Fragmented Pharmaceuticals: Why Indian Biopharma Does Not Have AI-Ready Data

When Silicon Valley was still recovering from the dot-com crash of the early 2000s, a new technological shift was quietly taking shape. Enterprises were beginning to discover the power of search, driven by the early success of Google. 

It was during this moment, in 2003, that Sai Gundavelli founded Solix Technologies in the US, with a vision that would eventually evolve from enterprise data archiving to building AI-ready data foundations for global organisations.

More than two decades later, the Bay Area-headquartered firm has established itself as a foundational data platform provider helping enterprises prepare for the AI era, especially in the biopharma sector.

Today, global brands including McDonald’s, Starbucks, AIG, and Pepsi rely on Solix platforms for enterprise data management across structured, unstructured, and semi-structured environments.

Cost of Uneven Data in Life Sciences

In life sciences, data silos are more than an IT problem—they’re a strategic liability. Most healthcare and life sciences data today is fragmented, poorly standardised, and designed for billing or compliance rather than machine learning, which directly undermines AI accuracy, explainability, and clinical trust. 

“Healthcare and biopharma need AI-ready data because AI amplifies both the value and the risks inherent in how data is created, governed, and used in these highly regulated, evidence-driven industries,” Biswajeet Mahapatra, Principal Analyst at advisory firm Forrestor, tells AIM.

As AI increasingly supports clinical decisions, drug discovery, trial optimisation, and manufacturing quality, regulators now expect clear data lineage, context, and auditability to establish model credibility and compliance. 

He adds that organisations that invest in AI-ready data—clean, connected, well governed, and semantically consistent—are able to scale AI safely and repeatedly across R&D, care delivery, and operations, while those that do not remain stuck in pilots, exposed to regulatory risk, and unable to translate AI ambition into real-world impact.

Organisations need to work with data that is findable, accessible, interoperable, and reusable , underpinned by solid metadata, lineage and quality controls. “Without these foundations, AI models risk producing incomplete insights or compounding the inconsistencies already present in the data,” Greg Killian, SVP, Head of Business, Lifesciences and Healthcare at IT services company EPAM Systems, notes.

According to Grand View Research, the global clinical trials market size was estimated at $84.54 billion in 2024 and is projected to reach $158.41 billion by 2033, growing at a CAGR of 7.5% from 2025 to 2033.

From Data Archiving to AI Foundations

Initially, Solix specialised in data archiving, enabling organisations to optimise performance, backups, and storage costs.

However, the arrival of AI marked a turning point. “When AI came, we said, ‘without data, there’s no AI’. And without AI-ready data, there’s no AI,” Gundavelli notes.

The company now describes its approach as combining Information Architecture (IA) with AI—using AI to improve data architecture while simultaneously preparing enterprise data for AI deployment.

Beyond data preparation, Solix has expanded into enterprise AI platforms, including the development of small language models (SLMs) designed specifically for corporate environments. “You can chat with the data, create digital assistants, and operate through an enterprise data fabric,” the founder adds.

The platform integrates multiple AI ecosystems, enabling enterprises to choose models based on governance, cost, or compliance requirements rather than locking into a single provider.

“We are enabling enterprises to embrace governance on which LLM they want to use—whether Anthropic, Grok, or others. We provide the fabric; customers decide, ” he mentions.

This model-agnostic approach reflects growing enterprise demand for flexibility amid rapidly evolving AI ecosystems.

While headquartered in Silicon Valley, Solix has a significant development presence in India, with a team of around 500. The India team plays a central role in product engineering and innovation, particularly around AI-ready data governance and enterprise compliance frameworks.

A major growth focus for Solix is the pharmaceutical and biopharma sector, where data fragmentation continues to slow innovation.

“The paradigm of drug discovery is changing,” he says. “Every country is imposing its own data policy. The current way of bringing all data into one bucket is no longer sustainable.”

The company is already working with major pharmaceutical players and building platforms tailored to regulatory compliance and distributed research environments.

Solix’s platform applies medallion architecture principles, cleansing and transforming data into AI-ready formats capable of powering predictive analytics and discovery models. The company is also exploring synthetic data applications, particularly in life sciences.

“People don’t want to train on animals,” Gundavelli explains. “They want to train on synthetic data, which has a singular property.”

Rather than dictating usage levels, Solix provides infrastructure that allows pharma companies to integrate synthetic datasets securely within governed environments.

“We are providing a platform—multicloud, hybrid cloud—your data, your AI, your insights, your location,” he states.

Beyond enterprise clients, Solix is extending its technology into public healthcare through its nonprofit initiative, the Touch Alive Foundation. “We are working with hospitals throughout India,” Gundavelli notes. “A lot of hospitals are not digitised, so we are providing our own EHR (Electronic Health Record) platform for free.”

The goal is twofold: modernise healthcare delivery while enabling anonymised datasets that can improve medical research and drug development.

“The data is anonymous and compliant,” he emphasises. “Lifecycle management exists from creation to retirement of data.”

Public Sector and Medical Tourism Vision

Solix is also collaborating with the Telangana government as well as the central government on healthcare and data initiatives.

“The big opportunity and challenge for India is AI taking away jobs,” Gundavelli notes. “Healthcare can be a phenomenal opportunity.”

Solix executives say governance remains the company’s core differentiator. Rather than moving enterprise data into centralised repositories—a process that often creates delays—Solix’s approach brings governance directly to where data resides.

The company has developed a digital platform to structure India’s medical tourism ecosystem—a sector they believe could drive large-scale economic growth. “If India pivots to medical tourism, it creates jobs and accelerates drug development,” he exclaims.

According to Solix, discussions with policymakers are ongoing, with larger initiatives expected to emerge soon.

Navigating the Era of Data Sovereignty

The rise of global data protection laws, including India’s Digital Personal Data Protection (DPDP) Act, is reshaping enterprise technology architecture. This shift will fundamentally change computing infrastructure, pushing storage, and processing closer to national borders.

“As a software company, we are building platforms that allow compliance locally while enabling federated monetisation of data,” Gundavelli explains.

As enterprises transition from experimentation to scaled AI adoption, Solix sees its role as an infrastructure provider rather than an application provider.