#agentic ai

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Custom AI: Top tech trends to watch out for in 2025

In the coming 12 months, a few transformative trends are poised to unlock unprecedented opportunities across sectors. Here’s predicting five key technologies that will shape the future: Custom AI: Tailored intelligence for strategic impact Custom AI will emerge as a transformative force in 2025, allowing organisations to design AI solutions tailored to their specific needs. By leveraging…

[aitalksblog]

Top Weekly AI News – December 20, 2024

AI News Roundup – December 20, 2024 OpenAI announces new o3 models OpenAI has introduced o3, a new family of reasoning models that surpasses its predecessor, demonstrating significant advancements in reasoning capabilities techcrunch Dec 20, 2024 Need a research hypothesis? Ask AI. MIT engineers developed AI frameworks to identify evidence-driven hypotheses that could advance biologically…

[jcmarchi]

Robots with Feeling: How Tactile AI Could Transform Human-Robot Relationships

New Post has been published on https://thedigitalinsider.com/robots-with-feeling-how-tactile-ai-could-transform-human-robot-relationships/

Robots with Feeling: How Tactile AI Could Transform Human-Robot Relationships

Sentient robots have been a staple of science fiction for decades, raising tantalizing ethical questions and shining light on the technical barriers of creating artificial consciousness. Much of what the tech world has achieved in artificial intelligence (AI) today is thanks to recent advances in deep learning, which allows machines to learn automatically during training. 

This breakthrough eliminates the need for painstaking, manual feature engineering—a key reason why deep learning stands out as a transformative force in AI and tech innovation. 

Building on this momentum, Meta — which owns Facebook, WhatsApp and Instagram — is diving into bold new territory with advanced “tactile AI” technologies. The company recently introduced three new AI-powered tools—Sparsh, Digit 360, and Digit Plexus—designed to give robots a form of touch sensitivity that closely mimics human perception. 

The goal? To create robots that don’t just mimic tasks but actively engage with their surroundings, similar to how humans interact with the world. 

Sparsh, aptly named after the Sanskrit word for “touch,” is a general-purpose agentic AI model that allows robots to interpret and react to sensory cues in real-time. Likewise, the Digit 360 sensor, is an artificial fingertip for robots that can help perceive touch and physical sensations as minute as a needle’s poke or changes in pressure. The Digit Plexus will act as a bridge, providing a standardized framework for integrating tactile sensors across various robotic designs, making it easier to capture and analyze touch data. Meta believes these AI-powered tools will allow robots to tackle intricate tasks requiring a “human” touch, especially in fields like healthcare, where sensitivity and precision are paramount.

Yet the introduction of sensory robots raises larger questions: could this technology unlock new levels of collaboration, or will it introduce complexities society may not be equipped to handle?

��As robots unlock new senses, and gain a high degree of intelligence and autonomy, we will need to start considering their role in society,” Ali Ahmed, co-founder and CEO of Robomart, told me. “Meta’s efforts are a major first step towards providing them with human-like senses. As humans become exceedingly intimate with robots, they will start treating them as life partners, companions, and even going so far as to build a life exclusively with them.”

A Framework for Human-Robot Harmony, the Future? 

Alongside its advancements in tactile AI, Meta also unveiled the PARTNR benchmark, a standardized framework for evaluating human-robot collaboration on a large scale. Designed to test interactions that require planning, reasoning, and collaborative execution, PARTNR will allow robots to navigate both structured and unstructured environments alongside humans. By integrating large language models (LLMs) to guide these interactions, PARTNR can assess robots on critical elements like coordination and task tracking, shifting them from mere “agents” to genuine “partners” capable of working fluidly with human counterparts. 

“The current paper is very limited for benchmarking, and even in Natural Language Processing (NLP), it took a considerable amount of time for LLMs to be perfected for the real world. It will be a huge exercise to generalize for the 8.2 billion population with a limited lab environment,” Ram Palaniappan, CTO of TEKsystems, told me. “There will need to be a larger dedicated effort to boost this research paper to get to a workable pilot.”

To bring these tactile AI advancements to market, Meta has teamed up with GelSight Inc. and Wonik Robotics. GelSight will be responsible for producing the Digit 360 sensor, which is slated for release next year and will provide the research community access to advanced tactile capabilities. Wonik Robotics, meanwhile, will handle the production of the next-generation Allegro Hand, which integrates Digit Plexus to enable robots to carry out intricate, touch-sensitive tasks with a new level of precision. Yet, not everyone is convinced these advancements are a step in the right direction. 

“Although I still believe that adding sensing capabilities could be meaningful for robots to understand the environment, I believe that current use cases are more related to robots for mass consumers and improving on their interaction,” Agustin Huerta, SVP of Digital Innovation for North America at Globant, told me. “I don’t believe we are going to be close to giving them human-level sensations, nor that it’s actually needed. Rather, it will act more as an additional data point for a decision-making process.”

Meta’s tactile AI developments reflect a broader trend in Europe, where countries like Germany, France, and the UK are pushing boundaries in robotic sensing and awareness. For instance, the EU’s The Horizon 2020 program supports a range of projects aimed at pushing robotic boundaries, from tactile sensing and environmental awareness to decision-making capabilities. Moreover, The Karlsruhe Institute of Technology in Germany recently introduced ARMAR-6, a humanoid robot designed for industrial environments. ARMAR-6 is equipped to use tools like drills and hammers and features AI capabilities that allow it to learn how to grasp objects and assist human co-workers. 

But, Dr. Peter Gorm Larsen, Vice-Head of Section at the Department of Electrical and Computer Engineering at Aarhus University in Denmark, and coordinator of the EU-funded RoboSAPIENS project, cautions that Meta might be overlooking a key challenge: the gap between virtual perceptions and the physical reality in which autonomous robots operate, especially regarding environmental and human safety. 

“Robots do NOT have intelligence in the same way that living creatures do,” he told me. “Tech companies have a moral obligation to ensure that their products respect ethical boundaries. Personally, I’m most concerned about the potential convergence of such advanced tactile feedback with 3D glasses as compact as regular eyewear.”

Are We Ready for Robots to “Feel”?

Dr. Larsen believes the real challenge isn’t the tactile AI sensors themselves, but rather how they’re deployed in autonomous settings. “In the EU, the Machinery Directive currently restricts the use of AI-driven controls in robots. But, in my view, that’s an overly stringent requirement, and we hope to be able to demonstrate that in the RoboSAPIENS project that I currently coordinate.” 

Of course, robots are already collaborating with humans in various industries across the world. For instance, Kiwibot has helped logistics companies dealing with labor shortages in warehouses, and Swiss firm Anybotics recently raised $60 million to help bring more industrial robots to the US, according to TechCrunch. We should expect artificial intelligence to continue to permeate industries, as “AI accelerates productivity in repeatable tasks like code refactoring, addresses tech debt and testing, and transforms how global teams collaborate and innovate,” said Vikas Basra, Global Head, Intelligent Engineering Practice, Ness Digital Engineering.

At the same time the safety of these robots – now as well as in their potentially “sentient” future – is the main concern in order for the industry to progress. 

Said Matan Libis, VP of product at SQream, an advanced data processing company, in The Observer, “The next major mission for companies will be to establish AI’s place in society—its roles and responsibilities … We need to be clear about its boundaries and where it truly helps. Unless we identify AI’s limits, we’re going to face growing concerns about its integration into everyday life.”

As AI evolves to include tactile sensing, it raises the question of whether society is ready for robots that “feel.” Experts argue that pure software-based superintelligence may hit a ceiling; for AI to reach a true, advanced understanding, it must sense, perceive, and act within our physical environments, merging modalities for a more profound grasp of the world—something robots are uniquely suited to achieve. Yet, superintelligence alone doesn’t equate to sentience. “We must not anthropomorphize a tool to the point of associating it as a sentient creature if it has not proven that it is capable of being sentient,” explained Ahmed. “However if a robot does pass the test for sentience then they should be recognized as a living sentient being and then we shall have the moral, and fundamental responsibility to grant them certain freedoms and rights as a sentient being.”

The implications of Meta’s tactile AI are significant, but whether these technologies will lead to revolutionary change or cross ethical lines remains uncertain. For now, society is left to ponder a future where AI not only sees and hears but also touches—potentially reshaping our relationship with machines in ways we’re only beginning to imagine.

“I don’t think that increasing AI’s sensing capabilities crosses the line on ethics. It’s more related to how that sensing is later used to make decisions or drive others’ decisions,” said Huerta. “The robot revolution is not going to be different from the industrial revolution. It will affect our lives and leave us in a state that I think can make humanity thrive. In order for that to happen, we need to start educating ourselves and the upcoming generations on how to foster a healthy relationship between humans and robots.”

[procurement-insights]

New GEP Paper: Agentic AI Versus Real Agents?

What is the ProcureTech "Fork in the road?"

Hi Jon, Did you see that paper by GEP / CIPS? I didn’t read it, yet. Thank you for sending it; I hadn’t seen it. Interestingly, GEP has been following me and my posts on LinkedIn in increasing numbers and frequency lately. 1999 Revisited (Video) – Real Agents Leveraging AI GEP Autonomous Agentic AI Agents (High-Level Summary) GEP is set to revolutionize procurement and supply chain operations…

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Emerging Trends in AI in 2024

Artificial Intelligence (AI) is not just a buzzword anymore; it’s a driving force behind the digital transformation across industries. As we move into 2024, AI continues to evolve rapidly, introducing new possibilities and challenges. From enhancing business processes to reshaping entire sectors, AI's influence is expanding. Here, we explore the emerging AI trends in 2024 that are set to redefine how we live, work, and interact with technology.

Emerging trends in Artificial Intelligence (AI) in 2024

AI-Driven Creativity: Expanding the Horizons of Innovation One of the most exciting trends in AI for 2024 is its growing role in creative processes. AI is no longer limited to analyzing data or automating tasks; it is now actively contributing to creative fields. AI-driven creativity refers to the use of AI to generate new ideas, designs, and even art. This trend is particularly prominent in industries such as fashion, entertainment, and design, where AI algorithms are being used to create novel designs, suggest creative concepts, and even compose music. For example, AI can analyze vast amounts of data to identify emerging design trends, which can then be used to create new products that align with consumer preferences. In the entertainment industry, AI is being used to generate scripts, compose music, and even create digital art. This trend is pushing the boundaries of creativity, enabling human creators to collaborate with AI in unprecedented ways. As AI continues to develop its creative capabilities, we can expect to see more AI-generated content across various media, leading to a fusion of human and machine creativity that will redefine innovation.

AI-Powered Automation: Transforming Business Operations Automation has been a key application of AI for years, but in 2024, AI-powered automation is set to reach new levels of sophistication. AI is increasingly being used to automate complex business processes, from supply chain management to customer service. This trend is driven by advancements in machine learning and natural language processing, which enable AI systems to perform tasks that were previously thought to require human intelligence. One area where AI-powered automation is making a significant impact is in customer service. AI chatbots and virtual assistants are becoming more advanced, capable of understanding and responding to complex customer queries in real-time. This not only improves the customer experience but also reduces the need for human intervention, allowing businesses to operate more efficiently. In addition to customer service, AI-powered automation is also being used in manufacturing, logistics, and finance. For example, AI algorithms can optimize production schedules, predict maintenance needs, and even automate financial transactions. As businesses continue to adopt AI-powered automation, they can expect to see increased efficiency, reduced costs, and improved decision-making capabilities.

AI and Sustainability: Driving Environmental Innovation As the world grapples with the challenges of climate change, AI is emerging as a powerful tool for driving sustainability. In 2024, AI is being used to develop innovative solutions that reduce environmental impact and promote sustainability across various sectors. This trend is particularly evident in areas such as energy management, agriculture, and transportation. One of the most promising applications of AI in sustainability is in energy management. AI algorithms can analyze energy consumption patterns and optimize the use of renewable energy sources, such as solar and wind power. This not only reduces carbon emissions but also lowers energy costs for businesses and consumers. In agriculture, AI is being used to optimize farming practices, from precision irrigation to crop monitoring. By analyzing data from sensors and satellites, AI can help farmers make more informed decisions, leading to increased crop yields and reduced resource use. This trend is critical for addressing the global challenges of food security and environmental sustainability. Moreover, AI is playing a crucial role in the development of smart cities, where it is used to optimize transportation systems, reduce traffic congestion, and minimize pollution. As AI continues to drive sustainability, it will play a pivotal role in creating a more sustainable and resilient future.

AI Ethics and Responsible AI: Ensuring Trust and Transparency As AI becomes more integrated into our daily lives, concerns about its ethical implications are growing. In 2024, AI ethics and responsible AI development are emerging as critical areas of focus for businesses, governments, and researchers. Ensuring that AI is developed and used responsibly is essential for maintaining public trust and preventing unintended consequences. One of the key ethical concerns surrounding AI is bias in decision-making algorithms. AI systems are often trained on historical data, which may contain biases that can lead to unfair outcomes. For example, AI algorithms used in hiring or lending decisions may inadvertently discriminate against certain groups. To address this issue, researchers and companies are developing techniques to detect and mitigate bias in AI systems. Another important aspect of AI ethics is transparency. Users need to understand how AI systems make decisions, especially when those decisions have significant impacts on their lives. This has led to a push for explainable AI, where the decision-making process is clear and understandable to humans. Additionally, there is a growing emphasis on AI governance, where organizations are establishing frameworks and guidelines for responsible AI development. This includes ensuring that AI systems are used in ways that align with ethical principles, such as fairness, accountability, and transparency. As AI continues to evolve, addressing its ethical challenges will be critical to ensuring that it benefits society as a whole.

AI in Healthcare: Revolutionizing Patient Care The integration of AI in healthcare is not a new trend, but in 2024, it is set to revolutionize patient care in unprecedented ways. AI is being used to improve diagnostics, treatment planning, and patient outcomes, making healthcare more efficient and accessible. One of the most significant applications of AI in healthcare is in medical imaging. AI algorithms can analyze medical images, such as X-rays and MRIs, with incredible accuracy, often detecting abnormalities that might be missed by human doctors. This can lead to earlier diagnosis and treatment of diseases like cancer, ultimately saving lives. In addition to diagnostics, AI is also being used to develop personalized treatment plans. By analyzing a patient's genetic information, medical history, and lifestyle, AI can recommend treatments that are most likely to be effective for that individual. This personalized approach not only improves patient outcomes but also reduces the likelihood of adverse reactions to treatments. Moreover, AI is playing a crucial role in drug discovery. AI algorithms can analyze vast amounts of data to identify potential new drugs and predict how they will interact with the human body. This accelerates the drug development process, bringing new treatments to market faster. As AI continues to advance in healthcare, it will lead to better patient outcomes, more efficient healthcare systems, and ultimately, a healthier population. Conclusion The year 2024 is set to be a transformative one for AI, with emerging trends that will shape the future of technology, business, and society. From AI-driven creativity and automation to sustainability and ethics, these trends highlight the growing influence of AI in our lives. As we navigate this rapidly evolving landscape, it is essential to stay informed and prepared for the changes that lie ahead. By embracing these emerging AI trends, businesses and individuals can harness the power of AI to drive innovation, improve outcomes, and create a better future.

[innova7ions]

Meet the Future: Proactive AI Agents Changing Our World!

Agentic AI signifies a groundbreaking evolution in artificial intelligence, transitioning from reactive systems to proactive agents.

These advanced AI entities possess the ability to comprehend their surroundings, establish goals, and operate independently to fulfill those aims. In this video, we delve into how agentic AI is revolutionizing decision-making processes and taking actions autonomously without human oversight.

A prime example includes environmental monitoring systems that identify and respond to threats such as forest fires.

Discover the implications of this technology on our future!

Video Automatically Generated by Faceless.Video

For other details on other Generative AI Platforms - Visit our YouTube Channel - AI Innovations

or Visit our Website at INNOVA7IONS

#AgenticAI

#ArtificialIntelligence

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Video Automatically Generated by Faceless.Video:

Agentic AI refers to AI systems designed to operate as agents that can autonomously perform tasks, make decisions, and interact with their environment and other systems or agents. These AI agents are goal-oriented, capable of sensing their environment, processing information, and taking actions to achieve specific objectives. Unlike traditional AI, which may require explicit instructions for each task, agentic AI systems can act independently within predefined parameters to achieve their goals.

Key Features of Agentic AI:

Autonomy:Agentic AI systems operate independently, making decisions and taking actions without needing constant human supervision.Goal-Oriented Behavior:These AI agents are designed with specific goals or objectives, and they use their capabilities to work towards achieving these goals.Environmental Awareness:Agentic AI can perceive and interpret its environment using sensors, data feeds, or other inputs. It adapts its behavior based on changes in the environment.Decision-Making and Problem-Solving:These AI agents use algorithms to evaluate options, solve problems, and make decisions that align with their goals.Interactivity and Communication:Agentic AI can interact with other systems, agents, or humans, exchanging information and coordinating actions to achieve collective objectives.Learning and Adaptation:Some agentic AI systems can learn from their experiences, improving their performance and adapting to new challenges over time.Task Execution:These AI agents can execute tasks within their domain of expertise, whether it’s navigating a physical environment, processing data, or coordinating with other agents.

Benefits of Agentic AI:

Efficiency in Task Automation:Agentic AI can automate complex tasks, freeing up human resources for more strategic activities.Improved Decision-Making:By processing large amounts of data and considering multiple variables, agentic AI can make more informed decisions than humans might.Scalability:Agentic AI systems can be deployed at scale, managing large, complex operations across multiple domains simultaneously.Adaptability:These systems can adapt to new environments or changing conditions, ensuring that they remain effective even as circumstances evolve.Enhanced Collaboration:Agentic AI can work alongside humans and other AI systems, facilitating better teamwork and coordination, particularly in complex environments.Cost Savings:Automating routine or complex tasks with agentic AI can reduce labor costs and minimize errors, leading to significant cost savings.24/7 Operation:Like autonomous AI, agentic AI can operate continuously, providing services or monitoring systems around the clock.

Target Audience for Agentic AI:

Enterprise Operations:Large businesses use agentic AI to automate complex processes, manage supply chains, optimize logistics, and enhance customer service.Healthcare:Agentic AI is employed in personalized medicine, patient monitoring, and automated diagnostics, where it can operate independently to improve outcomes.Financial Services:Financial institutions leverage agentic AI for automated trading, risk assessment, fraud detection, and customer interaction.Robotics and Automation:In industries like manufacturing, agentic AI powers robots that can operate autonomously in dynamic environments, adapting to new tasks or challenges.Smart Cities and Infrastructure:Governments and urban planners use agentic AI to manage traffic, energy consumption, public safety, and other aspects of urban living.Agriculture:Agentic AI is applied in precision agriculture, where it manages crop monitoring, irrigation, pest control, and other tasks autonomously.Defense and Security:Defense organizations deploy agentic AI for autonomous surveillance, threat detection, and coordination of unmanned systems.Consumer Technology:In the consumer space, agentic AI powers smart assistants, autonomous home devices, and personalized user experiences.

Comparison with Autonomous AI:

Autonomy vs. Agency:While both autonomous and agentic AI operate independently, agentic AI is specifically designed to achieve defined goals within a particular environment, often interacting with other agents or systems to do so.Interaction:Agentic AI often involves more interaction, whether with humans, other AI agents, or systems, as it’s designed to work in a collaborative or multi-agent setting.

Agentic AI is particularly valuable in environments where collaboration, decision-making, and adaptive behavior are essential, offering significant benefits across various industries.

Credit: ChatGPT

[gleaming-glasses]

Family antics

[enden-k]

you can tell the moment my brain paused LMFAO....

[fischiee]

omega when he’s implanted in tex: you should give into your rage and abandon those you might love to fulfill the urge to find revenge for all those who hurt you. kill your daughter in cold blood while she is incapacitated with agony at even the mention of your name

omega when he’s with the reds and blues: muahahaha 😈😈!!!!1!!! !!! im eevviilllll and im going to blow up the whole! WORLD! !1! 😈😈😈 !!!

[aitalksblog]

Top Weekly AI News – December 13, 2024

AI News Roundup – December 13, 2024 Elections and AI in 2024: observations and learnings Anthropic shares insights into the 2024 election cycle and lessons learned for future elections anthropic Dec 12, 2024 How Trump’s new FTC chair views AI, Big Tech New FTC Chair Ferguson aims to tackle Big Tech while adopting a hands-off stance on AI regulation yahoo!tech Dec 12, 2024 Microsoft’s…

[jcmarchi]

Dheeraj Pandey, CEO and Co-founder of DevRev – Interview Series

New Post has been published on https://thedigitalinsider.com/dheeraj-pandey-ceo-and-co-founder-of-devrev-interview-series/

Dheeraj Pandey, CEO and Co-founder of DevRev – Interview Series

Dheeraj Pandey, CEO and co-founder of DevRev, is also the former CEO and founder of Nutanix and a current board member of Adobe. Along with co-founder Manoj Agarwal, Pandey launched DevRev to transform how developers (Dev) connect with revenue-generating customers (Rev).

DevRev’s mission is to embed customer-centricity into the core of product development, turning it into a cultural foundation rather than a departmental focus. By leveraging data, AI, and design, the platform empowers developers to directly impact business outcomes, streamline workflows, and accelerate innovation. Backed by one of the largest seed fundings in Silicon Valley history, DevRev is redefining customer-focused product development with its Product-Led Growth (PLG) model.

What inspired you to found DevRev after your successful tenure with Nutanix, and how did your experience there shape the vision for DevRev?

While building Nutanix during the era of Enterprise SaaS 1.0, I learned that enterprise software often turns into a maze of fragmented tools, each tackling just a piece of a broader problem. Many products in the market are really just features packaged as full solutions. This experience fueled my desire to build a platform that could truly unify and simplify complex workflows, helping businesses focus on what really matters: their customers. DevRev was born from this idea of doing fewer things but doing them better—integrating functions seamlessly to build more customer-centric companies.”

DevRev is described as being built “from a blank page in the AI era.” Can you elaborate on what this means, and why it was important to start fresh rather than build on existing SaaS systems?

Starting DevRev from scratch in today’s AI-driven world allowed us to create a fundamentally different product without legacy constraints. AI is undergoing what I like to call a ‘Goldilocks moment’—a balance where technology, demand, and tools like neural networks are just right for transformation. Building from a blank page meant we could leverage these advances to rethink what SaaS could be and place customers and products at the center rather than adapting old systems to new demands.

You have emphasized creating a customer-centric platform at DevRev. How do you ensure that AI-driven processes still keep human needs at the forefront of operations?

Our approach is to make AI an enabler, not a replacement. We prioritize interactions that align with real customer needs by integrating human insights into the heart of DevRev’s AI and knowledge graph—a powerful, unified system that ties together product, customer, and operational data to provide rich context for AI interactions. This means the AI can support teams by managing updates and simplifying processes, allowing companies to focus on real customer needs. The result is a platform that enhances human interactions by being collaborative and contextual, helping companies remain empathetic and responsive.

What were the biggest challenges you faced during the early days of DevRev, especially in terms of integrating AI and creating the knowledge graph that powers the platform?

One major challenge was avoiding the pitfalls of traditional project-centric systems. We wanted DevRev to be customer- and product-centric, which required a comprehensive knowledge graph from the start. Building this was complex, but it was essential to breaking down silos and integrating everything from customer feedback to engineering workflows into one seamless interface.

DevRev is positioned as an AI-native platform. How do you see AI evolving within the enterprise SaaS space, and what role does DevRev play in that transformation?

AI is the driving force behind what we see as SaaS 2.0—moving from static software to an adaptive, agent-driven experience. In this new model, AI is not just a tool but a foundational layer that learns and evolves alongside the business. DevRev leverages agentic AI to create a seamless, continuous learning environment, allowing companies to shift their focus from operational mechanics to deep customer engagement. Just as the cloud redefined infrastructure, AI is reshaping SaaS, enabling platforms like DevRev to drive richer, more responsive interactions across the entire enterprise.

How does DevRev’s knowledge graph differentiate it from traditional SaaS solutions? What value does it bring to businesses using your platform?

DevRev’s knowledge graph is built to unify product and customer data, creating a dynamic, integrated view across departments. Unlike traditional CRMs, which often emphasize sales transactions, our knowledge graph captures the full journey of a product and the customer’s interaction with it. This means businesses can better predict needs, resolve issues faster, and ultimately create a product that is continuously aligned with customer demands.

The new features in AgentOS, such as no-code custom AI agents and conversational search, aim to simplify work. Could you share specific examples of how these features have transformed operations for your clients?

With AgentOS, companies are finding they can streamline processes that once required multiple tools. For instance, no-code agents allow support teams to quickly build workflows that respond to unique customer needs without heavy IT involvement. One client used conversational search to reduce their response time by 30%, empowering support teams to focus more on customer satisfaction than backend coordination.

With major backers like Mayfield and Khosla Ventures, what was your approach to securing funding for DevRev, and how did you pitch the value of your AI-native platform to investors?

The pitch centered on a fresh approach to SaaS that would be purpose-built for the AI era. Investors recognized that the timing was right—AI, cloud, and customer expectations have all evolved. They saw DevRev as a platform that could integrate these elements into a unified solution, making enterprise software both more intelligent and more customer-centric.

DevRev is already seeing substantial time-saving impacts (e.g., reducing incident response times by 30%). What other areas of enterprise SaaS do you believe can benefit most from AI-driven efficiency?

AI can make an impact across functions, especially in areas that involve high-volume customer interactions, complex engineering processes, and frequent updates. DevRev is actively developing solutions that go beyond just time savings—helping companies cut down on operational costs while achieving a more agile, customer-driven approach.

As DevRev continues to grow, how do you maintain the balance between rapid scaling and staying true to your mission of building customer-centric companies?

Staying customer-centric means continuously evolving with our clients and their needs. We are focused on scalable, high-impact features rather than overwhelming users with options. Our team is committed to balancing growth with the principle of ‘less is better,’ ensuring that every feature we roll out enhances the customer journey and aligns with DevRev’s core mission.

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

[procurement-insights]

ZIP Reaches Out

Procurement Predictions for 2025 - what awaits procurement in the new year?

I received the following email this morning from ZIP, and am glad they reached out. Hi Jon, Hope you are well. Reaching out because you recently covered Zip for Procurement Insights, so I wanted to give you a heads up that the company just released some compelling end-of-year metrics (total spend processed, # of suppliers managed, AI insights delivered) as well as an impressive list of new…

[spaceistheplaceart]

the Knight of Chaos saving the Princess of Order...

Marina's daydreams about being rescued by Pearl are so cute, I had to draw something about it :)

Bonus Designs:

(Pls Reblog! and also pls use they/them for my agent 8 thx)