highlighted by the Angel contract.

Founded in 2013 in Sydney, Australia, under the name Maestrano, the group originally specialised in master data management for small and medium-sized enterprises (SMEs), consolidating siloed data to provide actionable business intelligence through proprietary AI. In July 2019, the group acquired Airsight, a specialist in lidar technology suited to recording data in transport corridors, facilitating the group’s expansion into rail (Exhibit 2).

Airsight’s Corridor.ai product (Cordel.ai after 2020) was key to the acquisition, offering hardware and software to automate inspections, predict failures and improve asset management for transportation, especially rail. The group sought to drive adoption by integrating its own data management and application interface (API) capabilities, simplifying access to disparate data through a centralised cloud platform interoperable with third-party software.

Early momentum, including contract wins in Australia, the UK and the US, saw Maestrano pivot to solely focus on the growing rail opportunity. This strategic shift was reflected in its rebranding as Cordel Group in November 2021 (Exhibit 2). With this focus, Cordel has been phasing out other acquired products, including:

Cordel’s heritage of managing and consolidating large datasets has created a valuable core engine essential for leveraging vast amounts of unstructured lidar and video data. By solely focusing on rail, rather than a range of verticals, management has refined its core data processing capabilities, enabling faster development of tailored railway products that are essential for driving scalable growth. As at end-H124, Cordel had 35 employees based in Australia, the UK and the US, with offices in Australia and the UK.

Cordel designs solutions to seamlessly integrate with client systems, enabling continuous network monitoring and analysis, building on Cordel’s heritage in master data management. The company’s end-to-end solution is completed by the ability to provide proprietary lidar hardware to improve the reliability, recency and frequency of data collection. The company chooses lidar over methods such as intelligent video review or 3D scanning due to its superior measurement precision, especially in critical applications like clearances, where accuracy is paramount.

Cordel’s core engine addresses the challenge of making large, unstructured lidar datasets more accessible and easier to use. The software provides a user-friendly interface for clients to visualise data by performing advanced functions like point cloud creation – a 3D representation created using lidar measurements. Clients can also load and analyse external datasets like previous scans, offering a versatile platform, and can integrate this managed data across systems and platforms through an API. The group’s ability to standardise and validate lidar data ensures consistency and interoperability, enhancing usability across systems.

Cordel has a built a comprehensive stack from the ground up, incorporating hardware, data analysis and user interface (UI) design. In contrast to industry norms, the group’s open data access approach is unique, as data siloing is common in rail, and allows for greater data capture to be used to enhance the accuracy of its technology.

The base layer of Cordel’s technology is lidar and front-facing video hardware for mobile data capture on trains. Data is captured in two ways:

Historically, hardware adoption has been limited by cost and technology constraints, primarily relating to weather or age deterioration. Additionally, alternative lidar products have been designed for maintenance trains only, reducing data capture and potentially causing disruptions to in-service passenger trains.

Cordel’s Wave sensors leverage more durable, low-maintenance and miniature lidar from autonomous driving technologies to develop cost-effective wide-scale solutions. Benefits include wider deployment and increased data capture, enabling enhanced retrospective analysis for early issue identification, improving timeliness and accuracy across the network.

Finally, Cordel consolidates data from lidar, video and other sources into a unified database for comprehensive analysis. The combination of advanced hardware and managed data provides a powerful platform, which can be used to generate AI-powered real-time visual surveys of an entire rail network.

Given the significant data capture, management keeps raw data in ‘hot storage’ for six to 12 months for immediate needs, following which it is archived for longer-term retention based on client requirements. Archiving data reduces costs of storage but also provides clients with a ‘time machine’ view of the railway to assess conditions over time.

Recently, the group has been building a portfolio to include a wider range of sensors to enable more use cases. Acquired from third-party specialists, these may be more expensive than Cordel’s standard Wave sensors but will enable expansion into potentially high-growth new use cases, like unmanned geometry. To make contracts more attractive management may sell sensors at cost, affecting margins in the short term, with scope for rapid margin expansion following setup (see Strategy section below). Encouraging greater use of hardware across multiple vehicles captures more up-to-date, accurate data.

To balance maximising insights and minimising costs, Cordel selectively processes just 5–10% of collected data. Processing focuses on the highest-quality data captured under optimal conditions, as well as the most relevant information specified by the client. For example, in Australia and the US, less populated rural areas may require less frequent monitoring than busy urban zones. This selective approach optimises effectiveness, efficiency and costs at scale.

The company uses proprietary software that can remotely access and process data. This software leverages 4G wireless connectivity and breaks the continuous incoming data into smaller chunks, which can be separately and more easily processed in near real time.

Cloud integration is essential for securely storing the vast indexed data and ensuring accessibility, with Cordel’s system handling upwards of 110 gigabytes (GB) daily for customers. Condensing this big data is key for generating actionable insights. For example, Cordel was able to refine 50GB of Amtrak lidar data into 10 megabytes (MB) of clearance profiles, containing only the essential information.

Systematic indexing by time and location simplifies retrieving the most relevant data segments. Together, these capabilities allow Cordel to handle large datasets and deliver actionable insights efficiently.

This second layer is the platform on which all its contracts are built. For example, in 2021 Cordel won a competitive bid to replace the UK’s legacy National Gauging Database with a more resilient, modern system – Cordel’s Railway Gauging Data Solution (RGDS). Following an 18-month setup period, Cordel now owns and manages the gauging database through RGDS, providing consistent, high-quality data that enables National Rail decision-makers to make informed choices within hours instead of months as with the previous dataset.

Leveraging AI, Cordel can transform data into a comprehensive spatial understanding of railway environments. Through API, organisations can access this information on leading third-party enterprise asset management (EAM) and geographic information systems (GIS) platforms.

Cordel’s proprietary technology produces real-time infrastructure surveys, enabling change detection and predictive maintenance. These surveys are best illustrated through points clouds – detailed 3D digital rail corridor representations with AI categorisation providing geometric data on object surfaces.

Addressing specific use cases is driven by AI. For clearances, Cordel partners with D/Gauge, an AI clearance specialist. D/Gauge’s Rift product utilises Cordel’s full network lidar capture and automated processing stack to drive applications such as:

Although the group has partnered with D/Gauge for clearances given D/Gauge’s expertise, the group believes it has the internal capabilities to expand into new use cases without a partner, underpinning greater margin potential. Roadmap priorities include enhancing existing applications to provide comprehensive solutions at scale, with current developments including:

At its H124 results, Cordel confirmed it had taken its first commercial strides into new use cases following its expanded partnership with Angel Trains, to equip rolling stock with unmanned geometry hardware (using sensors to measure track alignments, gradients, profiles, etc).

Another key product in the pipeline is an AI-as-a-service offering, which will enable clients to upload their own lidar data for processing and analysis using Cordel’s AI to classify point cloud elements. This lowers barriers for clients challenged with deploying new rail hardware, letting them validate the effectiveness of Cordel’s platform on existing data. By showcasing AI abilities on client data, management aims to build trust and provide an easy entry point to demonstrate value. Releasing this AI-as-a-service product is a key short-term milestone to expand Cordel’s client base.

As a relatively new rail industry entrant, Cordel is focused on expanding the deployment of its clearances solution among existing and new customers to establish market presence, building trust and showing the effectiveness of its technology through proof-of-concept contracts. Significant scope remains to extend hardware across rolling stock and widen network coverage with existing clients. For new clients, management is focused on its core Australia, UK and US markets, with channel partnerships broadening geographic reach to new regions. Initial clearance deals could enable an effective land and expand approach, where Cordel can broaden mile coverage or cross-sell maturing pipeline offerings. We note that once embedded in an organisation, Cordel’s solution is sticky given the costs and effort to replace hardware and remove integrated software, particularly if the group addresses multiple use cases.

While diversifying into other verticals is part of the long-term vision, management expects the immediate focus to remain on rail, avoiding overextension across clients, capabilities and time zones. Initial steps into related domains such as Australian level crossing analysis, where rail intersects with road, reflects a cautious approach to expansion.

Cordel employs direct and indirect sales models to balance focused engagement with broad reach. The direct approach focuses on established US, UK and Australian markets where Cordel seeks to strengthen its influence. While direct engagement is preferred, to avoid margin sharing, indirect models can provide access to new geographies and a broader customer base.

Cordel typically partners with track maintenance and construction engineering companies, like Holland LP or Ricardo, as well as rolling stock providers, like Angel Trains. By reselling Cordel’s hardware and software, the partners enhance their own offerings. Recent examples include:

In addition to technology, Cordel and D/Gauge also support each other with referrals. In January 2023, D/Gauge was acquired by TÜV Rheinland, a leading German transport inspector, opening new opportunities for Cordel through TUV’s extensive European market reach.

Cordel focuses on established rail networks where issues and needs are clearly defined, prioritising straightforward engagement over involvement in complex new projects like High Speed 2 (HS2) in the UK.

Further penetrating the US market is management’s primary goal. There is potential to not only further engage with Amtrak’s 21,000-mile network, but also with the seven other major US rail networks, which cover an additional 145,000 miles, as well as shorter tier two lines (see the Market section below). These organisations typically have substantially larger budgets and more autonomy than other regions, providing financial leverage alongside regulation like PTC to drive demand. Additionally, Amtrak’s aim to expand into freight, which necessitates more comprehensive clearance data due to cargo variability versus passenger trains, catalysed adoption of Cordel’s clearances solution. This strong mix positions the US as an attractive growth opportunity beyond Amtrak’s network alone.

Europe’s established rail networks, budgets and infrastructure challenges make it the next priority, which could be accelerated through Cordel’s partnership with TÜV through D/Gauge. Management also sees potential in the Americas given networks may share personnel and track between North and South America. Asia would likely require local partnerships for entry due to unique challenges.

Management believes conducting business successfully in the UK enhances its international credibility. The UK’s railway network, overseen but not directly owned by Network Rail, highlights the need to navigate complex public and private sector dynamics to effectively implement technology and services. The UK budget encompasses various costs across five regions, while private companies like Angel Trains autonomously decide on investments based on resale potential.

While specific UK standards may not directly apply abroad, the experience gained is valuable when expanding to other complex markets requiring nuanced public-private coordination, like Germany, France, Spain and Italy.

Cordel uses a land and expand strategy to gradually broaden engagements, often starting with proof-of-concept trials to demonstrate value and build trust. The following are key examples of successful execution of this strategy:

As previously discussed, Cordel has the ability to offer various services such as clearances, vegetation management and ballast profiling on the same mile of track, which enhances the potential for increased revenue per mile.

With investments in its technology largely complete, the group is focusing on sales and delivery, recently hiring:

These hires should help Cordel to win new clients and deliver on contract expansions. Consequently we forecast revenue acceleration in FY25, leading to a move to operating profitability.

Over time, we see a smoothing in Cordel’s revenue generation as its client roster grows and contracts mature, underpinned by expanding DaaS revenue following lumpier initial setup fees. This shift is consistent across clients and contracts as, initially, higher costs are incurred for integration and database development, resulting in lower margins.

The contracts then transition to steady recurring payments for continuous data analysis, creating high-margin streams. Cordel aims to replicate this shift quickly across clients, pursuing a ‘hockey stick’ growth pattern – an initial investment followed by high-margin recurring revenue. Below, we highlight the gross margin progression for the various stages:

The Amtrak contract provides a clear example of this transition. The 6.5-year deal involved higher initial costs for the 18-month rollout, generating half of the contract revenue of this period. The subsequent five-year period shifts to consistent annual DaaS payments of c US$700,000 for clearances analysis. Additional use cases can further increase value over time, without the need to install additional hardware.

As the focus is on enabling high-margin recurring monitoring revenue, not immediate hardware profits, management may bundle hardware, even at low margins or at cost, as a strategic investment in future data income. Additionally, as Cordel wins more contracts, management believes it will learn how to deploy and customise solutions faster, shortening the implementation phase and accelerating the transition to service revenue.

Globally, infrastructure digitalisation and spatial computing trends present significant market opportunities as sensor proliferation expands collectible data volumes. However, most edge-stored data is siloed, meaning it is isolated and restricted to individual systems or applications, offering potential for specialists, like Cordel, to centralise and derive insights across use cases.

Rail’s economic and sustainable credentials are driving substantial government funding and private investment in automation, catalysing rail infrastructure technology advancement. This confluence of factors could drive a near tripling of the US$100bn (as of 2021) smart transportation market, as illustrated in Exhibit 5.

At end-FY23, Cordel covered 30,000 miles, an 8% share of the 360,000-mile addressable market in serviceable nations. Expanding to fully nationalised countries would increase the opportunity to 850,000 miles.

As previously discussed, Cordel’s strategy centres on growth in its core markets of the US, the UK and Australia. Exhibit 5 illustrates the addressable market potential through expanding the share of miles covered or cross-selling additional use cases, underpinned by substantial funding and government initiatives. At its H124 results, the group indicated it is in late-stage pipeline discussions with many of the key target customers listed below, especially tier one customers, and two US railroads. As shown below, US private railroads invest c US$23bn annually to modernise their freight networks alone, and so deploying Cordel’s solution requires a relatively minor investment for each railroad yet could generate up to US$1m per year in service revenue for Cordel, assuming contract sizes similar to Amtrak.

The smart rail market is expansive yet fragmented, ranging from large consultancies to hardware/software vendors that may lack rail focus or leverage different technologies/use cases. In Cordel's core regions, mandates may exist to engage SMEs, excluding larger players who may solely pursue bigger contracts. The fragmentation enables Cordel to selectively target projects aligning with its focused expertise in AI-powered end-to-end rail infrastructure analytics, including lidar deployment, data management and UIs. Additionally, management believes that its smaller size and rail focus enable it to deploy its technology faster and provide greater customisation versus peers.

Cordel’s selective focus, tailored solutions and tier one relationships distinguish it from both broad consultancies and specialised vendors, enabling a targeted competitive strategy. Competitors include:

Cordel’s board comprises CEO John Davis, Non-executive Chairman Ian Buddery and independent Non-executive Directors Jonathan Macleod and Nicholas McInnes.

John was appointed CEO in March 2023 after joining the board in 2018 as a non-executive director. He has over 20 years’ experience with banks and small businesses, previously serving as marketing and product director for Barclays Business. He has also founded and led several London-based fintech startups.

Chairman Ian Buddery provides extensive public company expertise from past roles leading eServGlobal and other ventures. He also has experience with IPOs, acquisitions and trade sales. Jonathan Macleod is a chartered accountant and financial advisor and Nicholas McInnes is a former British diplomat focused on trade and investment.

The management team consists of the CEO, CTO Aaron Hoye, CFO Thouraya Walker, CRO Mike Turner and GM Product and Delivery Paul Mullins.

Cordel’s H124 results show that momentum continues to build across all geographies, driven by contract extensions and new wins. For H224, new contracts with Mexico and HS1 announced late in H1 will fully contribute to revenue. Further growth will be driven in two ways: 1) converting pipeline targets into customer wins with the full material benefit in FY25, and 2) upselling existing contracts. With data processing complete among the current customer base, management believes it can more easily upsell new use cases or cross-sell to other departments within a network.

Management is primarily targeting the US for growth given the appetite for longer, more substantial contracts due to the autonomy and significant funding each network receives. A multi-million dollar contract may be transformational for Cordel, yet a fraction of a tier one network’s balance sheet.

In the mid-term, Cordel believes it can achieve a DaaS revenue base of over £10m per annum. This would require replicating three to four more contracts the size of Amtrak, most likely in the US, plus around seven more at £500k – in line with most existing customers. According to management, this is achievable from the group’s existing pipeline. The company believes that it can now scale, at least to end-FY25, on the existing cost base, driving a swing to operating break-even in FY25.

Cordel's business model centres on converting trials into long-term managed service contracts, transitioning clients from upfront hardware capital expenditure to ongoing DaaS operating expenditure that generates high-margin recurring revenues. Management believes accumulating experience and expertise over time can help reduce deployment latency and costs, shortening this transition period. Contract expansions, either through additional miles covered or new use cases, may require additional hardware sales to enable new capabilities or expand network coverage.

Revenue recognition is client dependent. Hardware revenue is always recognised upfront, then the setup period is determined internally based on customisation and implementation scale. After setup, DaaS revenue is recognised on a straight-line basis for the remainder of the contract term.

Payment terms are customised but are typically monthly or quarterly. Cordel maintains strong cash collection and no bad debts, reflecting its high-quality customer base, but may see working capital swings if contracts are signed late in the year.

Revenue increased by 108% y-o-y in reported currency in H124 and 111% at constant currency to £2.0m, with momentum building across all key geographies:

On a half-on-half basis, revenue was down 6.7%, reflecting seasonal factors and client budget cycles. As Exhibit 8 shows, H2 has historically been the stronger half for Cordel, giving us confidence in our forecasts. The more modest half-on-half increase to our H2 forecast reflects recurring revenue from existing customers, with less reliance on new customer wins.

New contract wins resulted in more hardware versus software and services revenue, decreasing gross margin by 18.8pp y-o-y to 53%. As contracts mature, higher-margin recurring revenue should become more predominant, with management expecting gross margin to return to over 70% by end-FY24. Investments in sales and delivery slowed margin growth on higher revenue, with the group reporting an EBITDA loss of £574k in H124 (H123: loss of £789k). With investments complete, this positions the group for operationally geared growth.

In H223, Cordel completed a £1.7m capital raise, funding investments in sales and delivery and closed the year with gross/net cash of £1.28m. Cash reduced by £92k in H124 to £1.19m, with a large working capital inflow of £671k substantially offsetting capex of £115k, lease payments of £20k, exchange losses of £49k and the EBITDA loss.

Our FY24 forecasts indicate continued positive momentum for the rest of the year, with year-on-year growth of 54% to £4.7m (H224e forecast growth of 30.3% y-o-y). We believe this will be driven by a full half-year contribution from Mexico and the UK, as well as continued Amtrak revenue. We believe the company may also deliver new smaller trial contracts across railway networks and rolling stock providers, although these will be more material to FY25 revenue. In the UK, growth may be affected by the transition from CP6 to CP7 (1 April) as contract talks are put on hold. We forecast a slight revenue decline in Australia, reflecting discontinued Airsight operations, partially offset by the NTRO research project.

Unlike its contract with Angel Trains (which has lower gross margins relating to the deployment of the new unmanned geometry hardware), management expects H2 revenue to be mostly software setup and services related only, driving a move back to over 70% gross margins for the full year on higher H2 revenue.

On operating expenses, we forecast 39% y-o-y admin expense growth to £4.2m reflecting additional hires, resulting in an EBITDA loss of £515k for FY24. We have reflected the new lease taken out for premises in Australia at the start of CY24. With no debt, interest payments on new leases drive our financial expenses assumptions.

Our free cash flow forecast is affected by a £95k capex increase, reflecting higher H1 spend and lower FY23 levels following Nextcore flight equipment disposal. The higher free cash outflow reduces year-end net cash to £803k before leases.

Cordel has several levers to drive scalable growth in FY25, including contract expansions and a full year contribution from customers won in H224. We reflect this potential with 49% y-o-y revenue growth to £7.0m, with a gross margin of 71% from a steady improvement in the revenue mix. We expect the group to swing to EBITDA profitability in the year on operating leverage, now investments in R&D, sales and delivery are mostly complete. After factoring in depreciation on the new lease, we forecast an operating margin of 0.6%. R&D tax credits in Australia and loss carry forwards in the US and UK should offset tax in FY25.

Higher operating cash flow could drive positive free cash flow. We note that the business is historically not capital intensive with minimal foreseeable development costs, which are all expensed. This should result in an increase in end-FY25e net cash to £843k.

Beyond FY25, we see potential for steadier revenue as existing contracts mature and DaaS sales grow as a percentage of total revenue, also driving margin expansion. With hardware and software integrated into several major rail networks globally, this should improve customer retention while providing case studies to attract new clients and diversify the customer base. We believe management’s mid-term target of £10m recurring revenue is achievable, requiring a small increase in Amtrak style contracts and c 10 customers paying c £500k annually – in line with current levels.

We do not foresee the need for capital raises to fund organic growth. However, a large, transformational project requiring substantial working capital or M&A to vertically integrate, such as acquiring a hardware provider, may necessitate fund-raising.

As discussed, Cordel has successfully transitioned to solely focus on the rail industry, completing the necessary investments in its technology stack. The group has successfully won several proof-of-concept trials and long-term contracts with major tier one players and is now in a position to scale profitably. Our valuation analysis shows that Cordel’s current rating does not reflect the current long-term growth prospects, including:

Key milestones needed to catalyse a re-rating include demonstrating demand for additional use cases, expanding contracts, and acquiring new customers, particular in the US.

We note that while the company is currently solely focused on exploiting the potential of the rail vertical, its software can be applied to any linear-recorded dataset, providing scope to expand into new verticals in the longer term.

We value Cordel against small-cap rail technology, data management and spatial data peers creating digital twin solutions, given there are no direct competitors at Cordel’s size. We also compare it to large data management companies providing intelligent rail offerings, which have greater business model similarity.

We value Cordel on EV multiples. The EBITDA margins across its peers demonstrate the group’s potential, where we believe a 17% margin (the mean of the small-cap peers in CY23) is achievable in the mid-term. Given the different year ends of all the peers, we compare on a calendar year basis assuming a 40/60 fiscal year split for Cordel based on historical seasonality.

On EV/sales, Cordel trades at 1.3x CY24e and 0.9x in CY25e, with the widening discount from 42% to 58% reflecting its faster forecast growth than peers. We believe the CY25e EV/EBITDA of 11.1x and the premium of 11% to the small-cap peers reflects the early-stage profitability of the company.

The increased discount when including large caps highlights Cordel's earlier stage, less established model and smaller size. This signals upside potential as Cordel grows its presence and executes its land and expand strategy with tier one partners.

Our reverse 10-year DCF uses an 11% WACC, applying a risk premium to reflect the company’s size and early stage, and a 2% terminal growth rate. To justify Cordel's 4.25p share price based on forecasts to FY25, the model requires EBITDA margin expansion to 11.6% from 3.1% in FY25. It also requires revenue growth to fall from 49% in FY25 to a 13.5% CAGR from FY26–2033.

In our view, Cordel’s valuation overlooks current contract momentum, particularly with existing contracts offering potential for operationally geared growth. Management may opt to invest in sales and delivery to sustain revenue momentum or focus on margin expansion by upselling existing contracts needing minimal investment. A blended approach is also possible. Our sensitivity analysis highlights upside to the current rating under either approach, as highlighted by the dark grey cells in Exhibit 11.