What Is a Temporary Chat in ChatGPT? Everything You Need to Know
What Is a Temporary Chat in ChatGPT? Everything You Need to Know As AI tools like ChatGPT become increasingly popular, users seek more control over their data and interactions. One useful feature that supports privacy-conscious and casual usage is the Temporary Chat. But what exactly is a Temporary Chat in ChatGPT, and how does it work? In this article, we’ll explain its purpose, benefits, limitations, and availability—helping you decide if it’s the right option for your needs. What Is a Temporary Chat? A Temporary Chat in ChatGPT is a conversation that isn’t saved to your chat history. Unlike regular chats, these sessions do not appear in your chat sidebar, and won’t be used to train OpenAI’s models (unless you opt in to share feedback). Temporary Chats are ideal for short, one-time interactions where you don’t want to store any context or personal information. Think of it as ChatGPT’s “incognito mode.” Benefits of Using a Temporary Chat Here are some key advantages of using Temporary Chat: 1. Enhanced Privacy Temporary Chats are not stored in your account history. This means you can ask questions without worrying that the conversation will be saved or referenced later. 2. No Impact on Training Data OpenAI does not use Temporary Chat conversations to train its models by default, which adds another layer of data privacy. 3. Clean Slate Every Time Each Temporary Chat starts fresh. ChatGPT has no memory of past messages, which is ideal for users who want unbiased or unlinked answers. 4. Quick and Simple You don’t need to manage or delete history—everything disappears automatically after the session ends. Who Should Use Temporary Chats? Temporary Chats are useful for: Privacy-conscious users who prefer not to leave digital footprints. New users testing the tool without committing to an account or long-term interaction. Professionals handling sensitive or confidential questions. Students and researchers conducting quick fact-checks or one-off tasks. Developers experimenting with prompts in isolation. Where to Find the Temporary Chat Option To start a Temporary Chat in ChatGPT: Open ChatGPT and log into your account. Click on the “+ New Chat” button. On the left side at the top, look for the “Temporary Chat” option. Start chatting—the session will not be saved to history. You can also access Temporary Chat via direct links or when using ChatGPT without an active login in some cases. Limitations of Temporary Chats While useful, Temporary Chats come with some limitations: No memory or continuity: The model does not remember previous messages after the session ends. Limited personalization: Since the chat is stateless, you don’t get customized replies based on past interactions. Unavailable features: Some advanced features tied to memory or custom instructions may not be accessible. No chat history recovery: Once closed, the conversation cannot be retrieved. Which Plans Include Temporary Chat? Temporary Chat is available on all plans, including: ✅ Free Plan (GPT-3.5) – fully accessible. ✅ ChatGPT Plus (GPT-4) – available alongside advanced model access. Note: While all users can start Temporary Chats, access to GPT-4 and other premium tools depends on your subscription. Final Thoughts Temporary Chat is a powerful and flexible feature that gives users more control over their data and privacy. Whether you’re handling sensitive topics or just exploring AI without commitment, this feature ensures a secure and distraction-free experience. Looking for a private, no-strings-attached chat? Temporary Chat is your go-to solution. 💡 Pro Tip: Want to keep your chat data private and benefit from memory features when needed? You can toggle memory on or off per chat in your settings. Want to Go Beyond Temporary Chat? While Temporary Chat is a great starting point for secure and casual conversations, the true potential of ChatGPT and other AI tools lies in their ability to transform how businesses operate. Whether you’re exploring AI-powered automation, customer support, or data-driven decision-making, we can help you unlock that potential. At Transition Technologies MS (TTMS), we specialize in creating tailored AI solutions for businesses—from prototypes and pilots to enterprise-scale integrations using tools like ChatGPT, Azure OpenAI, and more. Discover how we can help your business grow with AI →
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Seeing More Than the Human Eye – AI as a Battlefield Analyst
The modern battlefield is not only a physical space but also a dynamic digital environment where data and its interpretation play a crucial role. With the growing number of sensors, drones, cameras, and radar systems, the military now has access to an unprecedented volume of information. The challenge is no longer data scarcity but effective analysis. This is where Artificial Intelligence (AI) steps in, transforming reconnaissance and real-time decision-making. AI as a Digital Scout Traditional methods of intelligence data analysis are time-consuming and prone to human error. AI changes the rules of engagement by enabling: automatic object recognition in satellite and video imagery, detection of anomalies in troop movements and activity, identification of enemy behaviour patterns based on historical data, real-time analysis of audio, visual, and sensor data, classification and prioritisation of threats using risk models. Thanks to machine learning (ML) and deep learning (DL), AI systems can not only identify vehicles, weapons, or military infrastructure but also distinguish between civilian and military objects with high accuracy. Image analysis algorithms can rapidly compare current data with historical records to detect changes that may indicate military activity. For example, an AI system can detect a newly established missile site by analysing differences in satellite imagery over time. AI Supports Decisions, It Doesn’t Replace Commanders Artificial Intelligence does not replace commanders – it provides ready-to-use analysis and recommendations that support fast and accurate decisions. So-called “intelligent command dashboards” integrated with AI systems enable: analysis of projectile trajectories and prediction of impact points, risk assessment for specific units and areas of operation, generation of dynamic situational maps that reflect enemy movement, correlation of data from multiple sources, including: Radar: provides real-time movement tracking, SIGINT (Signals Intelligence): analyses intercepted electronic signals, e.g., enemy radio communication, HUMINT (Human Intelligence): includes data from agents, soldiers, and local informants, OSINT (Open Source Intelligence): utilises publicly available data from social media, news, and live feeds. AI also supports mission planning by analysing “what if” scenarios. For example: what happens if the enemy moves 10 km west – will our forces maintain the advantage? These tools significantly increase situational awareness, which is crucial during rapid conflict escalation. Examples of AI Use in Global Defence Project Maven (USA): A U.S. Department of Defense initiative that uses AI to automatically analyse drone video footage, detecting objects and suspicious behaviour without human analysts. NATO Allied Command Transformation: Using AI systems to support decision-making across multi-domain environments (land, air, sea, cyber, space). Israel: The Israeli military uses AI to merge real-time intelligence from multiple sources, enabling precision strikes within minutes of identifying a target. TTMS and AI Projects for the Defence Sector Transition Technologies MS (TTMS) delivers solutions in data analytics, image processing, and Artificial Intelligence, supporting defence institutions. Our experience includes: designing and implementing AI models tailored to military needs (e.g., object classification, change detection, predictive analytics), integrating with existing IT and hardware infrastructure, ensuring compliance with security standards and regulations (including NIS2), building applications that analyse data from radars, drones, optical and acoustic sensors. The systems we develop enable faster and more precise data processing, which on the battlefield can translate into real operational advantage, shorter response time, and fewer losses. The Future: Predicting Enemy Actions and Autonomous Operations The most advanced AI systems not only analyse current events but also predict future scenarios based on past patterns and live data. Predictive models, based on deep learning and multifactor analysis, can support: detection of offensive preparations, prediction of enemy troop movements, assessment of enemy combat readiness, automation of defensive responses, e.g., via C-RAM (Counter Rocket, Artillery, and Mortar) systems – these are automated defence platforms that detect, track, and neutralise incoming rockets, artillery shells, and mortars before impact. C-RAM systems use a combination of radar, tracking software, and rapid-fire weapons (such as the Phalanx system), while AI enhances threat detection, classification, and timing of countermeasures. In the near future, AI will also become the backbone of autonomous combat units – land, air, and sea-based vehicles capable of independently analysing their surroundings and executing missions in highly uncertain environments. Artificial Intelligence is no longer a futuristic concept but a real tool enhancing national security. TTMS, as a technology partner, is actively shaping this transformation by offering proven, defence-tailored solutions. Want to learn how AI can support your institution? Contact us! What is the Phalanx system? The Phalanx system is an automated Close-In Weapon System (CIWS) primarily used on naval ships and in some land-based versions. It neutralizes incoming threats such as missiles, artillery, or mortars before they strike. It includes radar and a rapid-fire 20mm Gatling gun that automatically tracks and eliminates targets. It’s a key component of C-RAM defense layers. How does the Israeli army use AI to integrate real-time intelligence? The Israeli military integrates intelligence from various sources (SIGINT, HUMINT, drones, satellites, cameras) using AI-powered systems. These algorithms analyze real-time data to identify threats and targets, allowing for precise strikes within minutes of detection. What is NIS2? NIS2 is the updated EU directive on network and information system security, replacing NIS1. It expands cybersecurity responsibilities for essential service operators (including defense) and digital service providers. It includes risk management, incident reporting, and supply chain evaluation requirements. What are C-RAM systems? C-RAM (Counter Rocket, Artillery, and Mortar) systems detect, track, and neutralize incoming projectiles before they reach their targets. They use advanced radar, optics, and weapons like the Phalanx CIWS. AI supports these systems by automating threat detection and engagement decisions. What is SIGINT? SIGINT (Signals Intelligence) involves intercepting and analyzing electromagnetic signals, including communications (e.g., radio) and non-communications (e.g., radar). AI can analyze massive volumes of SIGINT data to detect military activity patterns and anomalies. What is HUMINT? HUMINT (Human Intelligence) is based on information gathered from human sources – agents, soldiers, and local informants. While harder to automate, AI helps assess report consistency, translate languages, and cross-reference with other intelligence. What is OSINT? OSINT (Open Source Intelligence) refers to intelligence from publicly available sources – social media, news outlets, livestreams, and open satellite imagery. AI plays a key role in filtering and identifying relevant insights in real-time from vast data pools.
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AI and Copilot in Power BI – How Artificial Intelligence Transforms Data Analysis
The development of artificial intelligence (AI) has significantly transformed how businesses analyse and present data. Microsoft Copilot in Power BI is an advanced AI-powered tool that automates report creation, data interpretation, and anomaly detection, making data analysis more intuitive and accessible for all users—regardless of their technical expertise. 1. What is Microsoft Copilot in Power BI? Microsoft Copilot is an advanced AI assistant that is part of the Microsoft ecosystem and is used in many applications, including Power BI. In the context of Power BI, Copilot acts as a tool supporting users in data analysis, report generation, and interpretation of results without the need to manually create queries or configure visualisations. It allows users to communicate with data in a natural way – by entering questions in English – and then automatically generates appropriate reports and insights. With it, you can build dashboards, analyse trends, and quickly respond to market changes without needing to know DAX or M coding. Microsoft has chosen to integrate Copilot with Power BI in response to the needs of companies aiming to automate and simplify data analysis. The tool is designed to accelerate business processes, reduce human error, and support strategic, data-driven decisions. 2. How to Access Copilot in Power BI? Copilot in Power BI is available to users with a Power BI Premium or Power BI Pro licence and access to Microsoft Fabric. To activate Copilot, your organisation’s administrator must enable it in the Microsoft Fabric settings. Copilot is being rolled out in preview across regions, so some users may not yet have access to it. 2.1 How to Enable Copilot in Power BI? Log in to the Power BI Service as an administrator. Navigate to Admin Settings. Locate the Copilot option under the Microsoft Fabric section. Enable Copilot for the organisation and assign access to users. 3. What are the Features of Copilot in Power BI? Microsoft Copilot in Power BI offers a wide range of functionalities that enhance data analysis, reporting, and business decision-making. Its main advantage lies in the use of artificial intelligence to automate analytical processes, removing the need for manual report preparation or the analysis of complex queries. Copilot integrates with the Power BI interface, allowing users to interact using natural language. Here are the key features that make Copilot a powerful analytical tool: 3.1 Report Generation Using Natural Language Queries Copilot enables users to create reports without needing to manually define data sources, choose visualisations, or configure filters. Simply enter a question, such as “Show me sales by region for the last three months,” and Copilot will automatically generate the relevant report and adjust the data formatting. Users can also edit reports with simple text commands, such as “Add a line chart to the report” or “Change the X-axis to sales dates.” 3.2 Automated Narrative Generation and Insights Interpretation Copilot not only creates visualisations but also provides descriptive summaries of key insights from the analysis. This feature helps users to quickly understand trends and anomalies in the data without having to conduct in-depth analysis. For example, if a report shows a sudden increase in sales in one region, Copilot might generate a comment such as, “Sales in the North region increased by 15% last quarter, mainly due to increased orders from B2B customers.” 3.3 Visualisation Recommendations Copilot assists users in selecting the most suitable method for visualising data by analysing the report’s structure and the nature of the dataset. If a user is unsure how best to present their data, Copilot can suggest various types of charts and tables. For instance, when analysing sales trends, it may recommend a line chart or column chart, while for demographic data, a heat map or pie chart might be more appropriate. 3.4 Trend and Anomaly Detection Copilot applies AI algorithms to identify unusual patterns and deviations in the data. This allows users to automatically pinpoint areas that require attention, such as sudden drops in revenue, rising operational costs, or irregular sales figures. Copilot not only highlights these anomalies but also suggests possible causes and actions to explain or address them. 3.5 Automatic Correlation Analysis Between Data Sets Using AI, Copilot can analyse relationships between different variables within a dataset and identify correlations that may impact business outcomes. For example, Copilot might reveal that an increase in website visits corresponds with a rise in order volume over a specific period. This enables companies to adjust their marketing and sales strategies based on real evidence. 3.6 Predictive Analytics Support Although Copilot is not a full substitute for advanced machine learning tools, it does offer some predictive analytics features. For instance, Copilot can use historical sales data to forecast future buying trends and identify potential risks linked to demand fluctuations. Finance teams can leverage this feature for budgeting and inventory planning. 3.7 Integration with Microsoft Fabric and Other Services Copilot is fully integrated with the Microsoft Fabric ecosystem, enabling it to draw from multiple data sources such as Azure Data Lake, OneLake, and Microsoft Dataverse. This gives users a more comprehensive view of the organisation and allows them to create reports using data from various systems. 3.8 Team Collaboration and Interactive Analytics Sessions Copilot supports teamwork by allowing real-time collaborative editing of reports and sharing of insights. Users can ask questions in an interactive session and dynamically adjust reports to suit the team’s needs. This enhances report creation efficiency and speeds up decision-making. 3.9 Personalised Results and User Preferences Copilot learns from user behaviour, gradually improving the precision of its suggestions and analysis. Users can personalise report generation by defining preferences for formatting, the depth of analysis, and the presentation of data. 3.10 Advanced Query Handling and Data Filtering Copilot allows users to pose more complex questions, including those with advanced filtering criteria. For example, a user could ask, “Show me sales only to customers in the UK technology sector who placed an order in the past six months and whose order value exceeded £10,000.” Copilot will instantly generate a report showing only the relevant data. These features make Copilot in Power BI an indispensable tool for companies seeking to maximise the value of their data and make informed decisions based on solid analysis. Its versatility makes it useful for both data scientists and business managers who need fast access to critical insights. Microsoft Copilot in Power BI offers a wide range of functionalities that make working with data easier: Reporting – Users can type queries in natural language, and Copilot generates visualisations and recommendations. Automatic narrative generation – Copilot analyses data and presents key findings in a narrative format. Identifying trends and anomalies – AI scans data and detects unusual patterns. Visualisation suggestions – Suggests the best ways to present data. Interactive dataset queries – Users can ask questions without having to write DAX code. 4. What are the Limitations of Copilot in the Basic Version? The preview version of Copilot in Power BI has several limitations: Supports English only. Can generate reports for specific data types only. Requires activation by an administrator. Available in selected regions only. Does not support all complex data models. 5. Example Prompts for Copilot in Power BI Users can ask Copilot questions such as: “Create a sales report for the last three months by region.” “Show me a revenue trend chart for this year.” “What were the biggest changes in financial results last quarter?” “Find anomalies in last month’s sales data.” 6. How Much Does Copilot in Power BI Cost? Copilot in Power BI is included in Power BI Premium and Power BI Pro licences. Currently, it is available in a preview version, and pricing details may change as new features are introduced. Microsoft may introduce additional licensing options in the future for more advanced users. 7. Examples of AI and Copilot Applications in Business 7.1 Power BI and Copilot in Marketing Copilot in Power BI enables marketing companies to analyse the performance of advertising campaigns in real time. This allows them to identify which channels are performing best, which customer segments are converting most effectively, and where marketing budgets are being used least efficiently. For example, an e-commerce company can use Copilot to track advertising performance across platforms, automatically generating comparative reports that help optimise budgets. 7.2 Power BI and Copilot in Finance Finance departments can use Copilot to create budget forecasts and analyse cash flows. The tool can automatically detect anomalies in financial data, such as unexpected increases in expenses or irregular cash inflows. In the banking sector, Copilot can support the analysis of credit indicators and generate reports on the financial stability of customers, which speeds up the credit decision-making process. 7.3 Power BI and Copilot in Sales Sales teams can use Copilot to monitor sales performance and optimise sales strategies. The system allows for quick reporting on top- and bottom-selling products, customer purchasing trends, and sales seasonality. This enables sales managers to make more informed decisions about pricing and inventory planning. 8. Power BI Solutions from TTMS At Transition Technologies MS (TTMS), we specialise in delivering comprehensive analytics solutions based on Power BI. Our services include designing, implementing, and optimising reports and dashboards tailored to your organisation’s needs. By working with our experts, y ou can fully leverage AI-powered tools like Microsoft Copilot to enhance business efficiency and make data-driven decisions faster. Find out more at https://ttms.com/uk/power-bi/ Can Copilot in Power BI be used for real-time data analysis? Yes, Copilot can process and analyze near real-time data, provided the dataset is connected to a live data source. However, response times may depend on the complexity of queries and the refresh rate of the data source. Is Copilot in Power BI available on mobile devices? Copilot functionalities are primarily designed for the desktop and web versions of Power BI. While you can view and interact with reports on mobile devices, full Copilot capabilities may not yet be fully supported. Can Copilot generate DAX formulas automatically? Yes, Copilot can assist in generating DAX formulas based on natural language queries. It helps users create complex calculations without deep knowledge of DAX, improving efficiency in report development. How does Copilot ensure data security when processing reports? Copilot adheres to Microsoft’s enterprise security standards, ensuring that all processed data remains within the organization’s security framework. It does not store or share sensitive data outside of the Power BI environment. Can Copilot be customized to specific business needs? While Copilot operates on general AI principles, it adapts to user interactions over time, improving recommendations. Future updates may include more customization options to align with specific business processes and reporting standards. What is Microsoft Fabric? Microsoft Fabric is a comprehensive cloud-based analytics platform designed to integrate, process, and analyze data within a unified environment. It combines various Microsoft data services, such as Azure Data Factory, Power BI, Synapse Analytics, and Data Lake, providing businesses with a flexible and scalable data management solution. Key Features of Microsoft Fabric: Lakehouse Architecture – Enables storing and analyzing large datasets in a Data Lake without the need for data movement. Power BI Integration – Simplifies the creation of interactive reports and analytics based on data stored in Fabric. Built-in AI Capabilities – Supports predictive analytics, automated data processing, and anomaly detection. OneLake – A central data repository that eliminates duplication and provides unified data access. Support for ETL and ELT – Facilitates efficient data processing and transformation for advanced analytics. Security and Compliance – Advanced data protection mechanisms compliant with corporate standards and legal regulations. With Microsoft Fabric, businesses can collect, process, analyze, and visualize data within a single ecosystem, enabling data-driven decision-making and accelerating digital transformation.
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A flexible Time & Material model designed for complex IT projects in large companies
Time & Material (T&M) is a model of cooperation in which billing is based on the actual time worked by specialists and the resources used. Unlike the rigid Fixed Price model, where the scope and cost are defined upfront, T&M ensures flexibility – the scope of work can evolve during the project, and the client pays for the actual tasks performed. This model is gaining popularity among companies undergoing digital transformation, who need quick access to competencies and the ability to adapt to changes. Below, we explain why T&M is the preferred model for digital transformation leaders, in which situations it works best, and provide examples (including the cooperation between TTMS Software Sdn Bhd and ADA). Finally, we invite you to talk about how T&M can support your project. 1. What is the Time & Material model in IT? The Time & Material model means that the client pays for the hours worked and the tools used to complete the IT project. There is no fixed total cost or fully frozen scope – the project is carried out iteratively, and details can be refined during the work. This model is fully compatible with Agile methodologies and the iterative approach to software development. The project team logs work hours, reports progress, and settlements are made periodically (e.g., monthly or per stage). The client gains full transparency – they know exactly what they are paying for and can continuously adjust the direction of the work. In practice, the T&M contract sets the rates (e.g., hourly or daily) for specific roles in the project (developer, tester, analyst, etc.) and general rules of cooperation. But it leaves space for scope changes. If new requirements or changes arise during the project, there is no need to renegotiate the contract – the team simply continues the work, and the client pays for the additional time based on the agreed rates. This significantly shortens the project launch time and reduces the risk of underestimating or omitting important elements. In T&M, both the IT provider and the client act as partners sharing responsibility for the project’s success. 2. Flexibility above all – why leaders choose T&M Today’s business environment is extremely dynamic. Companies that are leaders in digital transformation know that change is the norm in ambitious IT projects – new ideas emerge, user expectations evolve, and technology is constantly developing. Traditional settlement models (e.g. fixed-price projects) often prove too inflexible in such conditions. That’s why leading organisations increasingly choose Time & Material to ensure the ability to respond quickly and keep pace with innovation. The T&M model offers a number of benefits for large enterprises and digital transformation programmes: Quick project start and delivery in stages: No need to wait for a perfectly refined scope – work can start quickly, and solutions are delivered in short iterations. This allows early business value realisation and continuous verification. Flexibility in implementing changes: When new challenges arise or new ideas appear, the team can immediately adjust the scope of work. There is no need to amend the contract for each change – the plan evolves within the agreed framework. Cost transparency: At every stage, it is clear how much time has been worked and what the budget is spent on. The client receives regular reports, knows exactly what they are paying for, and can control the budget throughout the project. Full control and involvement on the client side: The client is actively involved in the project – can prioritise tasks, decide on the order of implementation, and quickly change direction if necessary. Access to needed competencies exactly when they are needed: In the T&M model, the team can be scaled flexibly – increased in size or supplemented with new experts when the project enters a new phase. Higher quality through continuous improvements: As the project is run iteratively, the final product can be of better quality – continuous testing, feedback, and improvements increase value step by step. It is worth noting that the T&M model eliminates the need to pay for “extra” assumptions. In a fixed-price model, providers often add a risk buffer – so the client pays in advance, even for unforeseen difficulties. In T&M, you pay only for the actual work. If some tasks turn out to be unnecessary or simplified, the budget can be shifted to other priorities. 3. When does the T&M model work best? The Time & Material model is not a cure-all – there are situations where it works perfectly and others where a fixed-price model might be better. Below are typical scenarios where T&M works best: Long-term, complex projects – if the initiative is extended over time and consists of many phases, it is obvious that it’s hard to predict all requirements at the start. T&M allows scope adjustment according to current needs. Unclear requirements at the start – when the client has a general vision but not a detailed list of functionalities. This often occurs in innovative projects. T&M allows starting with an MVP and then iterative development. Dynamic business or technology environment – in industries like fintech, e-commerce, or telecoms, change is constant. If user needs evolve quickly, regulations change, or there’s competitive pressure, fixed contracts can slow you down. T&M allows flexibility and speed. Budget control during the project – paradoxically, although T&M doesn’t specify the final amount upfront, it allows strict budget control. You can monitor ROI and decide on funding further stages based on previous outcomes. Outsourcing and need for specific know-how – if you’re using IT outsourcing or staff augmentation, T&M is a natural choice. You can get the expert you need without long hiring processes. Of course, the T&M model requires trust and maturity on both sides – the client must be ready to collaborate and supervise, and the provider must ensure transparency. Experienced partners like TTMS introduce control mechanisms (hour tracking, budget checkpoints, milestones) to protect the project. 4. Example: TTMS and ADA – partnership in T&M model A real example of T&M flexibility is the recent cooperation between TTMS Software Sdn Bhd (TTMS branch in Malaysia) and ADA, a leading digital transformation company in Southeast Asia. ADA specialises in data analytics, AI, and digital marketing, serves over 1,500 clients in 12 markets, and is backed by investors like SoftBank and Axiata Group. The partnership began in the Time & Material model, with TTMS providing a Salesforce Administrator for three months. This form enabled ADA to use TTMS experience exactly when needed and created a foundation for further cooperation. Read more in the press release: TTMS Software Sdn Bhd starts cooperation with ADA 5. Other examples of T&M at TTMS At TTMS, we have been delivering projects in the Time & Material or similar flexible models for years. Most of our case studies are stories of long-term cooperation, iterative system improvement, and a partnership approach – that’s what T&M enables. For example: In the energy sector, we created a scalable application that integrated many systems. In the pharmaceutical sector, we supported an international company in building a CRM system with a growing scope. For Schneider Electric, we are a long-term outsourcing partner – we provide specialists in the T&M model. 6. T&M in Asia – a growing trend We observe growing interest in flexible contracts in Asia. Companies in this region, known for dynamic growth, often point to the T&M model as key to successful transformation. For example: A telecoms operator in Southeast Asia chose T&M for a new digital platform, which allowed them to adapt the roadmap in real time. In e-commerce, a platform was iteratively adapted to user needs through a T&M-based cooperation with an external team. These examples show that flexibility = effectiveness. 7. Choose the right model Time & Material is a proven way to run an IT project when speed, adaptability, and access to talent matter. Leaders choose it because it lets them focus on business goals instead of renegotiating contracts. Properly applied, T&M gives: Freedom of action Transparent costs Quality and results If your company is planning a new system or wants to improve an existing one and needs a flexible and experienced IT partner, T&M may be the right choice. TTMS has been supporting clients in this model for years – providing top experts and teams, building long-term relationships based on trust and shared goals. Let’s talk – we’ll tailor the cooperation model to your project. Contact us. What is the difference between Time & Material and Staff Augmentation? While both offer flexibility, Time & Material refers to billing for work completed over time, often in a project context. Staff Augmentation focuses on providing personnel to extend internal teams. T&M may include team delivery, project milestones, and shared goals—beyond just supplying resources. Is the Time & Material model more expensive than Fixed Price? Not necessarily. Although T&M lacks a fixed upfront budget, it often avoids overpayment by billing only for actual work done. Fixed Price contracts may include large risk buffers, while T&M enables better cost control if well-managed. How do you control scope and costs in a Time & Material project? T&M requires strong project governance—typically involving time tracking, regular reporting, sprint reviews, and clear communication. Clients remain actively involved, adjusting priorities and validating outcomes in real time. Is Time & Material suitable for regulated industries like pharma or finance? Yes. When combined with proper documentation, validation, and quality controls, T&M can meet industry compliance needs. It’s especially useful in complex environments where detailed requirements evolve during the project lifecycle. Can we start with Time & Material and switch to Fixed Price later? Absolutely. Many companies begin with T&M for discovery, MVPs, or early development. Once scope stabilizes, transitioning to a Fixed Price or hybrid model is common—ensuring flexibility early on and predictability later.
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Challenges and Entry Barriers for IT Companies in the Defence Sector – The Case of TTMS
The defence sector is becoming an increasingly important recipient of modern IT solutions. Growing defence budgets open up new business opportunities for technology companies. According to the International Institute for Strategic Studies, defence spending in Europe rose by 11.7% in 2024, reaching USD 457 billion. Despite this market’s potential, IT companies face exceptionally high formal, technological, and organizational barriers when attempting to enter the defence industry. Transition Technologies Managed Services (TTMS), a Polish software house, is a compelling example of a company that is successfully overcoming these hurdles. In recent years, TTMS has significantly expanded its defence-related operations. The company has doubled its defence contract portfolio while systematically enhancing its offer for military and governmental institutions. Sebastian Sokołowski, CEO TTMS As TTMS CEO Sebastian Sokołowski stated in a recent interview for ISBtech.pl: “We are currently focusing strongly on developing our operations in the defence sector, which has allowed us to double our order portfolio in this area. The growing demand creates many opportunities, but being a preferred partner in this market is a major challenge for many IT firms due to high entry barriers and the need for niche competencies.” Below, we explore the main challenges of entering the defence industry and how TTMS is addressing them to establish itself as a trusted supplier. Formal and Regulatory Barriers One of the biggest challenges for IT firms entering the defence industry is the number of formal requirements they must meet. In Poland, any activity related to the manufacturing or trading of military-grade technologies or products requires a government license. TTMS holds such a license since 2019. In 2024, the company renewed its permit to handle dual-use technologies for a maximum period of 50 years. This enables the company to legally participate in tenders and contracts involving advanced military technologies. Additionally, companies must have security clearances to handle classified information, a typical requirement in defence projects. This means that both the company and its staff must obtain industrial and personal security clearances at various levels. TTMS employees are certified to work on classified materials at NATO/ESA/EU Secret levels, meeting strict standards for confidentiality and secure information handling. Only a handful of Polish IT companies have this level of access and experience, putting TTMS in a select group of suppliers qualified to support military-grade IT projects. Technological Standards and Security Requirements From a technological standpoint, entering the defence market means complying with extremely high requirements for quality, resilience, and cybersecurity. Defence-related IT systems, especially those used for command, control, communications, and reconnaissance ISO 27001 and STANAG (NATO Standardization Agreements). TTMS has developed these competencies through years of experience and has built internal teams capable of working on military-grade systems. The company’s consultants understand the logic and workflows of defence systems at the tactical, operational, and strategic levels, allowing them to work on both pure software projects and integrations with military equipment and battlefield sensors. TTMS also applies methodologies and standards from the space industry — such as Product and Quality Assurance for the European Space Agency (ESA) — to ensure that each system meets the highest quality and safety benchmarks. This rigorous approach is equally applicable in defence contracts, where system failure can lead to mission failure. TTMS regularly participates in technology trials and validation efforts, including within NATO’s ACT Innovation Hub, where new tools and frameworks are tested under controlled conditions before being rolled out into production environments. Procurement Cycles and Organizational Challenges Even with the right certifications and technical expertise, IT companies face another critical hurdle — the length and complexity of public sector procurement cycles. Defence contracts are typically subject to multi-stage public tenders, technical consultations, and rigorous vetting procedures, which can take months or even years to complete. Moreover, tenders often require evidence of prior experience, financial stability, and the ability to provide long-term support. Companies may also need to commit to deploying personnel on-site, maintaining hardware and software for years, and complying with strict documentation and reporting protocols. For many IT vendors, the resources required to simply submit a compliant offer are a barrier in themselves. To mitigate these challenges, TTMS has adopted a partnership-driven strategy, participating in consortiums that combine different capabilities across organizations. Large defence contracts are rarely executed by a single vendor — instead, they are typically delivered by groups that include system integrators, hardware providers, software developers, and training companies. TTMS has participated in many such tenders — either independently or as part of a consortium — and has successfully won contracts or advanced to final stages in many defence procurement processes. Another key characteristic of this market is the long lifecycle of contracts. Once a solution is implemented, the provider is often responsible for its maintenance and evolution for several years. As CEO Sokołowski notes, “Defence contracts are by definition long-term engagements — specialists are often involved for years, and system rollouts are accompanied by ongoing support and maintenance.” This long-term horizon presents both an opportunity and a responsibility, as the company becomes a long-term strategic partner for military clients. How TTMS Prepares for Defence Sector Demands To succeed in such a highly specialized field, TTMS has made strategic investments in certifications, personnel, and organizational capabilities tailored to the needs of the defence sector. Since 2017, the company has consciously developed its Defence & Space business line, combining its roots in industrial software with the unique demands of national security applications. TTMS management board This includes establishing a dedicated Defence & Space division, hiring staff with security clearances, and creating secure environments for working with classified data. TTMS has also created internal teams for cybersecurity, geospatial systems, AI-based decision support tools, and interoperability between national and NATO command systems. A key part of the company’s strategy is to build strong reference cases through successful implementations. Before winning its own defence contracts, TTMS served as a subcontractor in consortia — gaining valuable know-how and building a project portfolio that later opened doors to larger tenders. Today, TTMS has successfully delivered more than ten defence-related projects and is involved in many others that are ongoing or in advanced stages of procurement. Notable Projects: NATO, ESA, and Beyond Among TTMS’s most prominent achievements is its involvement in projects for NATO’s Allied Command Transformation (ACT) and the NATO Standardization Office (NSO). For instance, the company was awarded a €0.9 million contract to build a new terminology management system for NATO. This platform allows the alliance to manage, distribute, and maintain unified military terminology and acronyms — critical for ensuring consistency across multinational forces. TTMS is responsible for delivering the entire system as part of a consortium, demonstrating its ability to deliver high-impact, multinational solutions. The company also participates in cyber intelligence and decision-support systems for NATO, including tools that process Open Source Intelligence (OSINT) using artificial intelligence to help commanders make better-informed strategic decisions. Other initiatives include communication interfaces that link the Polish Armed Forces with NATO systems, ensuring interoperability across command structures. TTMS’s expertise in the space sector further strengthens its capabilities. The company supports projects for ESA and the EU Space Program Agency, delivering services related to quality assurance and software safety. These space projects demand the highest standards of reliability and resilience — traits that are equally vital in military contexts. Earning Trust in the Defence Sector Ultimately, trust is the most valuable currency in the defence industry. Institutions are cautious and deliberate when selecting long-term partners. TTMS has worked for years to build a reputation for security, professionalism, and delivery excellence. Its certifications, long-term client relationships, and secure project environments help position it as a reliable supplier. TTMS’s credibility is further enhanced by its corporate governance and financial transparency. As a member of the Transition Technologies Group and a company preparing for an IPO, TTMS is subject to the oversight and reporting obligations that come with listing — reassuring public sector clients of its financial and operational maturity. The company also has a growing presence in international markets (Europe, Asia, Latin America), and its selection by major institutions such as NATO and ESA confirms its global competitiveness. TTMS’s leadership emphasizes that cutting-edge technologies such as artificial intelligence and cybersecurity will play a growing role in defence systems, and the company is committed to building long-term relationships with key institutions in these areas. Conclusion The defence sector is one of the most demanding — and most rewarding — markets for IT providers. Entry requires formal licenses, security clearances, technological specialization, and procedural fluency in public procurement. TTMS exemplifies how a company can build up these capabilities strategically, invest in the right people and certifications, and gradually earn the trust of major defence stakeholders. In doing so, it not only opens new revenue streams but also contributes to national and international security by delivering innovative, mission-critical digital systems. Why is it so difficult for IT companies to enter the defence sector? The defence sector imposes strict formal requirements (licenses, security clearances), advanced technological standards (system resilience, NATO norms), and complex procurement procedures. Trust and long-term references are also essential to succeed. What is a NATO/ESA/EU SECRET security clearance? It is an official authorization that allows a company and its personnel to access and handle classified information at the “SECRET” level in international projects for organizations like NATO, the European Space Agency (ESA), or the EU. It reflects high levels of security compliance and confidentiality. What does C4ISR stand for? C4ISR means Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance. It refers to integrated systems that help military forces make decisions, communicate, analyze intelligence, and monitor the battlefield. It is the digital backbone of modern defence operations. What technologies does TTMS offer for the defence sector? TTMS provides: decision-support systems for military command, NATO-compliant software solutions, AI-powered data analytics tools, interoperability tools between national forces and NATO systems, support for space and satellite-based defence initiatives. How is a military procurement process different from a civilian one? Military tenders are more complex and formalized. They often require special licenses, security clearances, inter-ministerial approvals, and guarantees for long-term system maintenance. The process typically takes longer and includes stricter evaluation criteria.
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Operator by OpenAI – A New Era of Business Automation
Can AI Work as Your Assistant? OpenAI has introduced Operator – an intelligent AI agent that performs tasks just like a human. It can purchase products, file expense reports, book restaurant reservations, and even manage online tasks by interacting with user interfaces. For businesses, this marks a breakthrough in process automation, offering time and cost savings. How Does Operator Work? Operator can scroll, click, fill out forms, and navigate web systems – exactly as a human would. This enables it to handle processes that traditionally required manual labor. It goes beyond classic chatbots and RPA (Robotic Process Automation) systems because: ✅ It operates like a human – no API integration needed, interacts directly with interfaces. ✅ It automates complex tasks – such as gathering information, comparing offers, and sending emails. ✅ It learns and adapts – analyzing user patterns and adjusting to evolving processes. How Can Operator Support Businesses? Customer Service and Sales Processes Automated meeting scheduling and calendar coordination. Real-time responses to customer inquiries. Personalized offers based on data analysis. Administrative and Operational Automation Form completion and expense report filing. Order processing and delivery tracking. Report generation and data analysis. Finance and HR Management Preparing HR documents and processing employee requests. Invoice verification and payment monitoring. Expense tracking and financial forecasting. OpenAI Operator in Action – Who’s Already Using It? Several prominent companies have integrated OpenAI’s Operator into their operations, demonstrating its versatility across various industries. Instacart: By collaborating with OpenAI, Instacart has enabled customers to utilize Operator for tasks such as ordering groceries. This integration allows users to delegate manual interactions to AI, streamlining the shopping experience. Uber: Uber’s partnership with OpenAI allows customers to use Operator for booking rides. This integration simplifies the ride-hailing process, enabling users to schedule pickups without manual input. eBay: eBay has leveraged Operator to enhance the online shopping experience. Users can instruct Operator to search for products, compare prices, and complete purchases, making e-commerce more efficient. DoorDash: DoorDash’s collaboration with OpenAI enables customers to use Operator for ordering food deliveries. This integration allows users to place orders seamlessly, enhancing the convenience of food delivery services. Stripe: Stripe has tested Operator as a tool to support internal process automation. By interacting with user interfaces, Stripe has optimized financial workflows and data management without requiring complex API integrations. Box: Box has explored the use of Operator to automate customer support processes. Operator’s ability to navigate web interfaces allows it to handle routine inquiries, freeing up human agents for more complex tasks. These real-world applications demonstrate that Operator can be utilized across various industries—from e-commerce and logistics to financial services and SaaS. Its capability to operate user interfaces as a human does make it easier to deploy without costly IT infrastructure changes. How Is Operator Different from Traditional Chatbots and RPA? Artificial intelligence has been transforming business automation for years, with chatbots and Robotic Process Automation (RPA) leading the way in improving efficiency. However, OpenAI’s Operator introduces a new paradigm that combines the best of both worlds while overcoming their imitations. But before we compare these technologies, let’s clarify what chatbots and RPA actually do and why they are relevant in this discussion. What Are Chatbots? Chatbots are AI-powered tools designed to simulate human conversations through text or voice interfaces. They are commonly used in customer support, sales, and virtual assistance. Many chatbots operate on predefined scripts or machine learning models that allow them to respond to inquiries, but they lack the ability to execute complex actions beyond conversations. What Is RPA? Robotic Process Automation (RPA) is a technology that automates repetitive, rule-based tasks across software applications. RPA bots can fill out forms, extract data from emails, process invoices, and transfer data between systems. Unlike chatbots, RPA operates behind the scenes, automating structured workflows but often requiring predefined rules and lacking the flexibility to adapt to unexpected changes. Why Compare Operator to Chatbots and RPA? OpenAI’s Operator is not just another chatbot or RPA tool—it is an intelligent AI agent that interacts with software just like a human would. While chatbots engage in conversations and RPA automates structured workflows, Operator bridges the gap by handling both communication and complex process execution through direct interaction with user interfaces. Now, let’s take a closer look at how these technologies compare: Feature Chatbots RPA Operator User interface interaction ❌ No ✅ Yes, but limited to certain systems ✅ Yes, dynamically Adaptation to new processes ❌ Limited ❌ Requires programming ✅ Self-learning Handling complex tasks ❌ Limited ✅ Yes, but rule-based ✅ Yes, flexibly Integration with various systems ✅ Yes, requires API ✅ Yes, requires scripting ✅ No API needed, operates like a human Operator by OpenAI – How Can AI Transform Your Business? 🚀 Operator by OpenAI is a game-changing technology that takes automation to the next level. With its ability to interact with user interfaces like a human, Operator eliminates manual processes and boosts operational efficiency. At TTMS, we harness the power of AI to transform businesses, combining OpenAI tools with our expertise in process automation, data analytics, and intelligent solutions. Is your company ready for the future of automation? Discover how we can help integrate AI into your organization. 📩 Contact us and explore AI-driven solutions for your business!
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