#Contract Lifecycle Management in Generative AI era

[promtad]

#Insurance2025_Life: Redefining the Future of Insurance

[anilpal]

The Best API Testing Tools for 2025

As we move into an era dominated by interconnected digital ecosystems, APIs (Application Programming Interfaces) have become the backbone of modern software systems. Whether it’s enabling third-party integrations, mobile applications, or microservices-based architectures, APIs are everywhere. Ensuring their reliability, performance, and security is crucial — making API testing one of the most vital phases in the software development lifecycle.

In 2025, the complexity of systems has grown dramatically. The demand for intelligent, scalable, and automation-friendly API testing tools is higher than ever. Amidst this landscape, GenQE.ai emerges as a premier solution, reshaping how teams approach API quality engineering through innovation, AI-driven analytics, and seamless automation.

What Do API Testing Tools Test?

Before diving deeper into what makes a tool like GenQE.ai so impactful, it’s important to understand what API testing tools actually test. API testing isn’t just about checking if the system returns a “200 OK” response. It involves a comprehensive evaluation across multiple dimensions:

1. Functional Testing

This validates whether the API behaves according to specifications. It checks endpoints, request methods, input parameters, and expected outputs. Tools must support testing all HTTP methods (GET, POST, PUT, DELETE, etc.) and ensure accurate responses for various input conditions.

2. Reliability and Uptime

In production, APIs need to handle real-world loads. Reliability testing helps simulate repeated requests to check if the API maintains consistent performance under stress or prolonged usage.

3. Security Testing

Given APIs are often exposed to external developers or applications, security testing is critical. Tests can include authorization (OAuth, JWT), input validation, injection vulnerabilities, and access control validations.

4. Performance and Load Testing

This measures how well an API scales with increased load, concurrent users, and data throughput. Performance metrics like latency, response time, and error rate are key indicators of quality.

5. Data Integrity and Validation

Data consistency is vital, especially when APIs interact with databases or external services. These tests validate that the API sends and receives the correct data, handling edge cases and malformed inputs gracefully.

6. Contract Testing

APIs are often governed by contracts like OpenAPI (Swagger) or RAML. Testing tools validate that the actual API behavior matches the defined contract — ensuring backward compatibility and smooth integration with client applications.

API Testing Tools in 2025

The needs of QA and DevOps teams have evolved rapidly. Modern API testing tools are expected to go far beyond simple request/response checks. Here’s what defines a best-in-class API testing tool in 2025:

1. AI-Driven Test Automation

Manual test creation is time-consuming and prone to human error. Intelligent platforms like GenQE.ai utilize AI to auto-generate test cases based on traffic logs, API documentation, or behavior patterns. This drastically reduces the effort needed to build and maintain test suites.

2. CI/CD Integration

With continuous delivery becoming the standard, API testing must be integrated into every stage of the development pipeline. Tools that offer seamless compatibility with popular CI/CD platforms ensure that tests are triggered automatically with every deployment.

3. Low-Code/No-Code Interface

As testing responsibilities expand beyond traditional QA teams, a low-code or no-code interface allows developers, testers, and business analysts to collaborate on API testing without deep technical expertise.

4. Test Orchestration and Management

Organizations today require a unified view of their test coverage, results, and regression insights. Modern platforms provide test orchestration, centralized dashboards, and historical analytics to track progress and ensure coverage across all API endpoints.

5. Smart Assertions and Self-Healing Tests

Rather than rigid, brittle assertions, intelligent tools offer contextual assertions that adapt based on data type, response pattern, or historical norms. Self-healing tests can adjust to minor changes in API structure without breaking, keeping the test suite robust and reliable.

Why GenQE.ai Leads the Way

In 2025, GenQE.ai stands out as a pioneering platform that redefines API testing through a blend of AI-powered automation, developer-first design, and enterprise-grade scalability.

1. AI-First Test Generation

GenQE.ai automates the creation of test cases by learning from user behavior, historical test runs, and API definitions. It analyzes Swagger/OpenAPI specs, generates test scenarios, and even prioritizes them based on usage frequency and risk level. This dramatically shortens the time-to-test for new APIs and ensures critical paths are always covered.

2. Unified Test Management

With GenQE.ai, teams can manage functional, performance, and security tests from a single interface. Its centralized dashboard provides real-time insights, including pass/fail rates, coverage gaps, and test execution trends. Teams can drill down into individual failures, debug issues collaboratively, and instantly rerun tests post-fix.

3. Shift-Left and Shift-Right Testing

GenQE.ai supports both early-stage testing during development (shift-left) and real-time monitoring in production (shift-right). By correlating test data with production telemetry, the platform ensures continuous quality assurance across the API lifecycle.

4. Scalable Test Execution

Whether running a few tests locally or executing thousands in parallel across distributed environments, GenQE.ai offers cloud-native scalability. Teams can simulate high loads, test geo-distributed APIs, and validate performance under peak conditions — all within the same platform.

5. Collaborative and DevOps-Friendly

GenQE.ai integrates effortlessly with tools across the DevOps stack — GitHub, GitLab, Jenkins, CircleCI, and more. Its collaboration features allow developers and QA engineers to co-author tests, tag issues, assign responsibilities, and maintain traceability from ticket to test to fix.

6. Security and Compliance

GenQE.ai includes built-in security testing modules that detect common API vulnerabilities such as injection flaws, broken authentication, and sensitive data exposure. It also helps enforce regulatory compliance by flagging violations of data handling and encryption standards.

Conclusion

The role of API testing has transformed from a post-development checkpoint to a continuous, intelligent, and automated discipline embedded in every stage of the SDLC. In this landscape, GenQE.ai has emerged as not just a tool but a strategic enabler of API quality engineering.

Its AI-driven approach, robust automation features, and seamless integration into the developer workflow make it an essential platform for organizations seeking to deliver reliable, secure, and high-performance APIs. Whether you’re building microservices, mobile backends, or partner integrations, GenQE.ai ensures your APIs are production-ready from day one — and stay that way through every release.

As businesses continue to scale and evolve in 2025, choosing the right API testing platform will make all the difference. With GenQE.ai, teams don’t just test — they accelerate quality, reduce risk, and innovate faster.

[covalesedigital]

Beyond Traditional CRM: The Distinct Features of IoT-Integrated Solutions

The convergence of Internet of Things (IoT) and Artificial Intelligence (AI) is fundamentally reshaping how businesses connect with customers. With IoT devices projected to grow from 15.9 billion in 2023 to over 32.1 billion by 2030, major industries including utilities, retail, transportation, and government are leading this transformation. In this new era, organisations must reimagine their CRM systems to handle massive data volumes, ensure security compliance, and create adaptive ecosystems that anticipate customer needs in real-time.

Key Features of IoT-Based CRM

Customer Information

The cornerstone of IoT-integrated CRM is its ability to capture and analyse comprehensive customer information through connected devices. This information encompasses number of smart devices a customer has subscribed to., A robust IoT-integrated CRM will accumulate all this information and transform it into meaningful insights.

For example:

In a B2C scenario, a person using a smart watch or fitness tracker will have access to vital statistics through their app, health indicators and customised health advice. This data creates a comprehensive customer profile in the CRM.

In a B2B scenario, smart building management companies can capture information like power consumption patterns and solar panels performance. AI integration provides predictive insights for maintenance and optimisation.

Product Catalogue

The modern IoT-integrated CRM requires a dynamic product catalogue supporting IoT services, plans, and packages, with the capability of bundling this IoT products and services with traditional telco data plans. CRM systems integrated with IoT data can track usage patterns and suggest products or services that align with customer needs through AI-based algorithms.

Sales Inventory Management

Efficient management of the lifecycle of IoT based devices and inventories including CCTVs, cameras, sensors, wearable devices and other IoT-based equipment is crucial. The sales inventory module should generate device inventories and manage status values such as active, inactive, allocated, and switched off.

Campaigns and Loyalty

The IoT-integrated CRM should run specific campaigns to attract new customers and reward them for using the services. For example: A smart home company monitors how customers’ use their connected devices (e.g., smart lights, thermostats, or security cameras). When software updates are pending, the CRM can trigger an automated email campaign encouraging them to upgrade their devices or to register for an AMC contract.

Data Security and Privacy

IoT devices collect vast amounts of sensitive and personal information. Due to the enormous volume, this data is generally stored in IoT data warehouses or data lakes which the CRM system can integrate to provide intelligent data analysis. Crucially, it’s crucial to handle and store this data securely and to abide by regulatory and data privacy laws of each country, such as GDPR in the European region and ACMA in Australian region

Cloud-Based Scalability

Modern IoT-integrated CRM platforms require scalable architecture leveraging:

Microservices Architecture: Breaking the CRM into modular, independent services

Independent Scaling: Managing increasing data volumes efficiently

Dynamic Resource Management: Using containers and Kubernetes

Edge Computing Integration: Enabling local data processing and real-time analytics

IoT Device Monitoring

With multiple edge devices in an IoT ecosystem such as sensors, smart devices, and machines, the IoT Gateway becomes extremely crucial to bridge the gap between the edge devices and CRM systems.

IoT device monitoring through a CRM system enables businesses to manage and track the performance, status, and health of connected devices in real time. This allows CRM systems to trigger proactive customer support actions, such as sending alerts or maintenance notifications.

Smart Farming Use Case with IoT-Integrated CRM

Consider a company that provides agricultural equipment like drones, sensors, irrigation systems and advisory services to farmers

The system enables:

Real-time monitoring of soil conditions and crop health

Automated alerts for anomalies

Integration with customer profiles for personalised insights

Mobile access to farm management

Challenges in IoT-Integrated CRM

Managing High Data Volumes: Processing and analysing massive data requires robust infrastructure.

Data Privacy and Security: Safeguarding sensitive information and ensuring compliance.

Integration Complexity: Connecting diverse systems seamlessly.

Conclusion

The fusion of IoT and CRM systems provides businesses with unparalleled opportunities for personalised customer engagement. Industry leaders like Salesforce IoT Cloud, Microsoft Dynamics 365 IoT, and SAP Customer Experience are enabling organisations to integrate IoT data for actionable insights and enhanced customer experiences.

Take the Next Step in Your Digital Transformation Journey

Ready to revolutionise your customer relationships with IoT-integrated CRM solutions? Contact our IoT solutions team at reachus@covalensedigital.com to discuss your requirements.

To know more visit: Covalensedigital

Visit: Covalensedigital LinkedIn

Follow Us on: Covalensedigital Twitter

[johnjjames]

Intelligent Document Processing: Healthcare, Invoice Automation & Logistics Solutions

In an era where efficiency and accuracy are paramount, businesses across various sectors are increasingly turning to intelligent document processing (IDP) technologies. These technologies leverage artificial intelligence (AI) and machine learning (ML) to automate the extraction, classification, and processing of information from documents. At Artificio, we specialise in providing innovative IDP solutions tailored to meet the specific needs of industries such as healthcare, finance, and logistics. This blog explores the transformative impact of intelligent document processing in these sectors, focusing on its applications in healthcare, invoice automation, and logistics.

Intelligent Document Processing in Healthcare

The healthcare industry generates vast amounts of data daily, from patient records and insurance claims to medical billing and compliance documentation. Managing this data efficiently and accurately is crucial for ensuring patient safety, maintaining regulatory compliance, and optimising operational efficiency. Intelligent document processing in healthcare offers a robust solution to these challenges.

IDP technology automates the extraction of critical information from various documents, including handwritten notes, electronic health records (EHRs), and lab reports. This automation reduces the manual effort required to process these documents, minimising the risk of errors that can occur during data entry. For instance, Artificio's IDP solutions can extract patient information, medical history, and treatment plans, integrating this data seamlessly into EHR systems. This not only speeds up the processing time but also ensures that healthcare providers have access to accurate and up-to-date information, which is crucial for patient care.

Moreover, intelligent document processing can enhance data privacy and security by automating the identification and redaction of sensitive information, such as social security numbers and financial data, in compliance with regulations like HIPAA. By automating these processes, healthcare organisations can reduce their risk of data breaches and ensure compliance with stringent data protection laws.

The Role of Invoice Automation Software

Invoice processing is a critical function for any business, impacting cash flow, vendor relationships, and financial reporting. However, traditional invoice processing methods are often time-consuming and prone to errors, particularly in manual data entry and approval workflows.  Invoice automation software addresses these challenges by streamlining the entire invoice lifecycle, from receipt to payment.

Artificio's invoice automation software utilises AI and ML algorithms to automatically capture and interpret invoice data, regardless of the format or source. This includes extracting details such as invoice numbers, dates, line items, and amounts due. The software then validates the extracted data against purchase orders and contracts, flagging any discrepancies for review. This automated validation process not only accelerates the approval workflow but also reduces the likelihood of fraudulent or duplicate payments.

Furthermore, our invoice automation solutions integrate with existing enterprise resource planning (ERP) systems, ensuring that all financial data is updated in real-time. This integration provides businesses with greater visibility into their accounts payable processes, enabling better cash flow management and financial forecasting. By reducing the manual effort involved in invoice processing, businesses can allocate their resources more efficiently, focusing on strategic activities rather than administrative tasks.

Document Automation for Logistics

The logistics industry is characterised by complex supply chains and the need for accurate, timely information to manage the movement of goods. Document automation for logistics plays a crucial role in streamlining these operations by automating the processing of key documents such as bills of lading, customs declarations, and delivery receipts.

Artificio's document automation solutions for logistics leverage advanced OCR (optical character recognition) and natural language processing (NLP) technologies to extract and process data from a wide range of documents. This includes handwritten notes, printed forms, and digital files. By automating the extraction of data such as shipment details, cargo descriptions, and tracking numbers, our solutions enable logistics providers to improve accuracy and reduce processing times.

In addition to data extraction, our document automation solutions offer workflow automation capabilities, routeing documents to the appropriate stakeholders for review and approval. This ensures that critical information is disseminated quickly and efficiently, reducing delays in the supply chain. For instance, customs documents can be automatically routed to compliance officers for verification, expediting the clearance process and minimising the risk of costly delays.

Document automation also enhances traceability and transparency in the logistics industry. By digitising and centralising documents, companies can maintain a comprehensive record of transactions and communications, which is essential for auditing and compliance purposes. This level of transparency is increasingly important as businesses strive to meet regulatory requirements and customer expectations for ethical and responsible supply chain management.

The Future of Intelligent Document Processing

The adoption of intelligent document processing technologies is poised to grow as businesses recognize the benefits of automation in improving efficiency, accuracy, and compliance. At Artificio, we continue to innovate our IDP solutions, incorporating the latest advancements in AI and ML to meet the evolving needs of our clients.

In the future, we anticipate further integration of IDP with other technologies such as blockchain and the Internet of Things (IoT). For example, integrating IDP with blockchain could enhance the security and traceability of documents, providing an immutable record of all transactions. Similarly, the integration of IoT devices with IDP systems could automate the collection and processing of data from physical assets, such as tracking the condition of goods in transit.

As businesses continue to navigate an increasingly digital landscape, the ability to process and manage information efficiently will be a key differentiator. Intelligent document processing offers a scalable and adaptable solution, capable of handling the growing volume and complexity of data in various industries. By partnering with Artificio, businesses can leverage cutting-edge IDP technologies to optimize their operations, reduce costs, and enhance their competitive advantage.

In conclusion, intelligent document processing is transforming how industries such as healthcare, finance, and logistics manage and utilize information. By automating manual processes, these technologies enable businesses to operate more efficiently, accurately, and securely. At Artificio, we are committed to providing innovative IDP solutions that empower our clients to achieve their business objectives and thrive in a rapidly changing world.

[shristisahu]

Exploring the Fusion of Procurement and Machine Learning: Pioneering a Path to Competitive Advantage

Originally Published on SpendEdge : Exploring the Procurement Landscape with Machine Learning 

Key Insights:

Procurement mastery requires a deep understanding of supplier dynamics, sourcing strategies, and regulatory compliance. Machine Learning (ML) emerges as a game-changer, automating tasks, enriching decision-making, and refining processes like spend analysis and contract management. SpendEdge stands at the forefront, offering cutting-edge market intelligence services, guiding companies towards optimal suppliers, and leveraging market insights for strategic procurement. Under SpendEdge's guidance, a food and beverage retailer experienced remarkable efficiency gains in inventory management and vendor relations. The procurement landscape is a dynamic ecosystem, intertwining supplier dynamics, regulatory nuances, and sourcing strategies, shaping the acquisition of goods and services. A comprehensive understanding of this landscape is crucial for cost optimization and supply chain efficiency.

Enter Machine Learning (ML), heralding a new era in procurement. ML's prowess in automating tasks and generating insights empowers procurement teams to focus on strategic initiatives. By nurturing supplier relationships, navigating intricate contracts, and embracing data-driven decision-making, ML drives corporate profitability.

Leveraging ML alongside technologies like AI and robotic process automation, procurement professionals streamline pivotal processes like spend analysis and contract management. This enables precise spend classification, fostering insightful learning from procurement data and enhancing operational efficiency.

Applications of machine learning in procurement:

Spend management: ML optimizes spend analysis, revealing cost-saving opportunities and refining procurement decisions. Supplier identification and management: ML enhances supplier evaluation, strengthens risk management, and fosters productive relationships. Contract management: ML ensures compliance and identifies avenues for optimization, refining the contract lifecycle. Compliance management: ML automates compliance monitoring, mitigating risks, and enhancing accuracy. Procurement entities increasingly turn to ML for process automation and deeper insights. ML's adaptive capacity sets it apart, offering continuous improvement and adaptability.

How SpendEdge Elevates Procurement with Market Intelligence:

Supplier intelligence: SpendEdge utilizes data-driven insights to pinpoint optimal suppliers, enhancing selection and market acumen. Spend analysis: SpendEdge facilitates comprehensive spend management, empowering informed decision-making and cost control. Performance evaluation: SpendEdge conducts performance evaluations, enabling data-driven supplier assessments and fostering accountability.

Unique Applications: Machine Learning in Procurement

Spend Analysis: ML uncovers concealed spending insights, reinforcing fiscal prudence. Sourcing: ML identifies and evaluates suppliers with unparalleled precision. Risk Mitigation: ML flags supply chain vulnerabilities, fortifying resilience. Contract Management: ML ensures adherence to agreements and identifies optimization prospects.

SpendEdge's Triumph:

SpendEdge aided a US-based food and beverage retailer grappling with inventory management. Through meticulous analysis, SpendEdge recommended technology solutions and suitable vendors, significantly enhancing procurement processes and inventory management.

Why Opt for SpendEdge?

Embark on the journey to procurement excellence today!

Conclusion:

Amidst evolving supply chain disruptions, electronic sourcing (e-sourcing) emerges as a pivotal solution for organizations seeking agility and efficiency in procurement. By leveraging e-sourcing tools and software, businesses can streamline supplier interactions, drive cost savings, and enhance process transparency. However, effective implementation demands addressing challenges such as standardization, investment costs, and regulatory compliance. With the backing of expert advisory services like SpendEdge, organizations can navigate these challenges and unlock the full potential of e-sourcing to optimize procurement operations and drive sustainable growth. #ProcurementInnovators

Contact us.

[kanchankhatanaa]

Harnessing the Future: The Role of Artificial Intelligence in Contract Drafting, Review, and Management

In the dynamic landscape of modern business, the integration of artificial intelligence (AI) tools has become increasingly prevalent, revolutionizing traditional processes and enhancing efficiency across various sectors. One significant domain where AI is making a transformative impact is in contract drafting, review, and management. This article explores the evolving role of AI in the legal sphere and its specific applications in optimizing the life cycle of contracts. AI in Contract Drafting:

Automated Contract Generation: • AI-powered tools are capable of automating the creation of contracts by analyzing predefined templates and extracting relevant information from diverse data sources. This streamlines the drafting process, reducing manual labor and ensuring consistency in language and formatting.

Natural Language Processing (NLP): • NLP algorithms enable AI systems to comprehend and interpret human language. In the context of contract drafting, NLP facilitates the analysis of complex legal language, ensuring accuracy and aiding in the creation of contracts that align with legal best practices.

Clause Recommendations and Optimization: • AI tools can provide real-time suggestions for clauses based on the context of the contract being drafted. These recommendations are often derived from a vast repository of legal knowledge, contributing to the optimization of contractual language and terms. AI in Contract Review:

Contract Analysis and Due Diligence: • AI algorithms excel in processing large volumes of data, making them ideal for contract review during due diligence processes. These tools can quickly identify relevant clauses, potential risks, and inconsistencies, significantly expediting the review phase.

Risk Assessment and Compliance Checking: • AI can assess contracts for potential risks and compliance issues by cross-referencing the content against legal databases, regulatory requirements, and internal policies. This proactive approach aids in identifying and mitigating risks before they escalate.

Contextual Understanding: • Advanced AI systems possess the ability to understand the context in which contractual terms are used. This contextual understanding enhances the accuracy of contract review, ensuring that the AI can grasp the nuances of legal language and identify subtle distinctions. AI in Contract Management:

Automated Workflow and Approval Processes: • AI-driven contract management systems can automate workflow processes, ensuring that contracts move seamlessly through approval stages. This not only accelerates the contract lifecycle but also reduces the risk of bottlenecks and delays.

Monitoring and Alerts: • AI tools can continuously monitor contracts for key events, milestones, and deadlines. Automated alerts can be triggered to notify relevant stakeholders of upcoming renewals, expirations, or other critical dates, enhancing proactive contract management.

Data Analytics for Decision-Making: • AI analytics can provide valuable insights into contract performance, vendor relationships, and overall contractual efficiency. This data-driven approach empowers organizations to make informed decisions, optimize contract terms, and enhance strategic planning. Conclusion: The integration of AI tools in contract drafting, review, and management signifies a paradigm shift in the legal landscape. By harnessing the capabilities of artificial intelligence, legal professionals can not only streamline their workflows but also enhance the quality, accuracy, and strategic value of the contracts they handle. As AI continues to evolve, its role in the legal domain is poised to expand, ushering in a new era of efficiency, innovation, and precision in contract-related processes.

[blockchaincouncil]

Blockchain and AI in Energy: The Next Wave of Disruption

Blockchain technology and artificial intelligence (AI) are two game changers that have made waves in a variety of industries in recent years. While each of these technologies has the potential to disrupt existing systems and processes on its own. Their combination in the energy industry is creating a tremendous force for change.

The convergence of blockchain technology and artificial intelligence is set to transform how energy is generated, used, and controlled, ushering in a new era of efficiency, transparency, and decentralization. We also believe that this combination will accelerate the development of such autonomous business models, as well as the digital transformation of industrial enterprises.

Blockchain and AI's Role

Blockchain, which is frequently associated with cryptocurrencies such as Bitcoin, is a decentralized and immutable ledger that enables secure and transparent transactions without the use of intermediaries. AI, on the other hand, refers to the simulation of human intelligence in machines, allowing them to learn, reason, and make decisions autonomously. When these two technologies are combined in the energy sector, they have the potential to address some of the industry's most pressing challenges.

One of the key areas where blockchain and AI can drive disruption in the energy sector is energy grid management. Historically, centralised energy grids have struggled to handle the increasing complexity of integrating renewable energy sources and managing demand and supply dynamics. Energy grids can become more efficient, resilient, and flexible by leveraging the decentralised nature of blockchain and the predictive capabilities of AI.

Blockchain can enable the creation of decentralised energy marketplaces in which consumers and prosumers (those who consume and produce energy) can transact directly with one another. Smart contracts powered by blockchain technology can automate and enforce the terms of these transactions, ensuring transparency, security, and trust. AI algorithms can analyse energy consumption patterns and optimise energy trading, matching supply with demand in real time and reducing waste.

Furthermore, blockchain and AI can help with the integration of distributed energy resources (DERs) into the grid. DERs, such as solar panels and wind turbines, generate electricity locally and can feed excess power back into the grid. However, managing the integration of DERs at scale is a difficult task. Blockchain-based platforms can enable the secure and transparent tracking of energy generated by DERs. Simultaneously, AI algorithms can forecast and balance the fluctuating supply from these distributed sources, ensuring grid stability.

Another area where blockchain and AI can cause disruption is in energy supply chain management. Currently, tracing the origin and authenticity of energy resources such as oil, gas, and minerals is a difficult and opaque process. It is now possible to trace the entire lifecycle of energy resources, from extraction to consumption, by utilising blockchain's immutable and transparent ledger. AI algorithms can analyse this data to detect anomalies, ensure regulatory compliance, and optimise the supply chain for efficiency.

Furthermore, blockchain and AI can improve energy efficiency by enabling the development of decentralised energy systems. Traditional energy systems suffer significant transmission and distribution losses as electricity travels long distances from centralised power plants to end users. These losses can be reduced by deploying decentralised energy systems in which energy is generated and consumed locally. AI algorithms can analyse smart metre and sensor data to optimise energy consumption patterns, reducing waste and increasing efficiency.

In addition to transforming the operational aspects of the energy sector, blockchain and AI can empower consumers to actively participate in the energy market. Blockchain-based platforms can enable the creation of peer-to-peer energy trading networks in which individuals can buy and sell energy directly with one another. AI algorithms can provide personalised energy recommendations and insights, allowing consumers to make more informed decisions about their energy usage and cost optimisation.

The convergence of blockchain and AI also creates opportunities for new business models in the energy sector. For example, blockchain-based tokens can be used to incentivize the generation and consumption of renewable energy. Energy producers can tokenize their excess energy and sell it to consumers, who can then use these tokens to pay for their energy consumption.

This creates a new form of economic exchange that not only promotes renewable energy generation but also empowers individuals to become active participants in the energy market. Blockchain technology, by tokenizing energy, enables the development of decentralised energy financing platforms. These platforms can facilitate crowdfunding for renewable energy projects, allowing individuals to invest in clean energy initiatives and share in the financial returns.

Furthermore, the combination of blockchain and AI has the potential to revolutionise the way energy data is collected, analysed, and shared. Currently, energy data is fragmented and siloed, making it difficult for stakeholders to access and apply valuable insights. Energy data can be stored and shared in a transparent and auditable manner thanks to blockchain's decentralised and secure ledger. AI algorithms can then process this data to derive meaningful insights such as demand patterns, consumption trends, and predictive maintenance requirements.

This improved data accessibility and analysis can lead to more informed decision-making and better energy planning. Utilities can optimise their energy generation and distribution strategies, lowering costs and reducing environmental impact. Energy consumers can gain greater visibility into their energy usage, allowing them to make more informed decisions about energy efficiency and conservation.

Energy Sector Blockchain and AI Challenges

However, the convergence of blockchain and AI in the energy sector is not without challenges.

One of the major challenges is the scalability of blockchain technology. As the number of transactions and data points grows, blockchain networks may experience speed and processing power limitations. Scalability solutions, such as off-chain transactions and layer-two protocols, are being developed to address these challenges and enable widespread adoption of blockchain in the energy sector.

Another issue is the interoperability of different blockchain platforms. To fully realise the potential of blockchain and AI in energy, it is critical to establish standards and protocols that enable seamless data exchange and collaboration across multiple blockchain networks. Industry consortia and collaborative efforts are underway to address these interoperability challenges and promote the development of an interconnected energy ecosystem.

Furthermore, the implementation of blockchain and AI in the energy sector necessitates collaboration among various stakeholders, including energy companies, regulators, technology providers, and consumers. It is critical to create a regulatory environment that promotes innovation while protecting data privacy, security, and compliance. Governments and regulatory bodies play a critical role in creating an ecosystem that encourages the adoption of disruptive technologies.

Conclusion

The convergence of blockchain and AI in the energy sector has enormous potential to disrupt traditional systems and processes. Blockchain and AI can drive the next wave of disruption in the energy industry by enabling decentralised energy marketplaces, optimising grid management, increasing supply chain transparency, and empowering consumers.

However, addressing scalability, interoperability, and regulatory issues will be critical to reaping the full benefits of these technologies. As the energy sector continues its transition to a cleaner and more sustainable future, blockchain and AI will play critical roles in shaping the energy landscape of tomorrow.

If you want to learn more about AI and add more stars to your resume, Blockchain Council is a great place to start. The Blockchain Council's newly launched AI certification and cryptocurrency degree programmes have been meticulously designed to meet the industry's needs. Furthermore, these programmes provide theoretical and practical knowledge while remaining cost-effective. If you're looking for online blockchain education programmes or other related courses, visit Blockchain Council's website.

[cpqsoftware]

How to Improve Customer Experiences with CPQ?

Manufacturers will expand in 2023 and beyond by supporting short-notice production runs, establishing more significant product quality standards, and releasing next-generation goods more adaptable to customer needs.

All thanks to CPQ Technology!

CPQ resources have enabled manufacturers to deliver a better customer experience. And don’t forget only satisfying customers’ bring more sales. Satisfied customers become your brand advocates and quickly leave great reviews on social media channels that ultimately get more business.

By cutting down product quoting time and making the process more smooth, CPQ resources completely turned the manufacturing industry and left behind happy clients only.

Not only this, CPQ technology made it achievable to create more flexible pricing and product bundles/configurations. This builds trust and makes customers more loyal to your brand despite the “Switching Economy.”

Let’s discuss in detail how CPQ resources improve customer experience.

Four ways CPQ improves customer experience

There are many advantages to using CPQ technology for improving customer experience. Here are a few reasons how using CPQ customer experience for the eCommerce businesses can enhance customer loyalty and engagement:

1. Offer faster results:

CPQ system with a virtual product configurator speeds up the manufacturing process and B2B purchases, fulfilling modern customer expectations. It also helps in complex quotes by generating them in seconds. If a particular quote doesn’t work for the customer, a business can generate another one in real time. While CPQ is often linked with manufacturing due to the complexity of designing big projects, it can also accommodate speed and direction to industries that facilitate services and subscriptions, thereby expanding its market.

With CPQ, it has become easier for customers to buy complex products online. KBMax Product Configurator CPQ enables customers to design and customize the product from the beginning of the manufacturing process.

2. Quotes accuracy:

Despite speedy responses, it also builds customer trust by giving accurate quotes. Previously errors in quotes and configurations were a widespread problem that customers usually faced, leading to a bad experience that caused a customer to switch. However, today with the help of Contract Lifecycle Management (CLM), businesses are streamlining the process of the final contract intervention on terms and pricing so that the intervention process doesn’t cause a painful experience.

AI-powered CPQ software engine facilitates dynamic quoting fashions. It leverages data to recognize buying patterns and examines price trends to provide real-time offer recommendations that closely match customer expectations.

3. Hyper personalization:

In the digital era, personalization has an imperative feature that helps in improving customer experience with your brand. If you don’t have integrated CPQ till now in your business process, ask for a CPQ demo, as this is the only solution that allows personalization more profoundly. For instance, companies can offer specific pricing and catalogs tailored just for them. Partners can have their catalogs suited to their precise needs. Personalization is vital for the manufacturing industry to let customers know that you care for them and to make them feel valued.

4. Better data analytics with Artificial Intelligence:

With analytics, B2B companies can make better business decisions by tracking their customer’s digital footprints. CPQ provides the perfect platform for an organization to launch a comprehensive analytics campaign. It provides an in-depth analysis of sales effectiveness. AI-powered CPQ systems provide optimal pricing along with recommended cross-sell and up-sell opportunities. It empowers the rep with granular insights and allows them to handle the deal more effectively. This improves customer journey, eliminating sales rep’s manual work and allowing them to work closely with clients. Following the customer’s buying journey is critical. CPQ can help you build the connections that today’s buyers expect.

Conclusion

Successful businesses are known for offering engaging and best customer experiences and never thinking twice about going the extra mile to explore all-new ways to satisfy customers.

CPQ software becomes integral to all B2B businesses by aligning all business processes and teams to scale. Organizations usually work unproductively due to resources being in the wrong positions or process defenses negatively influencing momentum.

But no more silos as KBMax CPQ has lined many eCommerce solutions so that companies get more out of their resources.

[rollinbrigittenv8]

Events Industry Joins the Influencer Trend — Meetings Innovation Report

The Atout France booth at IMEX Frankfurt 2017. Atout France

Skift Take: More convention bureaus like Atout France should adopt an influencer campaign strategy to drive a higher level of digital engagement around both industry and non-industry events.

— Greg Oates

The Future of Meetings & Events

Atout France, the country’s national tourism development agency, launched a 5-month influencer campaign in the spring, leading up to the IMEX Frankfurt meetings industry trade show last month.

The agency contracted London-based Irina Trofimovskaya, founder of The MICE Blog, to drive higher online and offline engagement around the #BizInFrance hashtag on Twitter and LinkedIn.

This is new for a destination to use influencers to engage meeting planners, at least at this scale. Atout France reported both a rise in social media interactions before IMEX, and a jump in meeting planners visiting all of the French partners during the show.

Jerome Poulalier, manager of Atout France’s meetings department in Frankfurt, said, “Our other goals included increasing awareness of French destinations beyond the most popular cities, extending the engagement lifecycle beyond the IMEX Frankfurt event, and creating more sharable, visual content.”

— Greg Oates

Subscribe to the Skift Meetings Innovation Report

Social Quote of the Week

“.@sxsw is the world’s fair of the future, @MayorAdler. #Austin #SXSW @usmayors”

— Santa Fe mayor @javiermgonzales on Twitter

Destination Disruptors

France Tests Social Media Influencer Strategy to Engage Meetings Industry: Lots of destinations work with influencers to drive leisure traffic, but France’s national tourism board is among the first to contract a meetings and events specialist to engage conference planners. This should inspire other countries and cities to try the same because it positions them as digital innovators to younger audiences. Read more at Skift

Announcing the Cities Summit at SXSW 2018: The South by Southwest conference in Austin is launching a new series of sessions next year focusing on the rise of cities as, what Austin Mayor Steve Adler calls: “incubators of the future.” As such, urban destinations are evolving as innovation platforms with a deep knowledge base across different growth sectors. Conference planners can leverage that to educate and inspire attendees, rather than cities merely playing the role of venue and experience providers. Read more at SXSW

U.S. Conference of Mayors Launches New Mayors Agenda for The Future Strategy: Bipartisan collaboration was the big theme at the annual U.S. Conference of Mayors last week in Miami Beach. The event produced the new MayorsAgenda.com portal and strategy paper focusing on four priorities: Safety, infrastructure, workforce, and inclusivity. You could say the meetings industry has the same four priorities. The value here for planners and the industry at large is the section on inclusivity. Download the paper at Mayors Agenda

Next Generation Meetings UX

PCMA Educational Conference Partnered With Innovative New York Venues: Representatives from organizations including Stanford University, Microsoft, Disney, and others hosted offsite sessions during PCMA’s annual industry education show in New York. By integrating the city’s innovation economy into the event programming, PCMA provided a more diverse platform for attendees to explore a wider range of creative thought leaders and venues. Read more at Convene

The Experience Movement: How Millennials are Bridging Cultural & Political Divides Offline: According to a new Eventbrite report, 79 percent of Millennials in 2017 agree that attending live events makes them feel more connected to other people, their communities, and the world, which is significantly higher than 69 percent who reported the same in 2014. Read more at Eventbrite

Event Manager Blog Publishes New Event Sponsorship Report: Event sponsors are looking for more out-of-the-box ideas to make sponsorship dollars extend further and drive higher return on investment. According to the report, “Sponsors are over the regular ideas of ads in event programs, social media mentions and followers, etc. They now look for more client presence and impact pre, during and post events.” Read more at Event Manager Blog

What Science Can Teach Us About Capturing an Audience’s Attention: According to new research, event speakers should lead with stories and back them up with data, versus the other way around. Neuro-economist Paul Zan says, “Character-driven stories with emotional content result in a better understanding of the key points a speaker wishes to make and enable better recall of these points weeks later.” Read more at Inc

Top Trends of London Tech Week 2017: Some of the big themes coming out of London Tech Week this month include: Brexit isn’t dampening the flood of tech talent into London; new life-like robots show increasing sophistication in artificial intelligence; tech companies are getting creative to attract young tech workers; and the growing conversation around 5G is making people imagine how we’ll actually use our devices in 2020. Read more at OFF3R

In the AI Age, Being Smart Will Mean Something Completely Different: The central premise here is that people will need to develop emotional intelligence and a creative, collaborative mindset to succeed in the era of artificial intelligence. According to the author: “What is needed is a new definition of being smart, one that promotes higher levels of human thinking and emotional engagement. The new smart will be determined not by what or how you know, but by the quality of your thinking, listening, relating, collaborating, and learning.” Read more at Harvard Business Review

Subscribe

The Skift Meetings Innovation Report is curated by Skift editor Greg Oates [go@skift.com]. The newsletter is emailed every Wednesday.

Subscribe to the Skift Meetings Innovation Report

[touristguidebuzz]

Events Industry Joins the Influencer Trend — Meetings Innovation Report

The Atout France booth at IMEX Frankfurt 2017. Atout France

Skift Take: More convention bureaus like Atout France should adopt an influencer campaign strategy to drive a higher level of digital engagement around both industry and non-industry events.

— Greg Oates

The Future of Meetings & Events

Atout France, the country’s national tourism development agency, launched a 5-month influencer campaign in the spring, leading up to the IMEX Frankfurt meetings industry trade show last month.

The agency contracted London-based Irina Trofimovskaya, founder of The MICE Blog, to drive higher online and offline engagement around the #BizInFrance hashtag on Twitter and LinkedIn.

This is new for a destination to use influencers to engage meeting planners, at least at this scale. Atout France reported both a rise in social media interactions before IMEX, and a jump in meeting planners visiting all of the French partners during the show.

Jerome Poulalier, manager of Atout France’s meetings department in Frankfurt, said, “Our other goals included increasing awareness of French destinations beyond the most popular cities, extending the engagement lifecycle beyond the IMEX Frankfurt event, and creating more sharable, visual content.”

— Greg Oates

Subscribe to the Skift Meetings Innovation Report

Social Quote of the Week

“.@sxsw is the world’s fair of the future, @MayorAdler. #Austin #SXSW @usmayors”

— Santa Fe mayor @javiermgonzales on Twitter

Destination Disruptors

France Tests Social Media Influencer Strategy to Engage Meetings Industry: Lots of destinations work with influencers to drive leisure traffic, but France’s national tourism board is among the first to contract a meetings and events specialist to engage conference planners. This should inspire other countries and cities to try the same because it positions them as digital innovators to younger audiences. Read more at Skift

Announcing the Cities Summit at SXSW 2018: The South by Southwest conference in Austin is launching a new series of sessions next year focusing on the rise of cities as, what Austin Mayor Steve Adler calls: “incubators of the future.” As such, urban destinations are evolving as innovation platforms with a deep knowledge base across different growth sectors. Conference planners can leverage that to educate and inspire attendees, rather than cities merely playing the role of venue and experience providers. Read more at SXSW

U.S. Conference of Mayors Launches New Mayors Agenda for The Future Strategy: Bipartisan collaboration was the big theme at the annual U.S. Conference of Mayors last week in Miami Beach. The event produced the new MayorsAgenda.com portal and strategy paper focusing on four priorities: Safety, infrastructure, workforce, and inclusivity. You could say the meetings industry has the same four priorities. The value here for planners and the industry at large is the section on inclusivity. Download the paper at Mayors Agenda

Next Generation Meetings UX

PCMA Educational Conference Partnered With Innovative New York Venues: Representatives from organizations including Stanford University, Microsoft, Disney, and others hosted offsite sessions during PCMA’s annual industry education show in New York. By integrating the city’s innovation economy into the event programming, PCMA provided a more diverse platform for attendees to explore a wider range of creative thought leaders and venues. Read more at Convene

The Experience Movement: How Millennials are Bridging Cultural & Political Divides Offline: According to a new Eventbrite report, 79 percent of Millennials in 2017 agree that attending live events makes them feel more connected to other people, their communities, and the world, which is significantly higher than 69 percent who reported the same in 2014. Read more at Eventbrite

Event Manager Blog Publishes New Event Sponsorship Report: Event sponsors are looking for more out-of-the-box ideas to make sponsorship dollars extend further and drive higher return on investment. According to the report, “Sponsors are over the regular ideas of ads in event programs, social media mentions and followers, etc. They now look for more client presence and impact pre, during and post events.” Read more at Event Manager Blog

What Science Can Teach Us About Capturing an Audience’s Attention: According to new research, event speakers should lead with stories and back them up with data, versus the other way around. Neuro-economist Paul Zan says, “Character-driven stories with emotional content result in a better understanding of the key points a speaker wishes to make and enable better recall of these points weeks later.” Read more at Inc

Top Trends of London Tech Week 2017: Some of the big themes coming out of London Tech Week this month include: Brexit isn’t dampening the flood of tech talent into London; new life-like robots show increasing sophistication in artificial intelligence; tech companies are getting creative to attract young tech workers; and the growing conversation around 5G is making people imagine how we’ll actually use our devices in 2020. Read more at OFF3R

In the AI Age, Being Smart Will Mean Something Completely Different: The central premise here is that people will need to develop emotional intelligence and a creative, collaborative mindset to succeed in the era of artificial intelligence. According to the author: “What is needed is a new definition of being smart, one that promotes higher levels of human thinking and emotional engagement. The new smart will be determined not by what or how you know, but by the quality of your thinking, listening, relating, collaborating, and learning.” Read more at Harvard Business Review

Subscribe

The Skift Meetings Innovation Report is curated by Skift editor Greg Oates [go@skift.com]. The newsletter is emailed every Wednesday.

Subscribe to the Skift Meetings Innovation Report