by Csongor Fekete | Nov 13, 2025 | AI, Business, Machine Learning
Amanda Kahlow, founder of 6sense, has launched a bold new venture named 1mind, backed by $30 million in funding. The startup aims to revolutionize sales by replacing traditional human roles with custom AI agents, pushing the boundaries of performance and scalability in martech.
The core idea behind 1mind is to use "AI minds" as highly personalized sales reps capable of handling multiple buyer interactions simultaneously. These custom AI models are designed to align deeply with a company’s tone, values, and customer journey while leveraging massive datasets to optimize outcomes. Kahlow envisions transforming the way brands communicate—more intelligent, more scalable, and more emotionally aware.
A standout use-case emerging from this innovation is in demand generation. Imagine deploying AI agents that can autonomously qualify leads, nurture them with contextual messaging, and tailor offers based on predictive behavior modeling. This kind of AI-supported funnel management can dramatically increase ROI and customer satisfaction while reducing time-to-sale.
For businesses dedicated to holistic AI implementation, especially in CRM and martech, the approach showcased by 1mind provides a viable blueprint. With the right AI partner or AI consultancy, companies can build Machine Learning models uniquely designed to amplify sales performance and humanize automation—reshaping customer relationships in the process.
Original article: https://news.google.com/rss/articles/CBMiygFBVV95cUxNR1h4Tjk5QVN2ME5XUGpkZndHcndjNDVSdzlqSTB4dHoybEgwWk5uRkROaFVTZXZPVnNUZGJMSkEwNnlHSTMxSFJoVUkwZ29GUTV5d0haWkVzWUx6ZTdMbUM4cXRFTWF3XzZaYUh4RHlNcUJfOUVKNS1sTm02bGpqX2dLZGpsSGNRSm9SOGxGbVo0aUVndm5DWGtsT28wcGw4eUR4ODdNTFp5ek9fblpoMjd2M24zRnVFQTA4YlNvTHEyYl92amlEVWl3?oc=5
by Csongor Fekete | Nov 12, 2025 | AI, Business, Machine Learning
A new entrant in the generative AI space is shaking the landscape with bold claims: a Chinese AI model named "01.AI Yi-34B" asserts it can outperform both GPT-5 and Anthropic’s Claude Sonnet 4.5. Even more notable, it’s open-source and freely available. According to benchmark results on Hugging Face’s leaderboard, the model ranks third globally for open large language models (LLMs) and first among models with fewer than 70 billion parameters, making it a compelling alternative for developers and enterprises alike.
The creator, venture capitalist and former Google China leader Kai-Fu Lee, highlights that 01.AI Yi-34B achieves top-tier performance with only 34 billion parameters, suggesting efficient architecture and data curation. It stands out not just for cost-effectiveness but also for multilingual capabilities, including English and Chinese, with plans for expanding its linguistic diversity. Optimized versions for laptops and smartphones are reportedly on the horizon, indicating a shift toward broader accessibility and AI democratization.
The implications for businesses are significant. Custom AI models that rival big-budget alternatives create opportunities for brands to develop tailored Machine Learning models at reduced cost without sacrificing performance. For martech and marketing, this means faster go-to-market strategies with advanced customer segmentation, personalized recommendations, and real-time analytics grounded in high-quality language comprehension.
A relevant use-case in CRM could involve deploying a lightweight, multilingual model like Yi-34B to improve customer satisfaction through smarter, more context-aware virtual assistants or intelligent ticket routing. HolistiCrm’s AI consultancy could leverage such models to develop bespoke AI features that align with each client’s unique data and workflow needs—delivering holistic performance across touchpoints.
As the competitive landscape evolves, partnering with an AI agency that enables adoption of open-access, high-performing LLMs will be crucial to future-proof strategies and elevate customer experiences.
Original article
by Csongor Fekete | Nov 12, 2025 | AI, Business, Machine Learning
Opendoor’s Q3 results paint a telling picture of the challenges and opportunities businesses face when integrating advanced technology into core operations. While the company's revenue of $980 million outpaced Wall Street expectations, its EPS fell short, resulting in a third-quarter net loss of $106 million. The discrepancy stems largely from the company’s transition to a new AI-powered pricing model.
This shift toward custom AI models is driven by a desire to improve unit economics and overall performance. Opendoor is adapting its Machine Learning model to be more "holistic," integrating both real-time market data and behavioral insights to price homes more effectively. Although this AI transformation has introduced short-term volatility, it signals a longer-term strategy focused on optimization and scalability.
From a martech perspective, this case study highlights how tailored AI solutions can enhance customer satisfaction by creating more accurate, responsive pricing systems. In real estate, a more dynamic pricing engine can improve conversion rates and reduce holding costs—both key to profitability.
For AI consultancies and agencies, this reflects a valuable use-case: combining domain-specific expertise with custom Machine Learning modeling to unlock efficiencies in sectors undergoing digital transformation. Companies adopting AI thoughtfully—while aligning it with business goals—are more likely to see sustainable growth.
As organizations in verticals like property, finance, or marketing begin similar transitions, the importance of engaging an AI expert or AI consultancy becomes clear. Building, testing, and maintaining such systems requires both technical expertise and a deep understanding of business objectives.
Original article: https://news.google.com/rss/articles/CBMihwFBVV95cUxQVE1mdXZvQWhFaFEwdjRNZHo3YjVvbXRHUHpQUHJicjdTN3dCb2RHT182ajA1TFp5M295Ti1BUkJ5dkU2M21FMFNtVXJIQUJBRExlNHo2ZjZfWTI4ajc1SlNDR1A4TXAzM040Z1BBMmtZWWlpR3B6M25DYUV3aHVuLTZmVXlkYmc?oc=5
by Csongor Fekete | Nov 11, 2025 | AI, Business, Machine Learning
Alibaba-backed Moonshot AI has made headlines again by rolling out its second generative AI model in just four months, signaling a rapid pace of innovation in China's intensifying AI race. The new model, dubbed Kimi, is designed to improve performance with longer context handling capabilities—accepting up to 2 million Chinese characters—which rivals or surpasses models available in the U.S. and Europe. Moonshot’s swift product iteration reflects China’s growing ambition to challenge Western AI dominance, particularly in generative AI and large language models.
The key takeaway is speed: Moonshot’s ability to ship frequent, substantial updates shows the strategic importance of custom AI models in a competitive landscape. Backed by Alibaba and Sequoia Capital China, Moonshot’s R&D intensity underlines the commercial importance of vertical AI capabilities tailored to local markets and languages.
A use-case with direct business value tied to this story can be seen in localized customer support automation. A company that integrates a custom AI language model capable of deep contextual understanding—like Kimi—into its martech stack can deliver hyper-relevant customer interactions in native languages. This boosts customer satisfaction, reduces support operational costs, and strengthens brand trust. HolistiCrm’s AI agency approach to building domain-specific models enhances CRM systems with holistic insights, enabling companies to turn massive volumes of customer interaction data into strategic action.
For companies seeking to compete at this level, working with an AI expert or AI consultancy to develop proprietary generative capabilities is now more critical than ever in sustaining long-term marketing and performance advantages in the global martech ecosystem.
Read the original article here: original article
by Csongor Fekete | Nov 11, 2025 | AI, Business, Machine Learning
Apple is reportedly planning a major AI leap by integrating Google's Gemini AI model into a revamped version of Siri, according to Bloomberg and Reuters. This collaboration follows months of speculation around Apple’s generative AI strategy and signals a shift toward partnerships that prioritize performance and scale over proprietary-only solutions.
Key highlights from the article:
- Apple is considering licensing Google’s Gemini, an advanced generative AI model, to power new functionalities in Siri.
- The integration could be announced as early as June during Apple’s WWDC, marking Apple’s first major external AI partnership.
- Apple is still investing in its own Machine Learning models internally, but may rely on Google’s model for complex text and content generation tasks.
- This move emphasizes a pragmatic approach — prioritizing customer experience, speed to market, and performance over exclusivity.
From a business perspective, this decision reflects a maturing martech landscape where performance and customer satisfaction outweigh the need to build every AI solution in-house. For customer-centric platforms like HolistiCrm, this demonstrates the value of selectively integrating third-party custom AI models that align with business goals.
A relevant use-case could be HolistiCrm incorporating large foundation models, tuned with vertical-specific data, to elevate conversational AI in marketing automation or CRM support. This allows for rapid deployment of complex AI capabilities while maintaining agility in product evolution. Partnering with an AI consultancy or AI agency can help companies identify the right models to leverage, create a holistic technology stack, and deliver measurable impact across customer journeys.
Ultimately, this news is a reminder that in a hyper-competitive AI environment, the winning formula combines proprietary development with strategic integrations — always anchored on delivering customer value.
Read the original article: https://news.google.com/rss/articles/CBMiqwFBVV95cUxPMWdpb1JNUHY2UkRyZXdXWmhqU3kwVmVkRXByay1IMHNReTR3WVlmN2NoempoZmM5TVVCeTREQWJ4TGZaaXRlSUNQeDVhY2hkT2NPZ0FnWTFNZE02QXlTTlp4d2w4Vl93MU94b201MDZoR1ZnelpPY2Q3OWZ4OXR2Z1NEMVlmcGdhWWdnS2lzMEJiM3dNUjRRWmNkS0UtUkpqRTIzOFJEQU00MVE?oc=5
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