Many AI, data and software initiatives are yielding promising results in pilot projects. However, the step towards productive deployment is often not taken. The reasons for this include a lack of integration into existing processes, unclear operating models, a lack of scalability, or a lack of accountability for further development, monitoring and governance. This results in siloed solutions that cannot be operated reliably or extended to other sites or processes.
From pilot project to full-scale operation – data, AI and software platforms for industry
jambit develops data solutions, AI applications and software platforms that can be integrated into established IT and OT environments and operated productively on a long-term basis. We modernise and expand existing systems step by step – without any pressure to switch to specific products.
This transforms production data into tangible business outcomes – from more efficient processes and better decision-making to new digital services and recurring revenue models in the service and after-sales sectors.
Would you like to evaluate an AI use case, harness production data, scale a service portal or securely bring a platform into operation? Let’s work together to assess your industrial project.
Integrating digital technologies into established industrial environments
Manufacturing companies face the challenge of integrating data, AI and modern software platforms not into a greenfield environment, but into established IT and OT landscapes. Machines, sensors, ERP, MES and other production systems form complex system environments in which data is often distributed, structured in different ways and can only be shared to a limited extent. Core systems dating back decades, siloed solutions and manual data flows further complicate new digital initiatives.
At the same time, economic and operational pressures are mounting:
- reducing costs
- reliably meeting quality targets
- making global production and supply networks more resilient
- increasing demands for energy efficiency
- sustainability
- compliance
- making data-driven decisions
Whilst companies need to boost their productivity, the shortage of skilled workers threatens to result in the loss of valuable process and service knowledge.
Customer expectations are also changing. Digital services are increasingly becoming an integral part of industrial value creation. Customers expect transparent processes and seamless interaction throughout the entire product life cycle. Particularly in the case of durable capital goods, the service and after-sales business offers potential for greater customer loyalty, differentiation and recurring revenue.
Where industrial digitalisation is stalling
Many industrial companies have already recognised the potential offered by production data, AI and modern software platforms. The bottleneck usually lies not in the idea or the technology itself, but in its implementation under real-world industrial conditions: in established IT and OT environments, with fragmented data, high security requirements and the need to operate solutions productively in the long term.
1. PoCs do not reach production
2. Data remains isolated and difficult to use
Machine, sensor, production, quality, service and company data are often stored in different systems. Without a shared database, subject-matter context and reliable data quality, this information can only be used to a limited extent for analysis, automation or AI applications. Even existing BI tools cannot compensate for this shortcoming if there is no reliable, integrated data foundation underlying them.
3. Software platforms are developed without a clear vision
Many companies build digital solutions in a piecemeal fashion without developing a holistic understanding of the platform. Individual applications, data solutions or integrations are developed in parallel, but are not consistently designed with scalability, reusability and extensibility in mind. A lack of interfaces and poor interoperability between legacy systems further complicate the integration of new use cases.
4. IT/OT security is taken into account too late
As production facilities, cloud platforms, data rooms and digital services become increasingly interconnected, the demands on security and compliance are rising. If access policies, regulatory requirements and operational risks are only taken into account at a late stage, projects are delayed or can only be operated productively at great expense. Security must therefore be an integral part of the architecture and implementation from the outset – particularly in light of NIS2, the EU AI Act, the Cyber Resilience Act and the Digital Product Passport.
5. Digital services remain isolated; knowledge remains tied to individuals
In many companies, digital services and service processes are still developed in isolation. Service portals, predictive maintenance offerings, spare parts processes and connected product solutions are often set up independently of one another. At the same time, practical knowledge in production, service and maintenance is often tied to individual employees. Without a shared platform, data and knowledge base, it is difficult to scale digital services and critical know-how and develop them further in a cost-effective manner. As a result, the potential for servitisation and recurring revenue also remains untapped.
Measurable added value is created when these barriers are systematically addressed: through integrated data, robust software platforms, interoperable legacy systems, security built in from the outset, and solutions that work in everyday industrial operations. It is precisely these barriers that jambit addresses end-to-end – from architecture through integration to live operation.
How jambit brings data, AI and software platforms into industrial practice
For data, AI and software solutions to deliver their full business value, they must be prioritised from a business perspective, developed to a technically sound standard, integrated and operated securely. This is precisely the responsibility that jambit assumes in partnership with industrial companies. We work in a technology-neutral manner and develop individual software where existing off-the-shelf solutions do not adequately cover specific processes or integration requirements.
Modernising and integrating legacy systems in stages
Existing ERP, MES and application systems can be modernised in stages without having to replace them entirely. jambit develops integration, API and middleware solutions that enable legacy systems to be connected. Applications are modernised or replaced where there is a clear business and financial benefit. This helps to minimise risks, reduce operating costs and roll out new functions more quickly.
Prioritising AI use cases with business value
Together with industrial companies, we identify and evaluate AI use cases where they can deliver tangible business value in production, quality, service or planning. In doing so, we consider not only the technological potential but also data availability, process maturity, integration effort and operational feasibility.
The result is AI roadmaps with realistic implementation paths: from technical prioritisation through production-oriented applications to the scaling of successful solutions. The focus is on use cases with a robust business case – not AI for AI’s sake.
Making production and company data usable
We consolidate machine, sensor, ERP, MES, quality and service data to create a robust data foundation. We structure data across systems, categorise it by business function and make it usable for analysis, automation, AI applications and management decisions.
Integrated production and business data give rise to data platforms, dashboards, analytics and AI solutions that create transparency, improve quality and efficiency, and enable data-driven decision-making.
Using the KPIXplain approach, jambit enhances existing data dashboards with an AI-powered dialogue with business data. Business users can more easily access key performance indicators, correlations and analyses with the help of AI, gain deeper insights and derive recommendations for action from them. Separate LLM and analytics layers ensure trustworthy and reproducible results.
Developing digital service platforms and connected products
Rather than creating isolated, stand-alone solutions, we develop software platforms with a focus on scalability, reusability and extensibility. These include platforms and architectures for digital services, connected products, customer and service portals, connected worker solutions, and the interconnection of international production and service structures.
Scalable platform architectures connect customers, products, partners, processes and data. They form the basis for remote monitoring, digital spare parts processes, usage-based offerings and Equipment-as-a-Service – and thus for scalable services and recurring revenue.
The jambit Internal Developer Platform is based on a standardised reference architecture, that incorporates our many years of experience gained from a wide range of client projects. It provides a proven foundation for the development and operation of digital applications. This enables applications to be deployed more quickly, operated reliably and continuously refined.
Scaling solutions and operating them in the long term
We take AI, data and software solutions from the pilot phase into production. Applications are developed in such a way that they can be integrated into existing system landscapes, operated securely and expanded flexibly.
In doing so, we combine modern software development with AI-supported development processes. AI-assisted development helps to make development and quality assurance more efficient. With the AI Software Development Lifecycle, jambit supports development teams in integrating AI into existing development processes in a structured manner and in increasing development output securely and scalably. On request, we also introduce these methods into our clients’ development teams.
Operating networked production systems safely
We take security, governance and compliance into account right from the start – particularly where IT and OT systems are becoming more closely integrated. Security architectures, access policies, regulatory requirements and governance issues are already incorporated into the architecture, development and operation phases. Depending on requirements, solutions can be operated in the cloud, in sovereign European cloud environments or on-premises.
Typical industrial applications
When companies strategically prioritise data, AI and software platforms and successfully integrate them into their processes, this gives rise to specific use cases that deliver measurable added value for production, quality, service and new digital business models.
1. Making intelligent use of production and quality data
By combining production, quality and business data, a centralised information base is created to support better decision-making. AI-powered analyses help to identify the causes of faults at an earlier stage, reduce scrap and improve production processes. This leads to greater transparency, more stable processes and lower quality costs.
2. Increasing plant availability with predictive maintenance
Machine and sensor data enable maintenance requirements to be identified at an early stage and potential failures to be detected before they occur. Predictive maintenance solutions help to reduce unplanned downtime, make maintenance processes more predictable and utilise resources more efficiently. In this way, industrial companies increase plant availability, improve planning reliability and reduce downtime-related costs.
3. Establish integrated digital customer and service platforms
Digital customer and service platforms lay the foundation for a scalable service and after-sales business. They enable self-service options, transparent product information, digital spare parts processes, and partner and customer portals throughout the entire product lifecycle. This results in more efficient processes, stronger customer loyalty and new revenue models in after-sales.
4. AI-powered support and sustainable knowledge retention
AI-powered service and support solutions assist staff and customers with product enquiries, fault analysis and support requests. They make experiential knowledge more readily available and help to retain individual expertise in the long term. This allows scarce specialist staff to focus more on complex and value-adding tasks.
5. Connected products and intelligent, data-driven services
Connected products continuously provide status and usage data, wich forms the basis for new digital value-added services and innovative business models. These include remote monitoring, condition-based maintenance, pay-per-use and equipment-as-a-service. This enables companies to strengthen customer loyalty and service quality in the long term, optimise processes and tap into additional revenue potential.
6. Improving traceability, compliance and accountability
Software and data platforms create transparency across production, quality and supply chain processes. They help companies meet audit, compliance, documentation and traceability requirements more efficiently and establish a robust data foundation for the digital product passport and the documentation of products and components throughout their lifecycle.
We provide scalable operating models and the expertise required for security architectures, modernisation, cloud transformation and data & analytics.
Measurable added value for production, quality and service
Measurable added value is not reflected in the number of projects launched, but in their outcomes for production, quality, plant availability, service and new business models.
Specifically, this business value is reflected in higher process quality, fewer unplanned downtimes, faster decision-making, lower operating and integration costs, and a shorter time-to-market for new features. In the service sector, digital portals, AI-supported support and data-driven offerings lead to more efficient processes, stronger customer loyalty and new revenue models.
Why jambit
For more than 25 years, jambit has been helping industrial companies integrate individual software solutions, data platforms and AI applications into established industrial system landscapes. Our focus is on production systems that can be integrated into existing IT and OT environments and deliver measurable added value.
To this end, jambit combines consultancy and implementation, software development, data expertise, AI, platform architecture and IT/OT integration, all from a single source. Our teams do not stop at the target vision, but develop solutions that can be operated, scaled and further developed. Depending on requirements, we take on full project responsibility or work in mixed teams with our clients’ specialist and development teams to specifically relieve the burden on internal teams and create scope for innovation.
As a technology-agnostic partner, we develop individual software to support existing ERP, MES and production systems and integrate them at both the software and data levels. We do not replace SAP consultancy or hardware-related machine, firmware or control system development; rather, we specifically bridge the gap between these systems, data and new digital applications.
What sets jambit apart:
Integration and phased modernisation of established IT and OT system landscapes
Consultancy, software development and expertise in data, AI and platforms, all from a single source
Technology-agnostic implementation, from concept through to live operation
Responsibility for scalability, security and long-term further development
Flexible collaboration with reusable assets for the cloud, data and AI
Frequently asked questions about data, AI and software platforms in industry
How do you successfully move from an AI pilot to production?
Moving from an AI pilot to production requires considering not only the technological potential, but also data availability, process maturity, integration, scalability, security, and operational readiness from the outset. AI solutions need to integrate reliably into existing systems and processes, operate securely, and remain flexible enough to scale and evolve. Clear responsibilities for continuous development, monitoring, and governance provide the foundation for successfully scaling AI pilots and transitioning them into long-term production.
How can AI use cases with business value be identified?
Not every AI use case automatically generates business value. The key factors are a clear business benefit, a robust data foundation and the ability to integrate the solution into existing processes and systems. jambit therefore works with industrial companies to assess not only the technological potential but also data availability, process maturity, integration effort and operational feasibility. This results in prioritised AI roadmaps with realistic implementation paths.
How can production, ERP and MES data be made usable for AI?
Machine, sensor, ERP, MES, quality and service data are often stored in different systems. Only once this data has been consolidated, categorised by subject area and quality-assured can it be used for analysis, automation and AI applications. To this end, jambit develops data platforms and integration solutions that provide a robust foundation for data-driven decision-making.
How can existing IT and OT systems be modernised in stages?
Existing ERP, MES and production systems do not need to be completely replaced in order to introduce new digital solutions. jambit develops integration, API and middleware solutions that gradually extend existing systems and make them interoperable. This allows data, AI applications and digital services to be introduced without jeopardising day-to-day operations through a technological ‘big bang’.
Industrievorhaben gemeinsam einordnen
The industry faces major challenges – and, at the same time, concrete opportunities. Companies that make their data usable, successfully integrate AI into their processes and establish robust software platforms are laying the foundations for long-term competitiveness. Digital services and data-driven business models can further expand existing product and service offerings.
Would you like to assess where data, AI or software platforms can have the greatest impact on your industrial value creation?
Together, we’ll categorise your project – whether it’s a data platform, an AI use case, a digital service offering, legacy modernisation or a platform initiative.
Maximilian Schenk
Head of Division Industry & Energy
