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Bridging the Skill Gap, the Spire.AI Way
AI Copilot tool enhances talent management by providing unbiased, data-driven opportunities for internal mobility(Reuters) In the fast-evolving world of business, organisations are increasingly aware of the importance of skill-based management. Yet, as they strive to become fully skill-based, they encounter significant challenges. The current HR systems, though well-intentioned, often fall short of addressing the real needs of businesses today. The lack of comprehensive skill data for employees, coupled with a reliance on subjective evaluations, leaves organizations unable to harness the potential of their talent fully. "The lack of domain-intelligent technology exacerbates these issues. Current systems often lack contextual understanding, leading to ineffective solutions. The absence of dynamic skills frameworks makes it hard to keep pace with changing demands," explains Saurabh Jain, founder and CEO of Spire.AI, a company that delivers talent operating models for skill-based organisations. Specifically in India, addressing the skill gap presents several challenges. One primary issue is the disparity in skill levels across different regions and industries, compounded by the rapid pace of technological advancements. "Many organizations still rely on outdated systems that lack the flexibility to adapt to changing skill requirements. Additionally, there is often resistance to adopting new technologies due to concerns mainly around the perceived complexity of implementation. Ensuring data quality and integration is another hurdle, as fragmented and siloed information can lead to inaccurate skill assessments," he further adds. AI to Enhance Talent Technology AI tools play a crucial role in Spire.AI's solutions, as they aggregate and analyse unstructured data from diverse sources to generate comprehensive skill profiles for employees with minimal input, such as job titles and experience or grades. "This allows for precise reskilling recommendations, career path simulations, and a robust skills-based internal talent marketplace. Spire.AI AI-powered frameworks continuously learn and adapt, ensuring they remain up-to-date with the latest skill trends and requirements in the marketplace," Saurabh Jain says. The AI Copilot tool enhances talent management by providing unbiased, data-driven opportunities for internal mobility and growth. The precision of the AI matching engine significantly improves internal mobility by utilizing cross-pollination across supply and demand, reducing the time to identify suitable matching employees and reducing the burden of external hiring while increasing the match-to-offer ratio. He further explains that AI tools are deployed to aggregate and analyze unstructured data from diverse sources, generating detailed employee skill profiles. "Our AI-powered framework automatically identifies skill gaps, recommends reskilling paths, and simulates career progression, ensuring employees and organizations can proactively address future skill needs - all of this without employees needing to enter any data in the forms, data is automatically generated and presented to employees for their self-verification which thereafter is validated by manager or SMEs," he says. Groundbreaking Large Ground Models for Skill Talent Additionally, the brand taps into LGM or Large Graph Models for Skills, which utilizes domain-intelligent AI tools to revolutionize talent management. "Spire.AI's LGM has over 10 million skill graph nodes that map skills, competencies, and qualifications across various industry domains and functions. The LGM identifies complex relationships between skills, including how they complement each other, their relevance to specific roles, and their progression paths," the CEO further adds. The LGM also integrates data from diverse sources and ensures a comprehensive and up-to-date model reflecting the latest job market and skill requirements. Advanced algorithms identify and map these relationships, recognizing skill adjacencies, hierarchies, and dependencies. The LGM enhances various aspects of talent management. The model facilitates personalized learning and development programs, recommending tailored training pathways to bridge skill gaps and support career progression, increasing employee engagement and retention. "A standout feature of the LGM is its continuous learning and evolution. As the model acquires new data, it updates its understanding of skill relationships, ensuring organizations access the most accurate skill information. The LGM's contextual understanding comprehends the relevance of skills within specific industries and roles, providing tailored and domain-specific insights," he adds. Additionally, the LGM aids strategic workforce planning by providing insights into the current skill inventory and future needs. It encourages internal mobility by mapping potential career paths and optimizing talent utilization by identifying underutilized skills. The HR landscape is evolving rapidly, emphasizing personalized employee development, strategic workforce planning, and efficient talent management. As businesses strive to remain competitive, the demand for AI-driven solutions continues to grow. Large Graph Model (LGM) for Skills and other innovative tools provide the agility and precision needed in modern HR practices. It further paves the way for exploring partnerships and collaborations to extend reach and impact. This further empowers more organizations to transition seamlessly into skill-based models, ensuring they remain competitive and future-ready in a rapidly changing business landscape.
The Financial Express
Mon, 19 Aug, 12:02 PM UTC
Bengaluru Startup Builds AI Assistant to Solve Enterprise's Hiring Issues
Can AI help you find the right talent according to the specific needs of your organisation? A startup in India thinks it can. Enterprises often face challenges such as talent shortages in specialised fields, fierce competition driving up salaries, and the need to ensure new hires fit the company culture. Additionally, evolving skill requirements- especially with the advent of generative AI- complicate finding candidates with the most current expertise. Hence, in the fast-evolving world of business, managing your talent pool efficiently becomes key. Spire.ai, which is based in Koramangala, Bengaluru, has developed an AI-powered assistant that helps large enterprises better manage and develop talent. The AI assistant automatically identifies skill gaps in an organisation, performs skill mapping, provides career recommendations to employees by scanning granular data, and predicts future skill gaps. A Copilot for Talent "Consider a professional services company with over 100,000 employees. These companies frequently rotate staff across various projects for their, let's say, 5,000 clients. They face a constant challenge in aligning supply with the high demand from clients," Saurabh Jain, founder & CEO at Spire.ai, told AIM. To manage this, they address the supply-demand balance in several ways- building versus buying talent, rescaling excess supply, commoditising or monetising surplus, and internal resource management through bartering or lending. "For instance, suppose an organisation needs engineers skilled in React.js, but you have experts in Angular.js; those AngularJS professionals might still be valuable. They could potentially be trained in React.js within one to two weeks," Jain said. The AI assistant leverages the enterprise data and automatically provides this suggestion to the enterprise and also lists out the engineers who excel in Angular.js and can be reskilled for React.js. This saves the enterprise a lot of time and effort. Instead of hiring new talent for one project, they managed to meet the needs internally. This has a direct impact on the enterprise's operational margin. "This has to happen in real-time and on a continuous basis within organisations. Imagine if you're doing that for 300,000 employees globally across, let's say, 60 countries. You have to continuously know all of this. So for this you need intelligent systems to do that," Jain pointed out. Currently, the available systems are workflow-based, requiring enterprises to input workflows for the system to operate effectively, which, according to Jain, is a single point of failure. The AI assistant also analyses unstructured data from various sources, to offer skill inventory and profiling solutions and marketplace and talent cross-pollination. The Secret Sauce At the heart of Spire.ai is a Large Graph Model (LGM) featuring over 10 million sanitised graph nodes. This model encompasses skills across 26 industries, including tech, healthcare, retail, supply chain, defence, and pharmaceuticals. The LGMs process extensive data, such as job descriptions, industry trends, and learning materials, to automatically identify and generate various roles and the complex skill sets needed for them across any industry or business function. This self-evolving skill framework removes the need for manual mapping. "On top of the LGM, we have developed the Spiral Bot Engine, which powers our applications and focuses on search and match capabilities, integrating with data management, data inference, and interpretation layers. It supports data interpretation in over 250 global languages," Jain revealed. However, interestingly, the startup has not integrated Large Language Models (LLMs) into its solutions. The LGM, coupled with the Spiral Bot and the application and insight layer- which is also part of the architecture- is substituting an LLM right now. But they are not ruling it out, either. "There is a good amount of interest from the industry that, unlike a regular LLM chatbot, where the user invokes the engine, can the engine invoke the user and then carry the conversation? That is the last leg that we are working on," he said. Customers The startup's product is designed to solve hiring challenges for large organisations but can also be used by smaller and midsize enterprises. According to Jain, any organisation with over 500 employees will find Spire.ai's AI assistant useful. Moreover, for smaller enterprises, the startup plans to launch the solution in an 'application mode' this year, specifically designed for smaller enterprises whose employee count is less than 500. Currently, it serves large IT enterprises, telecom and communication companies as well as insurance companies in India.
Analytics India Magazine
Sat, 7 Sept, 2:00 PM UTC
How App.Symph AI simplifies app creation for everyone
Thanks to App.Symph AI, you will be able to make and use programs in seconds without knowing the software. App.Symph AI offers a platform where users can build their AI-powered apps with little or no coding knowledge. This makes it an attractive option for a wide range of people, from educators who want to streamline lesson planning to small business owners who need fast, customized solutions. So what exactly is Symph AI and why is it attracting attention? At its core, App.Symph AI enables users to develop AI-driven applications that solve specific problems or improve their daily workflow. This is done without the complex technical hurdles often associated with AI development. Pricing varies according to the user's needs, with options to suit both casual users and those in need of more comprehensive features. Whether you are keen on automation or need a quick solution for mundane tasks, Symph AI's capabilities are worth exploring. The most remarkable feature of the App.Symph AI is its accessibility. Users don't need prior experience in programming to create useful applications. Symph AI eliminates complexity on the backend by using pre-built templates and customizable tools. Users can focus on what matters - accomplishing their tasks faster and more efficiently. We have tried this artificial intelligence for you. You can easily use this tool by following the steps: That's it, your program is done. You don't even need to write code. You can also try the program we wrote via this link. Symph AI's pricing structure offers flexibility. It includes a free version, allowing users to test the platform without any financial commitment. For those who need more advanced features, such as higher usage limits or additional templates, paid plans start from $8 per month. There's also a $20/month option for heavier users who want even more power and versatility from the platform. Additionally, Symph AI can be used in many professional fields. It's not limited to tech-savvy users. For instance, educators can use it to create quizzes or interactive lessons, while small business owners might find it useful for automating routine administrative tasks. While many platforms offer templates, Symph AI allows users to customize these templates according to their specific needs. Applications created within Symph AI can be tailored with unique commands or personalized workflows, providing a greater level of control compared to other tools on the market. Another standout feature is the user interface. It is designed to be intuitive, guiding users step-by-step through the app creation process. Even non-tech-savvy users will find it easy to navigate thanks to its clean and simple layout. Symph Al is not just for hobbyists. It is also useful for work, school, and personal tasks. Its wide range of templates, customizable features, and flexible pricing make it suitable for both individuals and organizations. Users who want quick solutions without learning complex programming turn to Symph Al. Symph Al fills a gap in the market by providing a platform where anyone can build their Al-powered tools. It is likely to continue to grow in popularity among those looking for a simple yet powerful way to integrate Al into their daily lives.
Dataconomy
Wed, 11 Sept, 4:08 PM UTC
The future of B2B prospecting: The AI-powered research revolution
In today's hyper-competitive B2B landscape, the ability to identify and engage with the right prospects can be the determining factor in a sales team's success. Traditional methods of prospecting -- relying on outdated databases, navigating complex filters, and manually cross-referencing data -- are not only time-consuming but also limited in scope and efficiency. The advent of AI-powered B2B prospecting tools is transforming the way sales teams approach lead generation and pipeline building, offering a new paradigm in precision, speed, and scale. Historically, sales professionals have depended on legacy databases that cover only a fraction of the market, often providing access to just 20-30% of potential leads within any given sector. This limitation leaves a vast number of untapped opportunities, as sales teams frequently target the same prospects as their competitors, missing out on fresh leads that could drive significant growth. This information gap is a critical challenge that many sales teams may not even realize exists. By continually fishing in the same small pond, businesses risk stagnation and missed opportunities for expansion and revenue generation. AI-tools are addressing these challenges by leveraging advanced algorithms to parse vast amounts of data in mere milliseconds. These platforms are designed to identify key decision-makers across millions of companies and hundreds of millions of employee profiles globally, offering a level of specificity and speed previously unattainable in the sales industry. Unlike traditional databases that require extensive manual searches and broad filter manipulation, AI-enabled systems allow users to pinpoint the exact companies and contacts they need, whether it's niche specialists within a specific industry or leaders in emerging markets. This precision ensures that sales teams are reaching out to the right people, at the right time, with the right message, thus maximizing their chances of success. One of the most significant advantages of AI-powered prospecting is its ability to deliver actionable data in seconds -- a process that would typically take salespeople or sales enablement teams weeks or even months to complete manually. This efficiency accelerates the entire sales cycle, enabling teams to engage with prospects faster and more effectively, thereby shortening the time to value. The impact of this speed and precision is already being felt by companies across various industries. Organizations that have embraced AI-driven prospecting tools are reporting significant increases in their pipeline generation and revenue growth, as they can now identify and engage with new leads that were previously overlooked. Beyond speed and precision, AI-powered prospecting platforms offer a range of advanced features that enhance the sales process. These tools seamlessly integrate with existing CRM systems, ensuring that sales teams can expand their reach without disrupting their established workflows. Additionally, machine learning algorithms continuously refine and improve the quality of data, ensuring that users have access to the most accurate and up-to-date information available. A particularly valuable feature is the ability to filter out contacts that are already in a sales team's database. This functionality prevents wasted effort on duplicate outreach and allows teams to focus exclusively on new opportunities, thereby optimizing their resources and increasing their chances of closing deals. In an increasingly crowded B2B market, having a competitive edge is essential. AI-powered tools provide that edge by equipping sales teams with the means to uncover opportunities that might otherwise go unnoticed, all while simplifying the prospecting process. This technological advantage enables sales teams to pursue leads with confidence, spending less time on data gathering and more time on meaningful engagement with prospects. The difference between success and failure in today's market can be measured in minutes. By leveraging AI, sales teams are not just participating in the race but leading it. With unparalleled access to high-quality leads, businesses can close deals faster and more efficiently than ever before. As the B2B landscape continues to evolve, the importance of innovative AI tools in closing the information gap, improving lead quality, and accelerating the time-to-value will only grow. For sales teams looking to stay ahead of the competition, these AI-driven platforms offer a glimpse into the future -- a world where precision, speed, and intelligence redefine how we think about prospecting. In this new era, sales teams that embrace AI will find themselves at the forefront of industry innovation, equipped to navigate the challenges of the modern marketplace with unprecedented efficiency and success. We list the best sales CRM.
TechRadar
Thu, 12 Sept, 8:02 AM UTC
HubSpot Unveils AI-Powered Tools and Agents to Revolutionize Customer Relationship Management
HubSpot introduces Breeze, an AI-powered tool, along with four new AI agents and hundreds of product updates. These innovations aim to enhance customer relationship management and drive business growth.
7 Sources
Thu, 19 Sept, 12:04 AM UTC
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