Kris@Work Expands Leadership with Three Co-Founders, Targets Enterprise GTM Platform Scale

Kris@Work, an AI-native go-to-market platform for enterprise sales teams, elevated three senior executives to co-founder positions on 18 June 2026. Ananta Joshi, Samanvith Reddy Balugari, and Sunil Chandra Angara now serve as co-founders alongside CEO Arun Singh, marking a shift from the original founding team to a broader leadership structure as the company scales customer deployments.

The three new co-founders bring specialized technical backgrounds to the platform's core engineering. Joshi, an IIT Bombay alumnus and former global leader at Sprinklr, will focus on product vision and AI execution architecture. Balugari, an IIT Madras alumnus with prior engineering experience at Indeed, is tasked with developing scalable AI-led engineering systems. Angara, also from IIT Madras and previously at Goldman Sachs, will oversee enterprise-grade platform scale, reliability, and performance. The company's product is a unified AI-native platform covering the full sales cycle—from initial customer contact through closed deals to expansion—addressing fragmentation across CRM and sales tools.

Kris@Work's technical approach centers on replacing disparate point solutions with a single AI-driven system orchestrating go-to-market workflows. Early customer deployments have reported performance improvements of up to 15x in specific metrics, though the company has not disclosed exact measurement criteria or timeframes. The platform's architecture appears designed to ingest data from existing CRM systems and sales tools, then apply AI models to automate lead routing, deal progression, and forecasting—reducing manual data entry and reconciliation common in enterprise sales stacks.

The announcement places Kris@Work in a competitive market for AI-powered sales platforms, where players like Gong, Outreach, and Salesforce's Einstein compete for enterprise budgets. With InfoEdge Ventures backing, the company has financial runway to scale its engineering team and pursue customer acquisition beyond initial deployments. Pricing and release schedules for general availability remain undisclosed, though the co-founder additions signal readiness to move beyond early access into broader market distribution. The leadership restructuring suggests Kris@Work is preparing for a growth phase, leveraging the newly formalized founding team's combined expertise in product strategy, engineering scalability, and enterprise reliability.

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ARC on ARC Announces Gaming Hardware Ambitions Without Revealing Core Details

ARC (branded as "ARC on ARC") has formally announced its company launch, positioning itself as a dedicated gaming hardware firm targeting the Indian market. The venture, founded by lifelong gamers Jobin Joseph and Kaustubh K Jadhav, is currently developing a handheld gaming device. According to a press release, the company's stated vision is to make premium gaming more accessible for Indian consumers. No specific technical specifications, model names, versions, pricing, or launch timeline have been disclosed at this stage.

The handheld device remains in active development, with no confirmed release window or retail price. Both founders are described as lifelong gamers, though their prior industry experience or technical backgrounds were not detailed in the announcement. The company has not yet released any software or hardware prototypes to the public, nor has it demonstrated a working unit. The press release emphasizes the goal of reducing cost barriers for local players but stops short of revealing how the device will achieve this compared to existing handheld consoles in the market.

The Indian gaming hardware market is dominated by global players such as Valve's Steam Deck, Nintendo's Switch, and various Android-based handhelds, with localized pricing and availability often being major hurdles. ARC on ARC's entry adds a domestic option to this segment, but without concrete hardware details, pricing strategy, or a release schedule, the company has yet to demonstrate how it will compete. The announcement provides no information on manufacturing partnerships, distribution channels, or funding. Until these specifics are revealed, the device remains a long-term aspiration rather than an imminent product. The press release confirms that further updates will be communicated through the provided contact.

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Stay Informed: How to Get Hourly Updates on Brisbane Weather on Your Smartphone

 Are you planning a day out in Brisbane and wondering what the weather will be like? Keeping track of the weather is important for planning your activities and ensuring you have a comfortable experience. Brisbane is known for its sunny climate, but weather conditions can be unpredictable at times. To stay informed about Brisbane weather, there are several ways you can get important information on your smartphone every hour.

One of the easiest ways to stay updated is by installing a weather app on your smartphone. There are many apps available on both Android and iOS platforms that can provide you with real-time weather updates, hourly forecasts, weather maps, and weather radar. With a weather app, you can ensure you are always aware of the temperature, humidity, and other weather conditions in Brisbane.

In addition to a weather app, you can also enable the weather widget on your smartphone's home screen. The widget is a small window that displays the current weather conditions and forecast. Most weather apps come with a customizable widget that you can adjust to show hourly updates of the Brisbane weather, weather map, and weather radar.

Another option is to use Google Assistant on your smartphone. By simply asking "Hey Google, what's the weather like in Brisbane?", you can get an instant response about the current weather conditions in the city, including weather maps and weather radar. You can also ask for hourly updates by saying "Hey Google, what will the weather be like in Brisbane in the next hour?"

Finally, you can visit the Bureau of Meteorology website, which is the official government agency responsible for providing weather information in Australia. Their website provides detailed weather forecasts, weather maps, and weather radar, and satellite images for all major cities, including Brisbane. By visiting their website, you can view the hourly forecast for the next 48 hours and get information on temperature, humidity, wind speed, rainfall, and other weather-related information.

In conclusion, there are many ways to get important information on Brisbane weather on your smartphone every hour, including weather maps and weather radar. Whether you choose to install a weather app, enable the weather widget, use Google Assistant, or visit the Bureau of Meteorology website, staying informed about the weather conditions is crucial for planning your activities in Brisbane. So, next time you plan a day out in Brisbane, make sure to check the weather beforehand and stay prepared for any unexpected changes in the weather.

Disclaimer: This post is generated by AI

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Machine Learning in Finance: Applications, Challenges, and Opportunities

 Machine Learning (ML) is a rapidly evolving field that has the potential to revolutionize the way financial institutions operate. With the ability to process large amounts of data and identify patterns, Machine Learning can help financial institutions make better decisions, manage risks, and improve customer experience. In this blog post, we will explore the applications, challenges, and opportunities of Machine Learning in finance.

Applications of Machine Learning in Finance:

1. Fraud Detection: Financial institutions are often targeted by fraudsters who attempt to steal money or sensitive data. Machine Learning algorithms can be trained to identify patterns in transaction data and flag suspicious activity, which can help detect and prevent fraudulent transactions.

2. Credit Scoring: Machine Learning can help financial institutions evaluate the creditworthiness of borrowers by analyzing data such as credit history, income, and employment status. This can help lenders make more accurate decisions about loan approvals and interest rates.

3. Investment Management: Machine Learning can assist investment managers in analyzing large amounts of data to identify trends and patterns, which can help in making informed investment decisions. This includes predicting stock prices, analyzing market trends, and identifying investment opportunities.

4. Risk Management: Machine Learning can help financial institutions assess and manage risks by analyzing large amounts of data related to credit, market, and operational risks. This can help in identifying potential risks and taking proactive measures to mitigate them.

Challenges of Machine Learning in Finance:

1. Data Quality: Machine Learning algorithms require large amounts of data to be trained, which can be a challenge in the finance industry where data quality can be poor. Data must be accurate, complete, and reliable to ensure that the algorithms produce reliable results.

2. Complexity: Machine Learning algorithms can be complex and difficult to understand, which can make it challenging for financial institutions to implement them. Skilled data scientists and engineers are required to develop and deploy these algorithms.

3. Regulation: Financial institutions are subject to strict regulations, and implementing Machine Learning algorithms must comply with these regulations. This includes ensuring that data is protected and that algorithms are transparent and explainable.

Opportunities of Machine Learning in Finance:

1. Cost Reduction: Machine Learning can help financial institutions automate repetitive tasks and streamline processes, which can reduce costs and improve efficiency.

2. Personalization: Machine Learning can help financial institutions personalize services and products based on individual customer needs and preferences, which can improve customer experience and loyalty.

3. Innovation: Machine Learning can enable financial institutions to develop innovative products and services that are more responsive to customer needs and market trends.

In conclusion, Machine Learning has the potential to transform the finance industry by providing valuable insights into data and helping financial institutions make more informed decisions. While there are challenges to implementing these algorithms, the opportunities for cost reduction, personalization, and innovation make it an exciting field with significant potential for growth. Financial institutions that invest in Machine Learning technologies today will be well-positioned to succeed in the future.

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Closing In: How AI and other Tech can Help Capture India's Wanted Criminals

Amritpal Singh, a Khalistani separatist with criminal charges wanted in several cases, has been on the run for days now. Despite multiple efforts by Indian law enforcement agencies, he has managed to evade capture. However, with the advancements in technology and the rise of Artificial Intelligence, Cyber Security, Data Analytics, and Big Data, there is a glimmer of hope that he and others like him can finally be brought to justice.

Artificial Intelligence (AI) is an advanced technology that enables computers to mimic human intelligence and perform complex tasks. In the case of Amritpal Singh, AI can be used to analyze vast amounts of data and identify patterns that could lead to his location. Using facial recognition technology, AI can analyze CCTV footage and social media images to identify Amritpal Singh and track his movements.

Cyber Security is another key technology that can be leveraged to capture Amritpal Singh. With the increasing reliance on digital systems, it is essential to secure sensitive data and prevent unauthorized access. By analyzing online communication channels and social media, cybersecurity experts can gather intelligence on Singh's activities and intercept any attempts to evade law enforcement.

Data Analytics and Big Data can also play a critical role in capturing Amritpal Singh. These technologies enable the collection and analysis of large amounts of data from various sources. By analyzing this data, law enforcement agencies can identify patterns and connections that could lead to the whereabouts of Amritpal Singh. They can also track his financial transactions and monitor his communications to gather intelligence and evidence.

The combination of AI, Cyber Security, Data Analytics, and Big Data can provide a powerful tool for Indian law enforcement agencies to nab Amritpal Singh. By leveraging these technologies, they can gather intelligence, track his movements, and intercept his attempts to evade capture. With the increasing sophistication of these technologies, it is only a matter of time before Amritpal Singh is brought to justice.

However, it is important to note that these technologies are not foolproof and require skilled professionals to operate them effectively. Additionally, there are ethical concerns around the use of AI and surveillance technologies that need to be addressed. It is crucial to balance the need for public safety with the protection of individual rights and privacy.

In conclusion, the use of Artificial Intelligence, Cyber Security, Data Analytics, and Big Data can provide a powerful tool for Indian law enforcement agencies to capture Amritpal Singh. By leveraging these technologies, they can gather intelligence, track his movements, and intercept his attempts to evade capture. With the right expertise and safeguards in place, these technologies can play a crucial role in improving public safety and bringing criminals to justice.

Disclaimer: AI generated post for research purposes.

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