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Founder Vantage Launches AVISHKAR to Help Indian Founders and Businesses Build Visibility in AI Search
Founder Vantage, the growth acceleration lab by Umanshi Marketing and Manimala Hazarika, has launched AVISHKAR, a Generative Engine Optimization (GEO) service designed to help founders and founder-led businesses show up accurately and credibly when investors, partners, and clients research them using AI platforms. AI has changed how business decisions begin. Before an investor agrees to a meeting, before a journalist writes a profile, or before a potential customer reaches out, many now start with a simple step. They ask an AI tool. Platforms such as ChatGPT, Gemini and AI-powered search tools are increasingly becoming the first-place people turn to when they want to understand who a founder is, what a company does and whether it is credible. What comes back in those few paragraphs generated by AI is often the first impression that shapes whether the conversation moves forward. "Over the years we have helped founders build credibility through PR, narrative strategy and media visibility. What we are seeing now is that before many of those interactions take place, there is an AI query. For many founders and family-run businesses, that first impression is often incomplete, outdated, or missing entirely. Not because the business lacks substance, but because the way AI systems gather and present information is very different from how traditional search engines worked. AVISHKAR is designed to ensure that when that query is made, the answer reflects the founder's real work and expertise," said Tamanna Gupta, Founder of Umanshi Marketing. Most businesses simply have not structured their digital presence for this new environment. The issue is not usually misinformation. The issue is invisibility. AI systems rely on signals drawn from structured information, credible citations, and consistent data across multiple online sources. When a company's digital presence is scattered across platforms, when different sources describe the business differently, or when key profiles and databases remain outdated, the AI often skips over that entity entirely. AVISHKAR, the Generative Engine Optimization service launched by Founder Vantage, is designed to address exactly this gap. The service begins with an AI visibility audit that examines how a founder and their business currently appear across major AI platforms and where information gaps exist. From there, the Founder Vantage team works to align and strengthen the company's digital footprint across platforms. This includes ensuring that business databases, professional profiles, media references, and official company information are consistent and credible across the web. The objective is straightforward. When someone asks an AI about a founder, their industry, or their company, the business appears and the information presented reflects who they actually are. "A lot of the founders and family business owners we work with built their reputation through relationships, word of mouth, and years of consistent work. They never had to think about how an AI system might represent them. What we are telling them now is that there is a new room where that reputation either exists or it does not. If investors, partners, and clients are beginning their research with AI, it becomes important to ensure that your presence in that environment is accurate, consistent, and visible," said Manimala Hazarika, Brand and Marketing Strategist and Partner at Founder Vantage. The launch of AVISHKAR comes at a moment when AI-assisted research is rapidly becoming a normal part of business decision-making. For founder-led and family-run businesses, where the credibility of the individual and the reputation of the company are often closely connected, how both appear in AI-generated answers can increasingly influence introductions, partnerships, and deal flow. Founder Vantage believes that as AI search becomes more widely used, ensuring that founders and businesses are correctly represented within these systems will become an essential part of modern brand and reputation management.
CXOToday
Wed, 1 Apr, 12:36 PM UTC
Clodura.AI Unveils Atlas: The AI-Native SDR for True Personalization at Scale Clodura.AI Unveils Atlas: The AI-Native SDR for True Personalization at Scale
Clodura.AI today announced the launch of Atlas, an AI-native Sales Development Representative (SDR) designed to deliver truly personalized outreach at scale by unifying Proprietary Data, Intelligence, and Execution into a Single Automated AI platform. Despite the rapid growth of sales tools, outbound execution remains fragmented. Teams rely on multiple disconnected tools for contact data, enrichment, research, sequencing, and deliverability, while spending significant time stitching these together. Even recent AI solutions have largely operated as overlays on this stack, generating template-based outreach on top of shallow/static data or simple wrappers around LLMs. Atlas was built grounds-up to replace this model entirely. Available within the Clodura.AI platform, Atlas brings together a proprietary database of hundreds of millions of contacts and companies, multi-source enrichment, real-time signal detection, email verification, and delivery infrastructure with a system of AI agents that execute end-to-end outbound sales. From identifying target accounts and researching prospects to generating messaging, structuring multi-step cadences, and launching campaigns, Atlas operates as a single, unified system with full-stack automation. At its core, Atlas is driven by a deep intelligence layer that models three dimensions before generating outreach: the seller's product and positioning, the target company's context and signals, and the individual prospect's behavior and communication patterns. By analyzing factors such as career trajectory, role context, and inferred decision-making style, Atlas generates a fully original email for each prospect and orchestrates it within a structured, multi-phase cadence designed to drive meaningful conversations over time. The platform continuously enriches and verifies contact data in real time, ensuring accuracy before every interaction. Email addresses are validated prior to sending to reduce bounce rates and protect domain reputation, while built-in deliverability systems test and optimize campaigns to maximize primary inbox placement. The intelligence behind Atlas is built on Atlas University, a proprietary four-semester training programme built on 10 million successful outbound emails, 5 million subject lines, and over 100,000 A/B-tested campaigns. The curriculum draws from established sales methodologies, Sandler, SPIN, Challenger, Gap Selling, as well as behavioural economics and cross-cultural communication patterns across 50 countries. Atlas automatically matches the appropriate sales framework to each prospect's profile, with a 95% style-match accuracy across prospect types and industries. This enables it to dynamically adapt tone, structure, and messaging strategy based on context, rather than relying on static templates or prompt-based generation. Every Atlas campaign follows a five-phase cadence, Hook, Value, Proof, Bump, Breakup, each phase carrying a defined psychological objective. A key design choice differentiating Atlas from other AI SDR tools is its human-approval model: teams review sample emails per prospect and can edit or regenerate any message before the full sequence goes live. Clodura.AI describes this as governed agentic execution, a deliberate departure from black-box automation. On deliverability, Atlas runs every campaign through a pre-launch testing protocol against over 250,000 test inboxes before a single real email is sent, achieving 95% Primary inbox placement. In production deployments, Atlas campaigns have achieved open rates exceeding 40% and reply rates above 4%, significantly outperforming prevailing industry averages of under 10% and 0.5% respectively, an 8X improvement in reply rates and a 4X improvement in open rates. "The problem with outbound today isn't effort, it's that most of it is built on incomplete context," said Kapil Khangaonkar, Founder and CEO of Clodura.AI. "Most AI SDR products generate variations of the same template on top of limited or rented data. Atlas was built differently. It is trained on millions of real outbound interactions, proven sales methodologies, and continuously updated intelligence across hundreds of millions of contacts and companies. What this means in practice is simple, every message is grounded in real context, not guesswork. When you combine that depth of data with full-stack automation and execution, you don't just automate outreach, you fundamentally improve its relevance and effectiveness." The launch comes as go-to-market teams increasingly move away from fragmented toolsets toward unified platforms that combine data, intelligence, and execution. Clodura.AI positions Atlas as part of a new class of AI-native systems designed to operate across the full sales workflow.
CXOToday
Tue, 14 Apr, 6:33 AM UTC
If AI Can't Find You, Neither Can Your Clients
The other day, I needed to look something up, and instead of giving it a Google search, I opened Claude and typed my question. I got a clear, organized answer in seconds without ads, without 10 blue links, and without having to cross-check review sites. It was faster and more useful, and I moved on quickly after getting the information I needed. Then, it hit me. If I am doing this, my prospective clients are doing it, too. The question every woman founder needs to ask right now is not whether AI is changing the way people buy. It is whether you are showing up when they ask. The shift is already happening The numbers make it impossible to ignore. According to research from the University of Virginia, nearly 60% of consumers have used AI to help them shop. Nearly 66% of frequent online shoppers report regularly using AI assistants such as ChatGPT to inform their buying decisions. Another 34% are turning to AI for initial product discovery, according to Yahoo Finance. This is not comparison shopping. This is the top of the funnel. People are asking AI who to hire, what to buy, and whose work to trust before they ever visit a website or read a review.
Inc.
Sat, 9 May, 8:00 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.
AIM
Sat, 7 Sept, 2:00 PM UTC
Skylark AI Launches Purpose-Built AI Engine to Revolutionize Private Investment Analysis and Enterprise AI Deployment
Skylark AI launches its revolutionary PyTorch Engine and Enterprise AI Platform, transforming private investment analysis and enterprise AI deployment. With 100% data ingestion, 100% recall, and 95% accuracy, it enables AI-powered agents to deploy in days, not months. Powered by 50+ pre-built integrations with sources like Cap IQ and FinHub, it creates a unified system of records, reducing due diligence timelines by 40% and cutting operational costs by 80%. New York, NY November 20, 2024 --(PR.com)-- Skylark AI Introduces PyTorch Engine and Enterprise AI Platform for Private Investment Analysis. Skylark AI, a leader in artificial intelligence for enterprise applications, has announced the launch of its PyTorch Engine and Enterprise AI Platform, a technology designed to address challenges in private investment analysis and enterprise AI deployment. The platform leverages advanced AI capabilities to streamline workflows, improve decision-making, and reduce operational inefficiencies. The platform is built to deliver 100% data ingestion, 100% recall, and 95% first-draft accuracy, thanks to its integration of a human-in-the-loop workflow. Skylark AI enables businesses to deploy AI-powered agents within days, a significant improvement over traditional timelines, which can take months. A Unified System of Records A key feature of the platform is its ability to integrate with over 50 data sources, including Cap IQ and FinHub, allowing businesses to unify their internal and external data into a single system of records. This integration ensures that data is accessible, accurate, and actionable, addressing common challenges in fragmented data management. Purpose-Built for Private Investment Workflows The platform includes features tailored to private investment professionals, such as: Unified "One-View" Access: Consolidating all data, files, and insights related to investment targets in one place. AI-Driven Insights: Enhancing analysis of contracts, portfolios, and market trends. Automated Deliverables: Generating detailed reports, presentations, and summaries with minimal effort. Workflow Optimization: Improving operational accuracy through human-in-the-loop collaboration. Real-World Impact Skylark AI has reported significant results from early adopters of the platform: 40% Reduction in Due Diligence Timelines: Achieved through faster and more accurate data retrieval. 30% Increase in Strategic Focus: By automating repetitive tasks like data standardization. 80% Reduction in Operational Costs: While improving satisfaction and accuracy. Industry Implications The new platform addresses a critical need for businesses in the private investment and financial sectors to manage complex data efficiently. By reducing reliance on manual processes and introducing scalable AI-driven solutions, Skylark AI aims to set a new standard in the industry. "This platform is a culmination of extensive research and collaboration with our clients," said Rajeev Kapoor, Chief Product Officer at Skylark AI. "It bridges the gap between fragmented data and actionable insights, allowing enterprises to operate more efficiently while scaling their capabilities." About Skylark AI Skylark AI specializes in AI-driven solutions for financial and enterprise applications. Focused on scalability, precision, and seamless integration, Skylark AI supports businesses in transforming how they access, analyze, and act on data. For more information, visit www.skylarkai.com. Media Contact Adi Kapoor Investor Relations Skylark AI Inc Email: [email protected] Phone: +1 (201) 620-1585 Contact Information: Skylark Ai Inc. Adi Kapoor +1 201-620-1585 Contact via Email www.skylarkai.com Read the full story here: https://www.pr.com/press-release/925802 Press Release Distributed by PR.com Market News and Data brought to you by Benzinga APIs
Benzinga
Thu, 21 Nov, 12:12 AM UTC
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