Multi-Cloud’s $60M Fix: Tessell’s AI Promises To Tame the Database Beast

Introducing DataManagement.AI: Your Partner in the Generative AI-Driven Data Revolution

In today’s data-driven world, organizations face a paradox: while data is their most valuable asset, many struggle to unlock its full potential. Disparate systems, siloed workflows, and evolving compliance demands turn data management from a strategic advantage into a costly burden.

At DataManagement.AI (a brand of Towards AGI), we’re rewriting this narrative. We combine decades of industry expertise with cutting-edge Generative AI to transform how enterprises manage, govern, and leverage their data.

Why DataManagement.AI?

• Tailored Solutions: No two organizations are alike. We design bespoke strategies aligned with your unique data challenges and business goals.

• AI-Powered Precision: Automate data quality, governance, and utilization with GenAI models that learn and adapt alongside your operations.

• Future-Ready Agility: Our solutions evolve with the data landscape, ensuring you stay ahead of regulatory shifts, technological advances, and market demands.

Our Mission
To empower your organization to harness data as a strategic asset, not just a resource. We equip you to make confident, data-driven decisions, optimize operations, and outpace competitors in an era where AI reshapes industries overnight.

What’s Inside This Edition

• Case Study: How a Fortune 500 client slashed data processing costs by 60% using our GenAI-driven governance platform.

• Expert Insight: Why “hybrid-by-design” is the future of enterprise data architecture.

• Tool Spotlight: Meet DataSync AI—your new ally in seamless cross-cloud data integration.

Join us as we explore how intelligent data management isn’t just a necessity; it’s your gateway to innovation, resilience, and growth.

Ready to turn data chaos into a competitive edge? Let’s begin.

Tessell Secures $60 Million to Revolutionize Multi-Cloud Database Management with AI

Tessell, a multi-cloud database-as-a-service (DBaaS) startup, has raised $60 million in a Series B funding round led by WestBridge Capital, with participation from B37 Ventures, Rocketship.vc, and existing investor Lightspeed Venture Partners. The investment will fuel its global expansion and the launch of an AI-driven conversational interface to simplify database management, as companies grapple with inflexible legacy systems and costly cloud solutions.

Bridging the Cloud Divide

Co-founded by Bala Kuchibhotla, a veteran of Oracle and Nutanix, Tessell addresses the pain points of modern data infrastructure. Legacy databases often lock enterprises into single clouds, while managed services strain budgets with performance-based pricing.

Tessell’s platform promises 10x faster performance and 64–73% cost savings over three years by eliminating IOPS metering and leveraging NVMe storage for high throughput with predictable pricing. Its architecture ensures zero downtime during migrations and cross-cloud resilience, supporting AWS, Google Cloud, Azure, and Oracle Cloud.

AI-Powered Agility

The startup’s compatibility with major databases (MySQL, PostgreSQL, MongoDB, etc.) and vector databases positions it as a versatile choice for AI applications. “AI teams can dynamically scale databases on Tessell’s infrastructure,” Kuchibhotla noted.

The new funding will accelerate the development of its AI assistant, designed to streamline tasks like query optimization and troubleshooting through natural language commands.

Growth and Ambitions

With 40 customers - including Moody’s, Tata Capital, and Aditya Birla Capital—Tessell plans to expand into Europe and APAC while deepening its presence in the U.S. and India.

The San Ramon- and Bengaluru-based company also eyes analytics integration, enabling enterprises to analyze data from platforms like Snowflake and Google BigQuery directly within its ecosystem.

As cloud complexity grows, Tessell’s blend of performance, cost efficiency, and cross-cloud flexibility could redefine how enterprises harness their most critical asset: data.

Forget GPUs! Data Unity is GenAI’s Real Superpower

In the age of generative AI, data management transcends traditional priorities like storage and security, it has become a strategic imperative for unlocking enterprise value.

A comprehensive, intentional approach is vital not only for operational stability but also for harnessing data’s full potential in our interconnected, cloud-dependent landscape.

AI, as the pinnacle of hybrid cloud workloads, demands seamless integration of data across diverse environments to ensure security and accessibility.

The Hybrid Imperative: Lessons from Cloud Vulnerabilities

The necessity of hybrid strategies was starkly illustrated by a 2023 outage at a leading cloud provider, which crippled multinational operations for seven days, delaying financial transactions and disrupting critical applications.

This incident underscores the urgency for organizations to adopt diversified data and storage frameworks, mitigating risks tied to reliance on single providers.

Data is the lifeblood of modern enterprises, driving both operational efficiency and competitive edge. Effective management is foundational to AI advancement and digital transformation.

Enterprises grappling with fragmented data must prioritize organizing and centralizing information through robust platforms, a crucial step for AI development.

According to IDC, a mere 33% of enterprise data resides in public clouds, with the remainder scattered across on-premises systems, data centers, and edge locations. As GenAI adoption grows, edge-generated data will exacerbate this fragmentation.

Forward-thinking organizations are now enhancing data visibility, scalability, and redundancy, deploying parallel backup systems to eliminate single points of failure.

From Chaos to Clarity: Transitioning to “Hybrid-by-Design”

Many enterprises inadvertently create data silos through ad-hoc dispersal—a “hybrid-by-accident” approach that heightens security risks, inflates costs, and stifles AI potential. The remedy lies in a deliberate “hybrid-by-design” strategy, where infrastructure and data deployment across hybrid environments are meticulously planned.

This shift empowers businesses to leverage high-quality operational data for advanced AI training, inference, and retrieval-augmented generation.

Unified Architectures: The Backbone of Transformation

While data distribution mitigates risk, it requires integration to be effective. Enterprises are increasingly adopting unified architectures that streamline storage, centralize management, and enable seamless data access.

These frameworks, combined with intelligent platforms, facilitate analytics and GenAI integration.

Innovations like software-defined storage and unified control planes allow data and applications to move fluidly across hybrid and multi-cloud environments, optimizing performance, cost, and resilience.

IT leaders can enhance security and simplify management by embedding hybrid cloud experiences into systems, ensuring global data environments are both protected and efficiently managed.

Data Management: A Non-Negotiable Priority

Robust data management isn’t just a technical requirement—it’s a strategic shield against reputational and financial risks. The largest 2024 IT outage, potentially avoidable through unified data formats and failover systems, highlights the cost of oversight. Similarly, cyber vaults for mission-critical data offer rapid recovery during ransomware attacks, minimizing disruptions.

Leadership must recognize that unified, accessible, and secure data is the key to transforming raw information into business value. Without harnessing dispersed operational data, enterprises risk stagnation in the AI race.

In an era where data drives innovation, complacency isn’t an option—proactive, integrated management is the gateway to resilience and growth.

Thank you for reading

DataManagement.AI & team