Why Technology Readiness Is Becoming a Valuation Issue for India’s IPO-Bound Companies
Arun Meena, Co-Founder & CEO of RHA OneAI, RHA Technologies, explains how technology infrastructure, cybersecurity, data governance, technical debt, AI and automation can impact IPO readiness and valuation.
This article has been contributed by Arun Meena, Co-Founder & CEO, RHA OneAI, RHA Technologies
India’s technology industry is entering a new phase of growth, driven by artificial intelligence, cloud adoption, cybersecurity, automation and digital transformation. India’s enterprise ICT market is projected to grow at a 15.5% CAGR through 2030, according to GlobalData, while the country’s IT-BPM industry is expected to reach around $350 billion by FY2030, growing at a CAGR of about 5.5% from FY2024.
Cybersecurity is also becoming a critical part of this transformation. India’s cybersecurity market is projected to grow at a 14.5% CAGR between 2025 and 2030, reaching $16.86 billion by 2030.
For companies preparing for a pre-IPO round or public listing, a reliable technology foundation can influence everything from financial reporting and cybersecurity to operational scalability and investor confidence.
In this interaction with StartupTalky, Arun Meena, Co-Founder & CEO, RHA OneAI, RHA Technologies, shares his perspective on how technology infrastructure, data governance, cybersecurity, technical debt and AI-driven automation can influence IPO readiness and valuation.
Technology Infrastructure Can Strengthen Pre-IPO Valuation
StartupTalky: How much does the quality of a company’s technology stack actually influence valuation during a pre-IPO round or listing?
Arun Meena: Technology does not decide valuation on its own, but it strongly influences how defensible that valuation is. When a company’s growth, margins and cash flows can be verified through dependable systems, diligence becomes faster and investor confidence improves.
A business preparing for its next stage of growth should be able to scale without depending on manual effort, disconnected spreadsheets or a few key people. That requires a strong data and process foundation, supported by systems that can produce consistent and verifiable operational evidence.
When this foundation is weak, the impact appears through delayed reporting, inconsistent numbers and unclear unit economics. These issues extend diligence and make investors more cautious. Companies that strengthen their technology base early are better placed to present a credible growth story.
Investors Closely Examine Technology During Due Diligence
StartupTalky: What do investors and bankers typically examine during technology due diligence, and where do growing companies most often fall short?
Arun Meena: Technology due diligence goes beyond checking whether a company has an application, cloud setup or engineering team. Investors examine data ownership, system architecture, access controls, security and the repeatability of internal processes.
The most common gaps are organisational rather than technical. Critical knowledge may sit with one person, data may be scattered across tools, documentation may be incomplete, or development and production environments may not be properly separated.
A company at this stage should establish clear data ownership, access governance, documentation and system dependencies. It does not need a large enterprise IT function to achieve this. It needs a structure where every important process has an owner, a source and an audit trail. This is the kind of foundation we help organisations build.
SMEs Need a Reliable Technology and Data Foundation Before Listing
StartupTalky: What minimum technology and data infrastructure should an SME have before listing?
Arun Meena: Before listing, a company should be able to answer five questions quickly. What is happening in the business? Can the numbers be trusted? Who has access to what? What happens if a system fails? How quickly can the organisation detect and respond?
To reach that position, it should have a central system of record, controlled data flows, reconcilable financial and operational data, role based access and tested recovery processes. Spreadsheets can still exist, but they should not be the primary source of truth for critical reporting.
A company should also maintain one governed source for management reporting. Board packs, investor updates and compliance reports should emerge from controlled data rather than multiple versions of the same file. The objective is decision grade reliability, not unnecessary technical complexity. We help companies create this structure in a practical and scalable way.
Strong Reporting Systems Improve Data Integrity and Cyber Readiness
StartupTalky: How should a growing company prepare its systems and processes for reporting timelines, data integrity and cyber incident disclosure?
Arun Meena: Reporting reliability should be part of everyday operations, not a quarterly exercise. A company should embed monthly closes, reconciliations, approvals and audit trails into its workflow well before statutory deadlines become a pressure point.
For data integrity, every material metric should have an owner, a defined calculation, a source system and a review process. Changes to reporting logic or systems should be documented and approved. This becomes especially important when a company is preparing historical financials or explaining variances to investors.
Cyber readiness requires a tested response framework. A company should know who declares an incident, who communicates internally and externally, who handles regulatory and legal questions, and how evidence is preserved. We help organisations build these workflows so that transparency and speed of response do not depend on last minute arrangements.
A Clear Security Posture Builds Investor Confidence
StartupTalky: How should founders present their security posture to public-market investors?
Arun Meena: A company should avoid presenting cybersecurity as an absolute guarantee. Investors value a proportionate, accountable and verifiable security posture.
This requires clear policies, access controls, encryption practices, vendor risk assessment, employee awareness, vulnerability management, logging and incident response. The framework should also match the company’s actual risk profile, particularly when sensitive financial, health or personal data is involved.
A company should also have clarity on the personal data it collects, where it resides, who can access it, how long it is retained and how consent, deletion and breach related obligations are handled. A documented data map and clear accountability are far more convincing to investors than broad reassurance. We help companies establish this level of clarity and control.
Technical Debt Can Become a Valuation and Liquidity Risk
StartupTalky: At what point does technical debt become a liquidity or valuation issue?
Arun Meena: Technical debt is a normal part of growth. It becomes a problem when early shortcuts start affecting revenue, cost to serve, product decisions, security or reporting reliability.
A company should watch for warning signs such as frequent system failures, long release cycles, difficulty onboarding customers, inability to add compliance requirements, dependence on individual engineers and increasing manual work across operations.
Rather than trying to eliminate every legacy issue at once, a company should identify the technical debt that directly affects revenue, compliance, security or scalability and address it in a prioritised sequence. We work with organisations to remove the constraints that could make the next stage of growth expensive, slow or restrictive.
AI and Automation Can Make IPO Readiness Faster and More Cost-Effective
StartupTalky: How are AI and automation changing the cost and speed of becoming IPO-ready for smaller companies?
Arun Meena: Automation can reduce the time and cost of becoming IPO ready, but only when it is built on governed data and clearly defined processes.
A company should use automated workflows to accelerate reconciliation, variance analysis, document review, compliance tracking, management reporting and internal knowledge retrieval. This allows lean finance, legal and operations teams to manage work that earlier required much larger teams.
However, automation cannot compensate for poor data. If the foundation is fragmented or unreliable, it will only produce incorrect results faster. A company should combine clean data, role based access and audit trails with intelligent workflows. This is the model we build for organisations, allowing management to spend less time collecting information and more time validating controls, making decisions and presenting a credible growth story to the market.
Nitin Konde
