Latest news with #TarunRaisoni
Forbes
17-06-2025
- Business
- Forbes
AI Agents Alone Won't Automate The Enterprise—But They Can Make It Smarter
Tarun Raisoni, CEO & Cofounder at Gruve Inc. Enterprise systems follow the rules by design. For decades, platforms like ERP, CRM and HR software have powered the backbone of business. But today's enterprises face new pressure: Move faster, do more with fewer resources and adapt in real time. The problem? Most systems they rely on were built for structure, not flexibility. And while APIs were once thought to be the fastest way to integrate business platforms, they've added more complexity and rigidity. That's where AI agents come in. AI agents bring a new layer of intelligence to enterprise automation. They don't just follow instructions, they interpret context, make decisions and take action with minimal human input. From classifying documents to triaging support tickets, they handle the messy, unstructured work that traditional systems struggle with. But AI agents aren't a standalone solution. While they excel at flexibility, they fall short when managing tasks where consistency and compliance are non-negotiable. That's why the smartest companies aren't choosing between traditional systems and AI. They're building hybrid automation models that combine the best of both. AI adoption is no longer about if but how. With 92% of companies planning to increase AI investment over the next three years, the focus is shifting from deployment to impact. Unlike traditional enterprise platforms, AI agents adapt. They interpret unstructured data, respond to changing inputs and take autonomous action, coordinating across systems without detailed instructions. Think of them less as static tools, more like dynamic teammates who can reason and act. This flexibility shines in context-heavy functions: • Customer Service: Classifying tickets, suggesting responses or resolving issues based on sentiment and history • Finance: Scanning invoices, flagging anomalies and feeding clean data into ERP systems • IT: Monitoring infrastructure and triggering remediation in real time What makes AI agents powerful isn't just their autonomy; rather, it's their ability to reason using enterprise-specific data. They fill gaps that traditional systems can't. Tools like Salesforce's Agentforce recommend the next best actions within CRMs, while Glean's agents let teams automate workflows like onboarding without writing code. These agents don't replace core systems; they extend them, adding intelligence where structure alone falls short. AI agents thrive when they're not working in isolation. To work effectively, they need orchestration. They must connect to the enterprise systems they rely on and the human teams that guide them. This orchestration layer is what enables hybrid automation to function. It ensures that: • AI agents hand off tasks to structured systems (like ERPs or CRMs) for compliant execution. • Human reviewers can step in when needed, especially for exceptions or sensitive decisions. • Processes remain auditable, traceable and aligned with business logic. We already see this across HR systems, IT workflows and facilities teams through automatically generating accounts, scheduling orientation sessions and provisioning equipment. However, those actions are governed by a central orchestration layer that ensures each step follows company policy, involves human oversight where needed and keeps the process compliant and consistent across regions. This isn't just automation; it's automation with guardrails that enable AI agents to move from experimentation into production. The more enterprises deploy AI agents, the more they need to think of them as a new kind of digital workforce. That means: • Oversight: AI agents need clear boundaries on what they're allowed to do and when to escalate. • Training: Just like employees, agents need context: domain-specific vocabularies, evolving workflows and access to the correct data. • Performance Management: Teams should monitor, evaluate and refine agents over time to improve output and prevent drift. Security and trust are also critical. Unlike rule-based systems, agents can make novel decisions, which makes explainability, audit trails and human-in-the-loop (HITL) frameworks essential. AI agents aren't a replacement; they're a multiplier. Their real value lies in being woven into the systems and processes that businesses already trust. Hybrid automation makes that possible, blending structure with intelligence to unlock new levels of scale and speed. In a landscape defined by pressure to move faster and do more, this isn't just a smarter model. It's the one built to last. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Yahoo
30-04-2025
- Business
- Yahoo
Gruve.ai promises software-like margins for AI tech consulting, disrupting decades-old Industry
Companies of all sizes are recognizing the game-changing possibilities of AI. Despite the excitement about the new technology, most of their pilot projects don't make it into production. a startup founded by the team behind Rahi Systems aims to help enterprises get AI solutions out of testing phase and into real-world application by using AI to deliver its services. Rahi Systems is an IT solutions company acquired by Wesco for $225 million in 2022. IT services firms, including major players like Accenture, have long been the go-to consultants to implement new tech projects for companies when they don't have the skilled staff in-house. However, given that their work relies on humans, their expertise often comes with a steep price tag. "Technology services industry hasn't been disrupted in the last 25 to 30 years," Tarun Raisoni, CEO of Gruve, told TechCrunch. "AI truly changes that dynamic." Gruve hopes to change the traditional IT consultancy model in two key ways: first, by reducing the need to hire a large staff of consultants by using AI agents for repetitive tasks. Second, by charging clients based on usage rather than on an hourly basis. In the past, VCs were generally not interested in investing in IT services in large part because their reliance on human labor made these businesses hard to scale. But by using AI agents instead of human consultants, Gruve can deliver software-like gross margins of 70% to 80%, which is significantly higher than the margins of traditional tech consultancies, said Navin Chaddha, managing partner at Mayfield. Gruve's innovative model and its team's experience building Rahi Systems has helped it raise a $20 million Series A round led by Mayfield, with participation from Cisco Investments and other investors. The fresh capital brings Gruve's total funding to $37.5 million. Raisoni said that his team first meets with the client to determine their AI needs and prepares their data to support AI applications before recommending and implementing AI solutions. "You must understand your customer's business before you can implement because their business processes are different, their workflows are different. How they service their clients is different," he said. But once Gruve is ready to implement, AI agents will handle tasks such as security breach detection and the transition from on-premises to cloud CRM. Similar to traditional IT consultancies, the company partners with select trusted tech vendors to implement their solutions for clients. Gruve's current partners include large companies like Cisco, IBM's Red Hat, and Google, as well as about a dozen AI-native startups like Glean and Supervity. But unlike most tech consultancies, Gruve won't bill its clients when the solution is first implemented. Their "services are available on demand, the same way electricity is provided or the same way cloud computing is provided," Chaddha said. For example, if Gruve has implemented AI for security, the company will only charge the client upon a security breach detected and analyzed by the installed AI. This article originally appeared on TechCrunch at Sign in to access your portfolio
