The Compliance Engine Powering India’s Fastest Growing Companies

Whenever a new company is born, founders sprint towards the familiar frontiers of product, market fit, customers, and capital. What almost never appears on the early roadmap is compliance. It sits quietly in the background until scale arrives. Then it reveals itself as a core operational function. Most teams discover this while closing enterprise customers, raising funding, or preparing for audits. They end up doing compliance not once, but repeatedly.

And when vendors begin sending questionnaires and access review requests, the workload grows even further. Evidence collection, policy updates, risk logs, system checks, and attestation trails expand into a parallel universe that founders never planned for.

The strain has intensified further after GDPR enforcement in 2018. What was once an occasional audit has shifted into an expectation of continuous clarity around data flows, access patterns, and control behavior.

The Hidden Operational Cost of Hypergrowth

Hypergrowth introduces a parallel workload that most founders and CTOs never plan for. As companies begin selling to enterprises, entering new markets, or preparing for funding rounds, compliance shifts from being a nice-to-have to becoming table stakes. Leaders suddenly find themselves spending hours interpreting frameworks, collecting evidence, responding to security questionnaires, and coordinating with auditors. Despite operating on modern cloud stacks, much of this work still lives in spreadsheets and email threads.

The cost is not just administrative; it is strategic. Time consumed by manual compliance work is time taken away from refining product-market fit, responding to customer feedback, unlocking new segments, and articulating value to investors. For companies expanding across geographies, overlapping regulatory expectations intensify the strain. Compliance should enable hypergrowth, but without the right systems, its manual overhead often slows progress at the moment speed matters most.

Where Traditional Approaches Fall Short

For Sprinto’s founders, this challenge was not theoretical. While building Recruiterbox, Girish Redekar and Raghuveer Kancherla encountered rising compliance demands at every stage of scale. Meeting standards like SOC 2 or ISO 27001 required more than documentation; it demanded a clear understanding of how systems, users, vendors, risks, and controls interacted in an environment that was constantly changing. Existing tools captured data but failed to surface what needed attention or why.

As the founders validated this experience with other fast-growing companies, a clear pattern emerged. Compliance tools were built for static environments, while modern organisations change daily. Without context, automation remained shallow and teams were left reconstructing reality each time scrutiny arose. This gap revealed the need for a new approach: compliance systems that understand how a business operates and adapt continuously. That insight set the foundation for Sprinto and leads directly into the role of intelligence-driven, agentic systems in modern compliance.

“Most GRC tools collect information, but they don’t tell you what to do with it,” Girish says. “Teams are left with data, not direction.”

The Role of Agentic AI in Modern Compliance

The shift toward intelligence-driven compliance is not being powered by generative AI. Generative models can produce content, but compliance demands contextual reasoning. It requires the ability to interpret dependencies, monitor control behavior, understand anomalies, and operate within clearly defined organisational boundaries. This is where agentic AI is beginning to reshape the category.

Agent-based systems can take multi-step actions, correlate signals across tools, and maintain a live understanding of the environment while keeping humans firmly in control. Sprinto’s AI Playground reflects this direction. Teams can build task-specific agents within minutes to automate vendor reviews, document analysis, incident classification, and risk drafting. Hours of administrative effort convert into supervised, high-clarity workflows.

The timing is significant because companies are confronting a new risk: Shadow AI, where employees rely on external AI tools that can unintentionally leak sensitive data. This has created a need for systems that enforce guardrails by design, tools that understand organisational context, restrict unsafe actions, and require human approval when decisions carry risk. Emerging standards like ISO 42001 are formalising these expectations and pushing companies toward safer, governed forms of AI.

The Shift Toward Live, Always-On Compliance

Compliance is also being reshaped by constant regulatory expansion. Companies rely on systems that can track new obligations, interpret relevance, and map requirements onto their existing controls. Sprinto’s Infinite Frameworks engine performs this interpretation so that teams can focus on reviewing output rather than decoding regulatory language manually.

Sprinto works largely with SMBs and mid-market companies across SaaS, healthtech, fintech, and other cloud-first sectors, many of which operate in multiple jurisdictions with overlapping compliance obligations. The platform is used by more than 3,000 customers in over 75 countries, giving the company visibility into how organisations adapt their controls as regulatory expectations evolve. This broader footprint informs how Sprinto approaches continuous compliance, particularly in environments where frameworks shift frequently and must be interpreted without rebuilding processes from the ground up.