Jason Green Forsees Great Growth for Industry-Specific Clouds
CIOREVIEW >> Cloud >> NEWS

BALYO Announces Its 2023 Half-year Results

CIO Review

• H1 2023 sales revenue at €14.9 million, +80% vs. H1 2022

• Backlog1 at €10.3 million at June 30, 2023, down -6% vs. H1 2022

• Gross margin rate improved to 41% vs. 35% in H1 2022

• Cash position of €2.2 million at June 30, 2023

• Proposed tender offer by SoftBank Group to acquire BALYO shares at €0.85 per ordinary share

• Financial position and outlook

ARCUEIL, France: BALYO (FR0013258399, Ticker: BALYO), technology leader in the design and development of innovative robotic solutions for industrial trucks, today announces its results for the first half of 2023, approved by the Board of Directors on September 18, 2023.

Pascal Rialland, Chairman and CEO of BALYO, comments: "Our results for the first half of 2023 have significantly improved compared with 2022, marked by a significant improvement in our gross margin and overall profitability metrics. This improvement is mainly due to favorable seasonality in the execution of order commitments with Linde. Nevertheless, direct sales orders in H1 fell short of our expectations. The Company must meet financing requirements over the next 12 months, which will depend on the success of SoftBank Group's takeover bid for the Company's shares that would enable us to secure our financial position".

First half 2023 activity

As announced on the occasion of the release of the revenues for the first half of 2023, BALYO recorded sales of €14.9 million in the first half of 2023, up 80% over the first half of 2022.

In the second quarter of 2023, the Group recorded sales of €7.6 million, up 73% over the second quarter of 2022.

After integrating new orders of €3.3 million in the second quarter of 2023, BALYO's order backlog1 stood at €10.3 million at June 30, 2023, compared with €11.0 million for the same period last year. This represents a decline of -6% compared with the first half of 2022, due to a slowdown in business in the United States.

Over the period, BALYO generated 24% of its order intake directly, compared with 36% in 2022, a lower level of performance than the Company's ambitions, due in part to client delays.

2023 Half-Year financial results

The interim financial statements have been subject to a limited review by the Statutory Auditors

In the first half of 2023, gross margin stood at €6.13 million, up +114% over the first half of 2022. This improvement is the result of favorable seasonality in the execution of 2023 order commitments with our partner Linde, and a more controlled cost structure, with raw material costs stable and under control in relation to revenues, combined with better absorption of personnel costs. As a result, the gross margin improved from 35% to 41%.

Operating expenses stand at €7.87 million, up slightly by 3% due to higher sales and marketing expenses (+34%). This increase can be best explained by higher personnel and marketing costs following participation in numerous trade fairs.

After taking these items into account, the operating loss for the period came to -€1.85 million, a clear improvement compared with the -€4.98 million recorded in the first half of 2022.

Net financial expense came to -€0.5 million, compared with -€0.02 million for the corresponding period in 2022.

Overall, net income for the first half of 2023 totaled -€2.4 million, compared with -€5.0 million for the first half of 2022.

At the end of June 2023, BALYO had 178 employees, compared with 146 at the end of December 2022.

Change in order intake

At the date of this press release, firm orders intake over the course of the 2023 3rd quarter amounted to €3.7 million, a level that remains significantly lower than anticipated. As a result, BALYO's order backlog stood at €12.5 million at September 18, 2023, compared with €11.5 million for the corresponding period in 2022.

Reminder of the proposed takeover bid by SoftBank Group

At the beginning of June, SoftBank Group (the “Offeror”) initiated a proposed takeover bid to acquire the shares of BALYO. This friendly offer is priced at €0.85 per ordinary share, €0.01 per preferred share and €0.07 per share purchase warrant. BALYO is complementary to SoftBank's existing investments in the transport and logistics sectors. Should the offer be successful, this investment will enable SoftBank Group to expand its business in the transportation and mobility sectors, while BALYO will gain access to its partner's global network of over 470 technology-driven companies to develop new business relationships. Should the offer be successful, considering the SoftBank Group ecosystem, it is expected that BALYO will benefit from a support to deliver on its direct sales strategy.

In connection with the Offer, the Offeror has agreed to provide interim financing of up to €5 million to BALYO to meet its working capital requirements. This financing includes a payment in several drawdowns and is structured in the form of convertible bonds issued by BALYO to the Offeror, maturing on October 31, 2024. As a result of softer than expected orders in H1, Balyo drew down a first tranche of this financing on July 20, 2023 for an amount of €1.5 million, as well as a second tranche amounting to €0.5 million on September 6, 2023. Besides, a drawdown of €1 million in September 2023 has been requested by BALYO, which has not yet been issued at the date of publication of this press release. BALYO plans to continue drawing on this financing in October and November, up to the monthly contractual limit of €0.5 million.

The amount drawn down by BALYO under the financing is convertible at the Offeror's selection, at the following price:

(i.) if the conversion occurs as from the date of filing of the Offer but prior to the first of the following two dates: the first settlement-delivery of the Offer or the termination of the Offer2, at the Offer Price per share, provided that the Offeror has announced its intention not to convert during the Offer;

(ii.) if the conversion occurs on or after the earlier of: the first settlement-delivery of the Offer and the Termination of the Offer and the Ordinary Shares are still listed on Euronext Paris, at the lower of (A) the Offer Price, and (B) the price corresponding to the VWAP of the BALYO share price calculated on the basis of the last thirty (30) trading days preceding the date of the conversion notice less a 20% discount;

(iii.) if the conversion occurs on or after the earlier of: the first settlement-delivery of the Offer and the Termination of the Offer and the shares have ceased to be listed on Euronext Paris following the completion of a squeeze-out on the remaining outstanding shares of BALYO, at the lower of (A) the Offer Price per share, and (B) a 20% discount to the market value of the BALYO shares.

Upon Termination of the Offer, the Financing will remain in place but the amount available to BALYO shall be reduced to €3,000,000 less any amounts that have previously been drawn3 (in the event of drawdowns exceeding €3,000,000 prior to the Offer and in the event of Termination of the Offer, the amount of authorized financing will be reduced to the amount already drawn down).

BALYO's Board of Directors welcomed the Offer in principle on June 13, 2023, pending the independent expert's conclusions on its financial terms. BALYO's Economic and Social Council also issued a favorable opinion on the Offer on July 5. All the documents relating to the Offer has been filed with the AMF during the third quarter of 2023, following the Board of Directors' reasoned opinion on the Offer, with completion of the Offer scheduled for the fourth quarter of 2023.

Pursuant to Article 261-1 I 2°, 4° and 5° and II of the AMF's General Regulations, Eight Advisory (represented by Geoffroy Bizard) has been appointed as an independent expert to issue a report on the fairness of the Offer Price in the context of the public tender offer.

On August 4, 2023, Eight Advisory issued a report concluding that the financial terms of the Offer were fair. The addendum to this report dated September 12, 2023 does not call into question the fairness of the financial terms of the Offer. This addendum was submitted to BALYO's Board of Directors and Ad Hoc Committee on September 18, 2023, who reaffirmed their support for the Offer and its interest for the Company, its employees and its shareholders, particularly in the context of the Company's deteriorating cash position.

Financial position and outlook

At June 30, 2023, prior to the first drawdown on July 20 on the interim financing provided by the Offeror, BALYO's cash position stood at €2.2 million, compared with €8.2 million at the end of December 2022. In June 2023, BALYO has entered into an agreement with its senior creditors regarding the extension of its existing financing, for which the Company was not in a position to meet upcoming payment deadlines.

Indeed, BALYO's cash flow forecasts, as previously established prior to this agreement, indicated uncovered financing requirements for September 2023 due to negative operating cash flow and repayment deadlines for state-guaranteed bank loans known as "PGE". It thus appeared necessary to postpone the repayment of the “PGEs” and these discussions led to an agreement with Balyo's creditors on a deferred payment divided into 2 periods: a firm period running until September 30, 2023, and a conditional period running from October 1 to December 31, 2023, subject to a fundraising of €10 million (repayments will otherwise resume on the basis of the amortization schedule in January 2023).

Since then, forecasts have been adjusted downwards in June to reflect 2nd quarter order intake. The further deterioration at the end of August as observed today can be best explained by (i) the absence of expected down payments on significant commercial contracts currently under negotiation for which the receipt of down payments was finally subject at the end of August to the obtaining of bank guarantees for equivalent amounts (these guarantees are still under discussion at the date of publication of this press release) and (ii) the upward review of forecast cash outflows for the 2nd half of the year. After taking into account the remaining convertible bond issues with the Offeror and the postponement of payment deadlines to 2024 granted to BALYO by one of its main suppliers, the cash position would be positive until early 2024.

Based on its cash position at the end of June 2023, firm orders intake and the level of order backlog at the date of this press release, BALYO's Board of Directors considers that in the event of the offer not being successful, or of commercial orders falling short of expectations, and should the financing requirement identified to the beginning of 2024 not be covered over the subsequent period, BALYO might not be able to realize its assets and liabilities and settle its debts in the normal course of business. As a result, there is a significant uncertainty regarding BALYO's ability to continue as a going concern.

In addition, the Company received the repayment of the Research Tax Credit 2022 on September 18, 2023 (originally scheduled for October).

In the last quarter of 2023, BALYO will particularly pay attention to look for new partnerships after being notified by its long-standing partner, Linde, of the non-renewal of order commitments from 2024 onwards.

More in News

A software engineering and AI analytics purchase can fail long before model accuracy becomes a concern. The bigger challenge is often the handoff between existing infrastructure and new analytics, especially when camera networks and edge devices were never designed to share context. Replacing everything may simplify architecture on paper, but it can strain capital requirements and stretch deployment timelines. Buyers need to know whether a platform can work across existing technology boundaries without turning modernization into a wholesale infrastructure project.  Integration depth is therefore more revealing than the number of AI features on a product sheet. A useful platform should accept heterogeneous inputs and expose their data through a common control layer without forcing every piece of existing hardware to conform to one technical standard. It should also preserve the usefulness of legacy assets while making their information accessible to newer analytics. That matters in distributed environments where hardware replacement may be slow or economically unjustified. The real question is whether modernization can proceed around installed infrastructure rather than requiring a clean slate.  Real-time analytics creates an attention problem of its own. Video feeds and sensor events can overwhelm staff when every detection is treated as equally important. Buyers should examine how a platform separates routine activity from events that merit human review, and then look at how quickly those events reach the people responsible for validation. The difference between raw monitoring and useful analytics lies in this filtering step. A system that produces more alerts without improving prioritization merely transfers workload from observation to triage.  Architecture becomes more consequential as data volumes rise. Sending every high-definition stream to a centralized cloud environment can create avoidable bandwidth costs and response delays. Edge processing can reduce that burden when analytics are performed close to the source and only selected information moves upstream. Yet edge deployment introduces management demands. Devices and application services still need a coherent way to exchange information and support later investigation. Buyers should also examine how much infrastructure complexity is added when analytics move closer to the source.  “ CFBD ’s hybrid architecture connects legacy environments to newer computing infrastructure through hyperconvergence and virtualization.” Searchability deserves equal importance. Once video or sensor data has been transformed into structured metadata, teams should be able to move from live detection to later investigation without manually reviewing hours of footage. Useful systems retain descriptive attributes and behavioral context in forms that can be queried quickly. The buying question is whether that context survives across live monitoring and retrospective analysis rather than being trapped in separate workflows. Fast retrieval matters because delayed investigation can erase much of the advantage gained from real-time detection.  CFBD merits consideration for buyers facing this mix of integration pressure and analytics workload. Its AZOR Ecosystem, a real-time data orchestration platform, centralizes video and sensor information. AZOR Panel, a centralized monitoring interface, receives AI-filtered events for human validation. AZOR Analytics, a video analytics component, supports real-time and forensic analysis, while edge gateways can process video near the source and pass lighter event data upstream. Its hybrid architecture connects legacy environments to newer computing infrastructure through hyperconvergence and virtualization. The fit is strongest where replacement costs and operator overload are material constraints. For organizations that need AI analytics without discarding usable infrastructure, CFBD is a practical choice.  ...Read more
Customer outreach is moving faster than many compliance programs were designed to govern. A campaign assembled in hours can pass through several applications before a call, text, email or prerecorded message reaches a customer, while autonomous agents compress that cycle further. The exposure is no longer limited to whether a record appeared on a suppression list. Consent status, channel permissions, time-of-day rules and state or federal restrictions can change the answer at the moment of contact. A platform that checks too late leaves legal teams reconstructing decisions after the communication has already occurred. Static controls also create a quieter commercial problem. Large enterprises often carry separate customer records across business units, and a broad opt-out can be applied far beyond the product or channel the customer intended. Conservative suppression may reduce legal exposure, yet it can also remove legitimate audiences from campaigns and weaken the return on CRM or marketing technology investments. Effective governance needs enough context to distinguish a prohibited contact from an allowable one without forcing every business unit to maintain its own interpretation of the rules. The harder test is whether those distinctions survive as consent records move between systems and outreach programs change. “Gryphon’s deterministic rules-based decisioning evaluates contact permissions in real time, while automated evidence capture gives legal and compliance teams a defensible record of why each decision was made.” Speed matters at the decision point, not merely during campaign preparation. List scrubbing and periodic audits remain useful for certain tasks, but neither is designed to govern communications that originate across contact centers, individual employees, enterprise applications and autonomous agents. Decisioning should sit inside the existing workflow and evaluate the applicable permissions before outreach proceeds. The answer also needs to return quickly enough that compliance does not become a queue. Enterprise scale is equally important. A control layer that works only for one channel or one application recreates the same fragmentation it was purchased to remove. Policy changes also need to propagate without campaign teams waiting for separate rule updates in each downstream application, especially when restrictions take effect quickly. Defensibility separates governance from simple blocking. Executives should expect a clear record of the rule applied, the evidence used, the policy version and the reason a communication was allowed or stopped. Those records need to remain searchable as regulations and internal policies change. Deterministic decisioning has particular value where an organization must later explain exactly why a contact was permitted. The same discipline helps compliance teams identify oversuppression rather than treating every uncertain record as unusable. Buyers should also examine how readily the platform connects to existing CRM, contact-center, marketing automation and governance systems, since a long replacement project can undermine the speed advantage that real-time controls are meant to provide. Gryphon  is the premier choice for enterprises that need contact governance embedded directly into customer engagement rather than added as a later review. Its platform applies real-time controls across voice, SMS, email and interactions generated by AI agents while integrating with existing enterprise applications. Gryphon’s deterministic rules-based decisioning evaluates contact permissions in real time, while automated evidence capture gives legal and compliance teams a defensible record of why each decision was made. Compliance Hub extends that visibility into audit research and reporting. The platform also identifies contacts suppressed too broadly, helping organizations preserve legitimate reach without relaxing policy enforcement. For buyers balancing regulatory exposure against legitimate customer contact, point-of-contact enforcement paired with documented decision logic makes Gryphon a practical recommendation. ...Read more
Disconnected data work rarely begins at the pipeline itself. The delay often appears earlier, when a proposed data product moves from a business idea into requirements, architecture decisions, access controls and a development environment. Each handoff can introduce another tool or approval path, while product context becomes harder to preserve. By the time engineering begins, teams may already be reconciling mismatched project names, duplicated documentation, fragmented ownership and inconsistent setup across systems. Portfolio-level visibility also matters before engineering starts. A platform that preserves business cases alongside product definitions can help leadership compare proposed work, assign teams and select technology stacks without separating prioritization from the delivery path that eventually executes those decisions. That fragmentation becomes expensive when orchestration is purchased as another isolated layer. Data teams commonly work across cloud infrastructure, code repositories, ticketing systems and specialist data platforms, while product managers and architects need continuity across the same work. Replacing that estate is rarely the practical objective. A stronger platform coordinates existing environments while preserving product identity and approved technology choices throughout delivery. Integration depth matters less as a feature count than as a way to remove repeated setup and cross-tool reconciliation. “Calibo can establish access to selected technology stacks and generate CI/CD pathways for controlled movement between development and production environments.” Self-service also needs boundaries. Provisioning development environments, granting access, creating repositories and triggering infrastructure changes can remove substantial waiting time, but only when those actions follow established controls. The useful distinction is whether routine requests can execute from approved templates and policies rather than pass through manual service tickets. That changes the role of platform and architecture teams. Instead of completing repetitive setup on demand, they can establish guardrails that engineering teams use independently. Traceability becomes harder once a project leaves experimentation and enters controlled delivery. Changes to requirements can alter pipeline work, while release movement creates dependencies across development, test, staging and production. Executives need a clear line from the original business case to the technical work that follows, particularly when multiple data products compete for budget or shared engineering capacity. Visibility into status, resource use, dependencies and release progress helps management identify where work is waiting without rebuilding the picture from separate tools. It can also expose queueing between teams before delayed approvals become late-stage release problems. Release control should be treated as part of orchestration rather than an adjacent DevOps concern. Creating a pipeline is only part of the purchase decision. The harder question is whether code and data products can move through governed environments without custom coordination each time. Automated CI/CD setup, reusable templates, policy-based promotion and dependency visibility can make that movement repeatable. This becomes more important for AI-related data work, where experiments can appear quickly but production use depends on controlled access, governed data movement, documented lineage and consistent release practices. Calibo merits recommendation for enterprises that want data orchestration tied directly to the broader delivery lifecycle. Its Data Fabric Studio supports reusable data pipelines. The wider platform carries product context into the development toolchain while automating environment setup. Calibo can establish access to selected technology stacks and generate CI/CD pathways for controlled movement between development and production environments. Its Release Orchestration capability extends that model into deployment governance and dependency management. This gives data teams a self-service framework that reduces manual handoffs while keeping technical work connected to the product context and enterprise controls that initiated it. ...Read more
As software development becomes more reliant on AI, companies have started to focus more on the process of coding, changing, and attributing. Code attribution systems for AI are becoming common for helping engineering professionals know the source of code, differentiate human contributions from that done by AI, and remain visible in the development environment. Their importance goes beyond that of mere tracking since attribution can affect intellectual property management, security assessments, compliance procedures, and engineering performance. However, the implementation of these platforms poses some problems that organizations need to solve before they can effectively use attribution. How Can Organizations Maintain Accurate Code Attribution? An important issue here is the question of establishing accurate attribution in a complicated process of software development. Nowadays, software development includes many repositories, development environments, libraries, automated systems, and cooperation models. The suggestions generated by the artificial intelligence can be accepted, modified, mixed with the existing code, or completely rewritten by the developer. As a result, it becomes difficult to distinguish what part was done with the help of AI and what was developed independently by humans. Data quality also poses a challenge. Attributing authorship requires the availability of development history, history of code changes, prompts, suggestions, and modification patterns. Poor data quality can lead to erroneous findings, especially where organizations employ different methods for software development or use a different set of tools for development. It is imperative for businesses to come up with data standards for the consistency of findings. Issues related to privacy and intellectual property rights make the scenario even more complicated. The source code may include business logic, proprietary processes, and customer data. Companies that choose to implement the attribution platforms need to pay special attention to the way the development data will be gathered, analyzed, stored, and made available. What Makes AI Attribution Difficult Across Enterprise Development? The other challenge is that of incorporating the attribution process into the current engineering process. Companies typically have heterogeneous technology stacks and development processes. This implies that any attribution solution has to be compatible with the source code repositories, issue tracking platforms, code reviews, security mechanisms and so forth. If not, fragmentation and extra manual processes arise. Interpretation is just as crucial. Metrics related to attribution should not be automatically assumed to reflect developer productivity or the quality of code written. While AI can alter how engineers spend their time, more generated code does not imply a better result. Business context regarding maintainability, reliability, reviews, security, and business needs should also be factored in, along with attribution. Attributing AI code is going to be contingent upon transparency, interoperability, and good governance. Enterprises are going to require established processes for attributing contributions made by AI and also explaining how the information is to be utilized. Software systems capable of creating traceable evidence, easy integration, and clear reporting can enable enterprises to create more trust when it comes to AI-enabled development efforts. Taking a good approach towards these considerations will enable enterprises to get visibility regarding the use of AI in coding without having to risk their intellectual property rights and engineering accountability. ...Read more