RNIT AI Solutions Raises ₹26.33 Crore Through Strategic Preferential Allotment

2 min read     Updated on 01 Apr 2026, 01:58 AM
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AI Summary

RNIT AI Solutions Limited completed a strategic preferential allotment raising ₹26.33 crore from 18 investors including Alternative Investment Funds and High Net-Worth Individuals. The company allotted 52,66,537 equity shares at ₹50 per share, with Sageone-Flagship Growth OE Fund being the largest investor. The funds will support expansion in AI-led government and enterprise solutions, strengthen technology platforms, and meet working capital requirements.

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RNIT AI Solutions Limited has successfully completed a preferential allotment of equity shares aggregating to ₹26.33 crore, demonstrating strong investor confidence despite challenging market conditions. The AI solutions company, formerly known as Autopal Industries Limited, announced the completion of this strategic fundraising initiative through an official press release.

Share Allotment Overview

The Board of Directors approved the allotment of 52,66,537 equity shares with a face value of ₹10 each at a price of ₹50 per share during their meeting held on March 28, 2026. The issue price includes a premium of ₹40 per share, with all allottees belonging to the Public (Non-Promoter) Category.

Parameter: Details
Total Shares Allotted: 52,66,537
Face Value: ₹10 per share
Issue Price: ₹50 per share
Premium: ₹40 per share
Total Amount Raised: ₹26.33 crore
Allottee Category: Public (Non-Promoter)
Number of Investors: 18

Strategic Investor Participation

The preferential issue witnessed strong participation from Alternative Investment Funds (AIFs), strategic investors, and High Net-Worth Individuals (HNIs). Sageone-Flagship Growth OE Fund emerged as the largest new investor, receiving 10,00,000 shares representing 1.18% post-preferential holding. The diverse investor base includes institutional investors, individual investors, and corporate entities.

Major Investor: Shares Allotted Post-Allotment %
Sageone-Flagship Growth OE Fund: 10,00,000 1.18%
Anupama K Katkar: 7,00,000 1.62%
Chhaya S Katkar: 5,00,000 1.38%
Sanjay Katkar: 4,00,000 1.60%
Visionary Vibes Consultancy Pvt Ltd: 4,00,000 0.47%
Sunil Aggarwal: 4,00,000 0.47%

Fund Utilization and Growth Strategy

The capital raised will support RNIT's expansion across AI-led solutions in government and enterprise sectors. The proceeds will be utilized for strengthening proprietary technology platforms and SaaS offerings, enhancing execution capabilities for large-scale projects, business expansion, and meeting working capital requirements.

Commenting on the development, Mr. Raja Srinivas Nandigam, Managing Director, stated, "The successful completion of this preferential issue is a strong endorsement of RNIT's strategic direction and execution capabilities. As demand for AI-led solutions continues to accelerate across both government and enterprise ecosystems, this capital infusion enables us to scale our operations and deepen our technology capabilities."

Regulatory Compliance

The share allotment was conducted pursuant to Regulation 30 of the SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015. The initiative forms part of the Resolution Plan approved by the National Company Law Tribunal (NCLT), Jaipur Bench, through its order dated September 23, 2024. Company Secretary T.T.V.R. Seshan digitally signed the regulatory filing on March 31, 2026, ensuring complete compliance with disclosure requirements.

This successful fundraising positions RNIT AI Solutions Limited for its next phase of expansion in the artificial intelligence solutions sector, with the company focusing on delivering sustainable growth and creating long-term value for all stakeholders.

How will RNIT's expansion strategy compete against established AI solution providers in the government and enterprise sectors?

What specific AI technologies and SaaS platforms is RNIT developing that could differentiate it from competitors?

Will RNIT consider additional fundraising rounds or strategic partnerships to accelerate its growth trajectory?

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RNIT AI Solutions Partners With Telangana Government For Ongoing AI Attendance Systems Contract

2 min read     Updated on 20 Mar 2026, 08:48 AM
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Reviewed by
Radhika SScanX News Team
AI Summary

RNIT AI Solutions has expanded its government e-governance portfolio by securing multiple work orders from Telangana Technology Services Limited for implementing AI-based facial recognition attendance management systems across the state's higher education sector. The comprehensive 3-year contract covers approximately 1 million users across ITI institutions, SBTET institutions, and collegiate education departments, operating on a Software-as-a-Service model with transaction-based pricing.

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RNIT AI Solutions Limited has secured multiple work orders from Telangana Technology Services Limited (TGTS), a Government of Telangana undertaking, for the implementation and maintenance of AI-based Facial Recognition Attendance Management Systems across the state's higher education sector. This development follows the company's recent agreement with Andhra Pradesh's higher education department, demonstrating continued expansion in government-led e-governance initiatives.

Telangana Project Scope and Coverage

The latest work orders encompass three distinct segments of Telangana's higher education ecosystem, covering comprehensive deployment across multiple institutional categories under the Government Higher Education Department.

Project Parameter: Details
Total Users: Approximately 10,00,000 (1 million)
Contract Duration: 3 years (including implementation and maintenance)
Service Model: Software-as-a-Service (SaaS) with transaction-based pricing
Geographic Coverage: State of Telangana
Pricing Structure: Rate contract basis with monthly billing based on usage

Work Order Breakdown

The company has received three separate work orders targeting different segments of Telangana's educational infrastructure:

Work Order: Target Institution Scope
Work Order 1: ITI Institutions AI-based Facial Recognition Attendance Management across state ITIs
Work Order 2: State Board of Technical Education and Training (SBTET) Attendance management system for SBTET institutions
Work Order 3: Collegiate Education Department Facial recognition attendance system for collegiate institutions

Strategic Expansion in Higher Education E-Governance

The Telangana engagement represents RNIT AI Solutions' expansion into another state within the higher education e-governance domain, reinforcing its presence in government-led digital transformation initiatives. The solution operates under a Software-as-a-Service model with transaction-based pricing, where consideration is determined based on attendance authentications processed through the AI-based platform.

Each work order includes standard terms and conditions with invoice-based payments and SLA-linked performance conditions, ensuring comprehensive service delivery across all participating institutions throughout the three-year contract period.

Multi-State Presence in Education Technology

With the Andhra Pradesh agreement covering approximately 3,900 institutions and 1.3 million users, combined with the new Telangana orders serving 1 million users, RNIT AI Solutions has established a significant footprint in South India's higher education digitalization efforts. Both projects utilize the company's AI-driven facial recognition technology for digital attendance authentication and management.

Regulatory Compliance

The work orders have been disclosed pursuant to Regulation 30 of the SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015. The company confirmed that these orders fall within the ordinary course of business and do not involve any related party transactions, with all agreements executed at arm's length with government undertakings.

Will RNIT AI Solutions expand its facial recognition attendance systems to other Indian states beyond Andhra Pradesh and Telangana?

How might the transaction-based SaaS pricing model impact RNIT's revenue predictability compared to traditional fixed-contract arrangements?

Could RNIT leverage its government education sector success to penetrate corporate attendance management markets?

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