RNIT AI Solutions Secures Paid Pilot Order from Meghalaya Government for AI Face Recognition System Integration

2 min read     Updated on 18 Feb 2026, 09:37 PM
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Reviewed by
Radhika SScanX News Team
Overview

RNIT AI Solutions Limited has received a paid pilot work order from the Government of Meghalaya for integrating its AI face recognition system with Meghalaya ONE and CM Connect applications. The order, received on 17th February 2026, marks the company's entry into Meghalaya and expansion into the North East region. Operating under a Tier-1 structure with 15-day execution timeline, the pilot project offers potential for state-wide rollout upon successful proof of concept completion.

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*this image is generated using AI for illustrative purposes only.

RNIT AI Solutions Limited has secured a significant paid pilot work order from the Government of Meghalaya for integrating its AI face recognition system with state government applications. The order, received on 17th February 2026, represents the company's strategic entry into the North East region and strengthens its presence in delivering AI-driven citizen centric services for government platforms.

Order Details and Scope

The work order has been awarded by the Planning Investment Promotion and Sustainable Department, Government of Meghalaya, for the Integration of RNIT AI Solution – Face Recognition System with Meghalaya ONE and CM Connect applications. This engagement operates under a paid pilot model with defined scope and volume, designed as a proof-of-concept framework.

Parameter: Details
Awarding Entity: Planning Investment Promotion and Sustainable Department, Government of Meghalaya
Project Type: Paid pilot Work Order for AI Face Recognition System integration
Target Applications: Meghalaya ONE and CM Connect
Order Classification: Tier-1 (Upto Rs.1 Cr)
Execution Timeline: 15 days from receipt date
Order Receipt Date: 17th February 2026

Strategic Significance

This work order marks RNIT's entry into a new State and forms part of its focused expansion into the North East Region, strengthening the company's footprint in delivering AI-driven citizen centric services for government platforms. The assignment has been structured under a pilot to rollout framework, where successful completion of the proof of concept could lead to further deployment across the state.

Project Structure and Future Potential

The work order operates under RNIT's tiered project classification system, falling within Tier-1 category. The company's project classification includes:

  • Tier-1 Orders: Upto Rs.1 Cr
  • Tier-2 Orders: Rs. 1 Cr to Rs. 10 Cr
  • Tier-3 Orders: Rs. 10 Cr to Rs. 50 Cr
  • Tier-4 Orders: Above Rs. 50 Cr

The work order provides for transition from the pilot to rollout across the State, subject to successful completion of the proof of concept and in accordance with the terms and conditions specified therein. This structure offers potential for scaling the engagement based on performance and government requirements.

Regulatory Compliance

RNIT AI Solutions Limited has disclosed this development in compliance with Regulation 30 of the SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015. The company confirmed that the promoter, promoter group, and group companies have no interest in the awarding entity, and the order does not constitute a related party transaction.

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RNIT AI Solutions Limited Reports No Deviation in Fund Utilization for Q3 FY26

1 min read     Updated on 13 Feb 2026, 11:54 PM
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Reviewed by
Ashish TScanX News Team
Overview

RNIT AI Solutions Limited has filed its Q3 FY26 compliance report confirming no deviation in utilization of Rs. 20.83 crores raised through preferential issue on November 5, 2025. The company has utilized Rs. 10.53 crores for business expansion and working capital purposes, with Rs. 10.30 crores remaining unutilized. The Audit Committee confirmed no deviation in fund utilization.

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*this image is generated using AI for illustrative purposes only.

RNIT AI Solutions Limited has submitted its quarterly compliance report to BSE Limited, confirming no deviation in the utilization of funds raised through preferential issue for the quarter ended December 31, 2025. The statement was filed in accordance with Regulation 32 of SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015.

Fund Raising Details

The company successfully raised funds through preferential issue of equity shares allotted to persons belonging to public category. The fund raising exercise was completed on November 5, 2025, generating total proceeds of Rs. 20,82,72,372, rounded off to Rs. 20.83 crores.

Parameter: Details
Mode of Fund Raising: Preferential Issue of Equity Shares (Public Category)
Date of Fund Raising: November 5, 2025
Total Amount Raised: Rs. 20,82,72,372 (Rs. 20.83 crores)
Reporting Quarter: December 31, 2025

Fund Utilization Status

The funds were allocated for business expansion including working capital and general corporate purposes. The company has maintained adherence to its original allocation plan without any modifications to the stated objects.

Metric: Amount (Rs. in Crores)
Original Allocation: 20.83
Funds Utilized: 10.53
Unutilized Amount: 10.30
Deviation/Variation: NIL

Compliance and Oversight

The company confirmed that no monitoring agency oversight was applicable for this fund raising exercise. The Audit Committee has reviewed the fund utilization and noted that there is no deviation or variation in the utilization of funds raised. The statement indicates no changes in terms of contract or objects that would require shareholder approval.

Company Background

RNIT AI Solutions Limited, formerly known as Autopal Industries Limited, operates with its registered office in Jaipur, Rajasthan, and corporate office in Hyderabad. The company is incorporated under CIN: L62090RJ1985PLC003427 and maintains its compliance obligations through Company Secretary T.T.V.R. Seshan.

The quarterly filing demonstrates the company's commitment to regulatory compliance and transparent reporting of fund utilization to stakeholders and regulatory authorities.

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