#CRM Application

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How To Select Best CRM Application Development Company?

Looking for a reliable CRM development company in New York? We offer custom CRM solutions tailored to your business needs. Enhance customer relationships and streamline your processes with our expert team. Contact us today!

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Colan Infotech is a leading Custom Software Development Company offering innovative solutions to various business problems. We are an ISO certified organisation having expertise in developing custom web applications, mobile apps, desktop applications, ERP systems, CRM, CMS, eCommerce websites, etc.

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[iqstreamtech]

Become a Salesforce Developer with Expert Training in Bangalore

Salesforce is a leading cloud-based customer relationship management (CRM) platform used by businesses worldwide to manage customer data, sales, and marketing efforts. As demand for Salesforce expertise continues to rise, becoming a skilled Salesforce developer can open up countless career opportunities. IQ Stream Technologies offers specialized Salesforce Developer Training in Bangalore, designed to equip you with the knowledge and hands-on experience needed to thrive in this dynamic field.

What is Salesforce Developer Training?

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IQ Stream Technologies provides a structured curriculum that is designed to cover both theoretical concepts and practical, real-world use cases. By the end of the training, you'll be ready to create custom Salesforce applications, automate workflows, and integrate Salesforce with other business systems.

Why Choose Salesforce Developer Training in Bangalore at IQ Stream Technologies?

Comprehensive Curriculum: Learn the fundamentals of Salesforce development, including Apex programming, Visualforce pages, Lightning components, and Salesforce architecture.

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Experienced Trainers: Learn from certified Salesforce developers with extensive industry experience who provide personalized instruction and support.

Job Placement Assistance: IQ Stream Technologies provides career support, helping you connect with potential employers through job placement assistance.

Flexible Learning: The Salesforce Developer Training program in Bangalore is available both in-person and online, allowing you to choose a format that suits your schedule and learning style.

If you're looking to build a rewarding career in Salesforce development, IQ Stream Technologies is the perfect choice for training. Enroll in our Salesforce Developer Training in Bangalore today and start your journey toward becoming a certified Salesforce developer.

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Don Schuerman, CTO at Pegasystems – Interview Series

New Post has been published on https://thedigitalinsider.com/don-schuerman-cto-at-pegasystems-interview-series/

Don Schuerman, CTO at Pegasystems – Interview Series

Don Schuerman is chief technology officer and vice-president of product marketing at Pegasystems, responsible for Pega’s platform and customer relationship management (CRM) applications.

He has 20 years’ experience delivering enterprise software solutions for Fortune 500 organisations, with a focus on digital transformation, mobility, analytics, business process management, cloud and CRM.

Pegasystems offers a robust platform designed to help organizations achieve business-transforming results through real-time optimization. The platform enables clients to address key business challenges using enterprise AI decision-making and workflow automation, including personalizing customer engagement, automating services, and improving operational efficiency. Established in 1983, Pegasystems has developed a scalable and flexible architecture that supports enterprises in meeting current customer demands while adapting to future needs.

Given your extensive experience as CTO at Pegasystems, how does Pega GenAI distinguish itself in the rapidly evolving landscape of generative AI for enterprises?

Pega has been innovating AI solutions for years, including exploring generative AI well before it broke into the mainstream. I think there are three things that set us apart:

First, we’re not just speeding processes, we’re driving innovation. Most enterprise software vendors have rolled out various gen AI bots, agents, or co-pilot features, but the truth is these look-alike tools will not drive competitive differentiation. We enable our clients to reimagine how their entire business runs with unique tools such as Pega GenAI Blueprint, which provides best-of-breed app designs in seconds. We’re not just automating tasks; we’re fundamentally reimagining how businesses operate and innovate.

Second, we’re not just automating in isolation, we’re orchestrating how work gets done from start to finish. Other vendors sprinkle in these gen AI bot features and hope that’s enough to increase efficiency. Our platform is rooted in our industry-leading case management and orchestration, which enables us to not only automate with gen AI but also orchestrate and optimize the entire process from end to end.

Third, we’re not just a generic gen AI engine – we’re focused on driving better client engagement and workflow automation through AI. Sometimes, the problem at hand calls for the creative power of generative AI, whereas other issues might require predictive AI or decisioning AI to infuse more logic into the process.

In your Forbes article, “Unlocking The Potential Of Advanced AI For Business Innovation,” you mention the potential of generative AI to reimagine business operations. What are some specific examples where AI could catalyze legacy transformation in established companies?

Deutsche Telekom’s SVP of Design Authorities, Daniel Wenzel, described to the audience at PegaWorld iNspire this summer how he’s currently using Pega GenAI Blueprint to help him reimagine over 800 separate business processes in the HR services department. He says the biggest bottleneck in trying to improve these processes was that the businesspeople and IT don’t speak the same language, which leads to unrealized expectations. Pega GenAI Blueprint helps both stakeholders understand the process and how to improve it much faster than traditional methods, leading to more effective solutions.

The same article discusses the limitations of current generative AI applications. How can companies move beyond incremental productivity improvements to harness AI’s full transformative potential?

Most generative AI in enterprise software is applied as one-off features that help speed specific aspects of the process. But these types of features are commonplace now, providing little competitive advantage. Productivity hacks like summarization and text generation are table stakes – what businesses need to advance in the market is to use generative AI to innovate all new ways of doing business at a high level. For example, Gartner has identified a new technology category they call Business Orchestration and Automation Technologies (BOAT) that looks at driving business outcomes more holistically, from streamlining costs, to improving decision making, to reducing operational costs and using the right automation technologies for the job at hand. One-off gen AI features have their place, but it’s just a piece of the puzzle and not the silver bullet to solve all problems.

What are the most promising enterprise use cases for generative AI that go beyond typical productivity enhancements, and how can businesses best implement these?

The most exciting generative AI opportunity is the potential to inject best practices into a process. Those that are using gen AI to just write more code could be setting themselves up for more technical debt down the line. The injection of IP into the software design process is a game changer, enabling organizations to get to an optimal solution much faster based on years of experience. And because it’s developed as a visual model and not just lines of code, it’s easier to collaborate and refine it over time across technical and non-technical stakeholders. Previously, finalizing an app design could take weeks and required very specialized skill sets; now, these gen AI-powered tools enable business users to type in their specific needs in plain language and quickly move from concept to comprehensive design. Forrester recently published some research predicting that using AI to inject IP into low-code or model-based design systems will fundamentally shift how enterprises use software – allowing them to build more and buy far fewer ‘off the shelf’ apps.  I think this is a big transformation, and we believe with Pega GenAI Blueprint we are well positioned to be the platform of choice for our enterprise clients.

You’ve previously suggested that generative AI can aid in product development by identifying market gaps. Can you elaborate on how this process works and share a real-world example?

Our Pega Customer Decision Hub is a predictive AI solution that helps our clients make the next-best action with their customers, whether that means up selling a product, fixing a service issue, or sometimes doing nothing at all. This allows us to connect with customers 1:1 with actions that best serve their individual needs. But operating in a 1:1 way means you need a great quantity of tailored offers – it’s far better than spamming everyone with the same message, but it requires marketing organizations to create more messages that are unique to different customer groups. Now with gen AI, we can uncover which customers have been underserved and then suggest new actions and build new treatments that would be more beneficial to these groups. This has the potential to help organizations expand into market audiences they have typically not been able to address.

How can established companies with legacy systems effectively integrate generative AI to remain competitive against more agile startups, particularly in reimagining their core operations?

I think we are entering a tipping point for legacy systems. For decades, large enterprises have been kicking the technical debt can down the road. We spent years applying band aid solutions like RPA that didn’t address the fundamental drain that legacy systems place on enterprises – they siphon off IT spend that could be going to innovation, they introduce risk, and they prevent enterprises from moving fast in changing markets. Luckily, I believe one of the superpowers of gen AI is that it will let us dramatically accelerate the rate at which we redesign and retire our legacy systems – not by simply recoding them, but by rethinking the workflows and processes themselves to both run on modern cloud architectures and deliver the digital experiences customers and employees expect.

In a separate article on establishing an AI manifesto, you emphasize the importance of tying AI strategy to actionable outcomes. Can you provide guidance on how businesses can align their AI goals with tangible business results?

Too many companies start by focusing on a shiny new tool like AI rather than starting by figuring out what their business objectives are and what problem they need to solve. By focusing on the tool rather than the problem, they pigeonhole themselves into a path that might not be optimal for their business. Instead, they need to step back and ask themselves what they are really trying to accomplish. Sometimes gen AI isn’t the right solution and may be better served by applying AI decisioning instead. They need to remember there are different types of AI that are better suited to solving different business problems.

How can businesses leverage generative AI to revolutionize their operations rather than just automating routine tasks? What strategies should they employ to maximize ROI in this area?

Don’t just focus on the individual tasks – this will prevent you from seeing the forest for the trees. Step back and understand your overall business workflows and the outcomes you are trying to drive from them. Generative AI can be used to analyze your processes and infuse best practices in any number of different industries. This can drive profound changes by enabling companies to rethink and redesign their core workflows. For example, AI can help design new operational models from scratch or re-engineer existing ones to improve efficiency and innovation. Establish clear metrics to measure success and regularly refine your approach based on these insights. By leveraging AI to drive meaningful change rather than incremental improvements, businesses can unlock significant value and stay ahead of the competition.

What industries do you believe are most poised to benefit from redesigning workflows using AI, and how should they begin implementing this approach?

Nearly any organization can universally benefit from improving their workflows, particularly in fast-changing markets. Services industries such as financial services, telco, and healthcare can likely realize the most gains to help streamline how they engage with their customers. These sectors handle complex, data-intensive processes and are under increasing pressure to improve efficiency, reduce costs, and deliver better outcomes. In addition, any industry with large amounts of legacy services – such as banking – can benefit by examining their processes likely established years ago to modernize them and ensure they keep pace with newer competition.

How does the ‘human-in-the-loop’ approach enhance the effectiveness and ethical deployment of AI, particularly in customer-facing roles?

Generative AI, while powerful, can produce outputs that are not always accurate or appropriate. By integrating human oversight, we can mitigate risks such as AI-generated content inaccuracies or ethical issues.

For instance, in customer service, AI can generate responses and recommendations, but having a human review these outputs ensures they align with company values and customer needs. This oversight is crucial for maintaining transparency and accountability, particularly when AI models produce plausible but incorrect or misleading information.

Interestingly, having a human in the loop allows you to take one of the weaknesses of gen AI – it is inherently non-predictable or non-deterministic, which means it doesn’t give you the same answer twice – and turn that into a strength. With Pega GenAI Blueprint, we use gen AI as a brainstorming partner, suggesting new approaches to workflow design. The human is always the final decider, but by constantly suggesting new approaches, gen AI pushes original thinking and helps humans avoid ‘repaving the cow path.’

Thank you for the great interview, readers who wish to learn more should visit Pegasystems. 

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At Tecnolynx, we take great pride in consistently achieving 100% client satisfaction by providing high-quality applications at competitive prices. Our team of experienced and highly skilled professionals is committed to delivering outstanding service. With our 24/7 support, clients can rely on us for assistance whenever they need it.

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[jaysonmurphyitservice]

Jayson Murphy IT service

Website: http://jaysonmurphyitservicer.com/

Address: 609 New York Ave, Brooklyn, NY 11203, USA

Phone: 917-577-3337

Jayson Murphy IT Service is a comprehensive provider of managed IT solutions tailored to meet the unique needs of businesses. With a focus on enhancing operational efficiency and ensuring robust cybersecurity, we offer a range of services including network management, cloud solutions, data backup, and IT consulting. Our team of experienced professionals is dedicated to delivering reliable support and innovative technology strategies that empower organizations to thrive in a digital landscape. At Jayson Murphy IT Service, we prioritize customer satisfaction and work closely with our clients to develop customized solutions that drive growth and success.

Business Email: jmitservice@gmail.com

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[tranktechnologies]

What Are The Top Features Every CRM Application Should Have?

Looking for a reliable CRM application development company? We specialize in creating custom CRM solutions tailored to your business needs, helping you streamline processes and enhance customer relationships. Contact us today!

[ajay585]

Powerful CRM Platform | Elevate Customer Engagement & Business Growth

Transform your business with our powerful CRM platform. Manage customer interactions, drive sales, and enhance team collaboration with intuitive tools and seamless automation.

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How AI Chatbots are Revolutionizing OnlyFans and Fansly for Creators

In the dynamic world of online content creation, platforms like OnlyFans and Fansly have emerged as powerful tools for creators to monetize their unique talents and build dedicated fanbases. As these platforms grow, so does the need for efficient communication and management tools. Enter AI chatbots—a revolutionary technology transforming how creators interact with fans and manage their accounts. This blog explores how AI, particularly chatbots, is reshaping the landscape of OnlyFans and Fansly, offering unprecedented benefits to creators.

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Best HR Software Providers in Bahrain

Enhance your HR and payroll processes with the best HR software in Bahrain. Our HR and payroll software Bahrain offers cloud-based HR management, HR CRM software, and comprehensive solutions for small businesses and SMEs.

[jcmarchi]

Leighton Welch, CTO and Co-Founder of Tracer – Interview Series

New Post has been published on https://thedigitalinsider.com/leighton-welch-cto-and-co-founder-of-tracer-interview-series/

Leighton Welch, CTO and Co-Founder of Tracer – Interview Series

Leighton Welch is CTO and co-founder of Tracer. Tracer is an AI-powered tool that organizes, manages, and visualizes complex data sets to drive faster, more actionable business intelligence. Prior to becoming the Chief Technology Officer at Tracer, Leighton was the Director of Consumer Insights at SocialCode, and the VP of Engineering at VaynerMedia. He has spent his career pioneering in the ad tech ecosystem, running the first ever Snapchat Ad and consulting on commercial APIs for some of the world’s biggest platforms. Leighton graduated from Harvard in 2013, with a degree in Computer Science and Economics.

Can you tell us more about your background and how your experiences at Harvard, SocialCode, and VaynerMedia inspired you to co-found Tracer?

The original idea came a decade ago. A childhood friend of mine rang me on a Friday night. He was struggling with aggregating data across various social platforms for one of his clients. He figured this could be automated, so he enlisted my help since I had a background in software engineering. That’s how I was first introduced to my now co-founder, Jeff Nicholson.

This was our light bulb moment: The quantity of money being spent on these campaigns was far outpacing the quality of the software tracking those dollars. It was a nascent market with a ton of applications in data science.

We kept building analytics software that could meet the needs of increasingly large and complex media campaigns. As we hacked away at the problem, we developed a process – clear steps from getting the disparate data ingested and contextualized. We realized the process we were building could be applied to any data set – not just advertising – and that’s what Tracer is today: an AI-powered tool that organizes, manages, and visualizes complex data sets to drive faster, more actionable business intelligence.

We’re helping to democratize what it means to be a “data-driven” organization by automating the steps needed to ingest, connect, and organize disparate data sets across functions, providing powerful BI through intuitive reporting and visualizations. This could mean connecting sales data to your marketing CRM, HR analytics to revenue trends, and endless more applications.

Can you explain how Tracer’s platform automates analytics and revolutionizes the modern data stack for its clients?

For simplicity, let’s define analytics as the answering of a business question through software. In today’s landscape, there are really two approaches.

The first is to buy vertical software. For CFOs, this might be Netsuite. For the CRO, it might be Salesforce. Vertical software is great because it’s end-to-end, it can be hyper specialized, and should just work out of the box. The limitation of vertical software is that it’s vertical: if you want Netsuite to talk to Salesforce, you are back to square one. Vertical software is complete, but it’s not flexible.

The second approach is to buy horizontal software. This might be one software for data ingestion, another for storage, and a third for analysis. Horizontal software is great because it can handle pretty much anything. You could certainly ingest, store and analyze both your Salesforce and Netsuite data through this pipeline. The limitation is that it needs to be put together, maintained, and nothing works “out of the box.” Horizontal software is flexible, but it’s not complete.

We offer a third approach by creating a platform that combines the technologies necessary to report on anything, made accessible enough to work out of the box without any engineering resources or technical overhead. It’s flexible and complete. Tracer is the most powerful platform on the market that is both application agnostic, and end-to-end.

Tracer processed on the order of 10 petabytes of data last month. How does Tracer handle such a vast amount of data efficiently?

Scale is incredibly important in our world, and it has always been a priority at Tracer even in the beginning days. To process this volume of data, we leverage a lot of best in class technologies and avoid reinventing the wheel where we don’t need to. We’re incredibly proud of the infrastructure we’ve built, but we’re also quite open about it. In fact, our architecture program is outlined on our website.

What we say to partners is this: It’s not that your in-house engineering teams aren’t capable of building what we’ve built; rather, they shouldn’t have to. We’ve assembled the pieces of the modern data stack for you. The framework is efficient, battle-tested, and modular for us to dynamically evolve with the landscape.

A lot of partners will come to us looking to free up engineering resources to focus on bigger strategic initiatives. They use Tracer’s architecture as a means to an end. Having a database doesn’t answer business questions. Having an ETL pipeline doesn’t answer business questions. The thing that really matters is what you’re able to do with that infrastructure once it’s been put together. That’s why we built Tracer – we’re your shortcut to getting answers.

Why do you believe structured data is critical for AI, and what advantages does it provide over unstructured data?

Structured data is critical for AI because it allows for manual human interaction, which we believe is an essential component to effective outputs. That being said, in today’s ecosystem, we are actually better equipped than ever before to leverage the insights in unstructured data and previously hard to access formats (documents, images, videos, etc.).

So for us, it’s about providing a platform through which additional context can be incorporated from the people who are most familiar with the underlying datasets once that data has been made accessible. In other words, it’s unstructured data → structured data → Tracer’s context engine → AI-driven outputs. We sit in between and allow for a more effective feedback loop, and for manual intervention where necessary.

What challenges do companies face with unstructured data, and how does Tracer help overcome these challenges to improve data quality?

Without a platform like Tracer, the challenge with unstructured data is all about control. You feed data into the model, the model spits out answers, and you have very little opportunity to optimize what’s happening inside the black box.

Say for example you want to determine the most impactful content in a media campaign. Tracer might use AI to help provide metadata on all the content that was run in the ads. It also might use AI to provide last mile analytics for getting from a highly structured dataset to that answer.

But in between, our platform allows users to draw the connections between the media data and the dataset where the outcomes live, more granularly define “impactful,” and clean up the categorizations done by the AI. Essentially, we’ve abstracted and productized the steps, in order to remove the black box. Without AI, there is a lot more work that has to be done by the human in Tracer. But without Tracer, AI can’t get to the same quality of answer.

What are some of the key AI-based technologies Tracer uses to enhance its data intelligence platform?

You can think of Tracer across three core product categories: Sources, Content, and Outputs.

Sources is a tool used to automate the ingestion, monitoring and QA of disparate data.

Context is a drag and drop semantic layer for the organization of data after it’s been ingested.

Outputs is where you can answer business questions on top of contextualized data.

At Tracer we don’t see AI as a replacement for any of these steps; instead, we see AI as another form of tech that all three categories can leverage to expand what can be automated.

For example:

Sources: Leveraging AI to help build new API connectors to long tail data sources not available through our partner catalog.

Context: Leveraging AI to clean up metadata prior to running tag rules. For example, cleaning up variations of publication names in every language.

Outputs: Leveraging AI as a drop-in replacement for dashboards where the business use case is exploratory, rather than a fixed set of KPIs that need to be reported on repeatedly.

AI allows us to achieve these types of applications in ways that are both simple and accessible.

What are Tracer’s plans for future development and innovation in the data intelligence space?

Tracer is an aggregator of aggregators. Our partners will lean on us for specific applications within teams and functions, or for use in cross-functional business intelligence. The beauty of Tracer is that whether you’re leveraging us for making better decisions with your media spend and creative, or building dashboards to link disparate metrics from supply chain to sales and everything in between, the building blocks are consistent.

We’re seeing organizations who formally relied on us within one area of the business (e.g., media and marketing), expand applications to elsewhere in the business. So where our primary customers were formally senior media executives, or agency partners, these days we work across the org, partnering with CIOs, CTOs, data scientists, and business analysts. We’re continuing to build out our tools to accommodate for more and more applications and personas, all while ensuring the core tech is scalable, flexible, and accessible for non-technical users.

Thank you for the great interview, readers who wish to learn more should visit Tracer.