RNIT AI Solutions: FY26 closes with sharp growth and new state wins

RNIT AI Solutions Limited, formerly Autopal Industries Limited, ended FY 2025-26 with a strong financial performance and a wider footprint across public-sector deployments. For the year ended 31 March 2026, the company reported revenue from operations of ₹5,149.88 lakhs, up 59.8% year on year. Profitability expanded even faster. EBITDA rose to ₹2,146.13 lakhs, with EBITDA margin improving to 41.7%. PAT came in at ₹1,201.73 lakhs, translating to a PAT margin of 23.3%.

The quarter also showed sequential momentum. In Q4 FY26, revenue was ₹1,761.57 lakhs, up 26.6% compared with Q3 FY26. EBITDA in Q4 stood at ₹771.74 lakhs, while PAT was ₹434.57 lakhs. The presentation frames this as evidence of operating leverage, with PBT margin rising to 36.6% in Q4 from 34.5% in Q3.

What RNIT sells and where it deploys

RNIT positions itself as an AI-led e-Governance and enterprise technology provider, built around identity, accountability and real-time decision dashboards. Its core stack, as described in the presentation, includes AI-based facial recognition systems across mobile, device-based, browser-based and CCTV-based identification. These solutions are presented as identity and authentication layers for use cases such as workforce attendance, beneficiary verification, and institutional compliance.

Beyond identity, RNIT highlights AI-driven e-Governance platforms as “single-source-of-truth” systems that bring last-mile activity into dashboards for decision makers. The portfolio also includes IoT plus AI transformation platforms for integrating smart and non-smart devices, and a conversational and generative AI offering branded as NIA, aimed at multilingual interview simulations, personalised feedback and skill-gap analysis.

Geographically, RNIT claims a pan-India presence and explicitly lists deployments across Andhra Pradesh, Assam, Bihar, Goa, Lakshadweep, Meghalaya, Odisha, Telangana, and Uttar Pradesh. On the domain side, it references work across school education, higher education, tribal welfare, social welfare, skill development, legal metrology, municipal administration, and panchayats.

Financial performance in context

The FY26 results indicate meaningful margin expansion versus FY25. EBITDA margin increased to 41.7% from 31.9%, while PBT margin increased to 32.3% from 22.7%. PAT margin improved modestly to 23.3% from 22.4%.

For Q4 versus Q3, EBITDA margin improved slightly to 43.8% from 43.3%, while PAT margin softened to 24.7% from 25.8%. The presentation also highlights that OE as a percentage of revenue moved higher in Q4 compared with Q3.

Order momentum and the operating playbook

RNIT’s order book section is focused on public-sector wins and rollouts across education, skilling and local governance. In existing regions, it lists work with the State Board of Technical Education and Training in Andhra Pradesh for online application monitoring, Telangana Social Welfare Residential Educational Institutions Society for AI-based identification, and multiple work orders in Telangana via Telangana Technology Services and the Higher Education Department for FRS attendance across institutions.

In Andhra Pradesh, the company also cites wins in skilling, including an AI-based multilingual interview and conversational job-preparation platform, with additional scope for a broader skill and employment enhancement platform. In higher education, it references a notification of award and an SLA for AI-based mobile FRS attendance.

A notable strategic theme is entry into new regions. The presentation lists Goa Electronics Limited and the Directorate of Panchayats in Goa for an AI-based FRS ERP suite rollout for panchayat staff. It also cites a paid pilot in Meghalaya to integrate RNIT’s FRS with Meghalaya ONE and CM Connect applications, and a rollout in Lakshadweep for AI-based FRS attendance for the Department of Education.

RNIT’s business model positioning aligns with these contract types. The presentation describes SaaS and transaction-led pricing as pay-per-usage with one-time deployment plus recurring revenue, alongside O&M managed services, long-term government contracts, enterprise subscriptions and a pilot-to-scale approach with elastic pricing based on user volumes.

Management commentary and signals investors will track

The Managing Director’s message highlights three areas. First, continued strengthening of the NIA AI companion solution along with existing facial recognition and IoT-based digital applications. Second, strategic entry into new regions through wins in Goa, Lakshadweep and Meghalaya. Third, a successful preferential equity allotment that management says strengthened the capital base and enables faster growth, innovation investment and scaling.

Management also states that an NCLT-related resolution application process has been fulfilled and completed, though no details are provided in the presentation. Investors typically watch such statements closely, because the nature of the process and any residual obligations can influence risk perception.

The presentation also mentions awards, including a Prime Minister’s Award for Excellence in Public Administration 2024 and a National Award in e-Governance, positioning RNIT as a recognised vendor in public administration technology.

Takeaways from FY26

RNIT’s FY26 investor presentation points to a company benefiting from higher scale and stronger profitability, with revenue up 59.8% and meaningful margin expansion at the EBITDA and PBT levels. The order wins indicate continued concentration in government-led deployments, but also show geographic diversification into new states and territories.

The next phase for RNIT, based on what is disclosed, appears to hinge on sustaining transaction-led usage in live deployments, converting pilots into statewide rollouts, and broadening its portfolio beyond facial recognition into conversational AI and integrated digital ecosystems. For investors, the key will be whether the company can keep scaling while maintaining disclosure quality on revenue mix, customer concentration and contract economics in future communications.