AI Tool Builds Predictive Models from Raw Data
A platform called Elai is being pitched as a "data science agent" for GTM teams. The tool uses generative AI to create predictive models for lead scoring, churn risk, and cross-sell opportunities directly from raw CRM and product usage data, aiming to eliminate the need for an in-house data science team.
The company behind the platform, formerly known as BigProfiles, was founded in 2018 by Lorenzo Luce and Roberto Visceglia and rebranded to Elai after a €3 million investment from AI Acceleration. This funding aims to democratize predictive AI, making it accessible to business functions without deep data science expertise. Elai's platform functions as an autonomous data science agent, using generative AI to reason through raw data, build predictive models, and reduce costs by up to 90% compared to traditional methods. The shift toward signal-based GTM is a direct response to rising customer acquisition costs and declining returns from volume-based outbound sales. Teams using this approach report up to 3x higher meeting booking rates by focusing on accounts showing active buying signals like hiring patterns, funding events, or increased content engagement. Platforms such as 6sense, Demandbase, and ZoomInfo are central to this strategy, providing the intent data that allows sales teams to time their outreach precisely when buyers are in-market. For technical buyers of API products, the sales process is shifting from a focus on features to a value-based conversation about solving business problems. In India, a major hub for API production and export, global buyers are increasingly prioritizing suppliers with strong regulatory compliance (FDA, EMA), transparent pricing, and sustainable "green chemistry" practices over just the lowest cost. This requires sales leaders to equip their teams to discuss total cost of ownership, integration support, and long-term partnership value. In India's HR tech landscape, the focus for 2026 is moving from simple AI chatbots to "agentic AI" that can autonomously handle workflows like screening candidates or scheduling interviews. With the shelf-life of technical skills dropping to just 2.5 years, companies are prioritizing verified skill badges over traditional degrees, creating opportunities for API-driven HR platforms that can track and verify micro-credentials. Furthermore, the full enforcement of the Digital Personal Data Protection (DPDP) Act requires HR systems to integrate with "Consent Managers," a new layer of the tech stack. The Bangalore tech ecosystem, a key market, saw a funding slowdown in 2025, with total capital raised for Karnataka-based tech companies dropping to $3.8 billion. However, early-stage funding proved resilient, increasing by 32% over 2024 as investors shifted focus from large late-stage deals to younger companies. Enterprise applications and fintech were the top-funded sectors, attracting $1.1 billion and $1.0 billion respectively. As leaders transition from individual contributor roles, the most common failure point is an inability to shift from being a "deal-doer" to a "rep-developer." Effective scaling requires standardizing the sales process and creating a structured onboarding program before hiring new team members. About 60% of new sales managers report receiving no formal training for their leadership role, highlighting a critical gap in development.
