Event Participants
Executives
1 Bhaveshkumar Dhirajlal Gadhethriya, Managing Director
Analysts
4 Kapil Adwani (AARTH Growth Fund), Piyush Nandilal, Prashant, Pravesh Saxena
Financials & KPIs
| Metric | Reported | Commentary |
|---|---|---|
| Revenue | ₹6.89 crores (689 lakhs) | >100% YoY growth vs Q1 FY26; QoQ declined ~20-25% due to seasonal Q1 weakness (consistent with last 3 years trend) |
| EBITDA | ₹3.44 crores (344 lakhs) | 115% YoY growth; margin ~50% (MD confirmed target range of 42-46%) |
| PAT | ₹2.01 crores (201 lakhs) | 93% YoY growth |
| Order Book | ₹75 crores (as of May 30, 2026) | Includes new orders + long-term government contracts (ARR); covers next 2 years |
| Intangible Assets | ₹10 crores | Includes Zero Touch hardware+software and AI engines under development; expected to increase 10-20% further |
| Revenue Split | Education 60% / Manufacturing 40% | Education includes ERP + online examination vertical |
Geographic & Segment Commentary
Education ERP (60% of revenue): Core vertical serving Indian schools, colleges, universities, and state higher education departments. Achieved highest-ever admission record in Madhya Pradesh with 117 million views on admission portals and 2.8 million unique users. Secured India's first AI-based project in higher education with ₹11 crore order, delivery commenced in Q1.
Manufacturing ERP (40% of revenue): Second major revenue contributor focused on finance, sales, production, and inventory management challenges. Company building AI models for manufacturing sector with use case presented in business presentation.
Online Examination: Third business line classified under education vertical; combined with education ERP for the 60% education share. Zero Touch machine targets this segment, focusing on mass, high-risk competitive/institute government exams.
Company-Specific & Strategic Commentary
Zero Touch Machine Launch: India's first patented question paper security solution; 20-year Indian patent received this quarter. First machine launched May 16, 2026 in Jaipur. 150 machines developed with pilots completed covering question paper generation to delivery.
AI-Led Growth Engine: Building complete AI ecosystem for education (students, professors, management) and manufacturing. Using proprietary open-source LLaMA LLM with in-house algorithms - no third-party APIs. Beta launch targeted for Q3 FY27 with revenue commencing by March 31, 2027.
Strategic Acquisitions: Planning disciplined acquisitions across 5 focus areas - technology, education, fintech, AI, and data center - aligned with Infinity vision, culture, and long-term strategy.
Expansion and Team Growth: Expanded marketing/sales teams to Chandigarh (Punjab & Haryana), Odisha, Patna (Bihar), Jaipur, Pune, Mumbai, Indore, Bhopal, and Gujarat (Rajkot). HQ remains in Gujarat.
Guidance & Outlook
| Metric | Guidance / Outlook | Commentary |
|---|---|---|
| Zero Touch Revenue Contribution | 20-22% of total revenue within 2 years | Achieving target in 2 years with strong potential this year and next financial year |
| Zero Touch Orders (FY27) | ₹5-6 crores minimum | Based on current pilot orders and expected tender confirmations; currently only pilot orders with commercial tender bids in process |
| EBITDA Margin | 42-46% | Historical range maintained over last 3 years; adding only products with higher margins contributing to bottom line |
| AI LLM Launch Timeline | Beta in Q3 FY27, revenue by March 31, 2027 | Free tier initially with per-user/per-query pricing model after adoption |
| Employee Costs | Continue at elevated level | One-time expansion phase; will increase further only if additional sales team expansion needed |
Risks & Constraints
| Risk | Context |
|---|---|
| Government Order Dependency | Zero Touch currently has only pilot orders; commercial revenue depends on government/university tenders converting. 100% government focus is a concentration risk but MD confirmed tender bids in process |
| High Intangible Capitalization | ₹10 crores capitalized intangibles with 10-20% expected growth; AI investments may create amortization pressure if revenue enefits delay |
| Q1 Seasonality | Revenue down ~20-25% QoQ due to seasonal pattern; Q1 traditionally weakest quarter across last 3 years |
| AI LLM Competitive Pressure | Open-source LLaMA based model faces established AI players; management targeting value-added adoption first before monetization |
Q&A Highlights
Zero Touch Commercialization
- Question: Timeline for Zero Touch contributing 20-22% of revenue? (Prashant)
- Answer: Target to be achieved within next 2 years; strong potential this FY and next FY (Bhaveshkumar Gadhethriya)
- Question: How many Zero Touch machines developed? (Prashant)
- Answer: 150 machines developed; no additional under development currently; focus on improving accuracy and deployment of existing units (Bhaveshkumar Gadhethriya)
Zero Touch Business Model
- Question: Revenue model for Zero Touch - one-time sale, subscription, or transaction? (Prashant)
- Answer: DaaS model (Device-as-a-Service) - end-to-end service, revenue per question paper printed and delivered at classroom (Bhaveshkumar Gadhethriya)
- Question: Expected EBITDA margin from Zero Touch? (Prashant)
- Answer: 55-60% EBITDA margin expected from Zero Touch because patented, unique product (Bhaveshkumar Gadhethriya)
Segment-Wise Revenue Mix
- Question: Revenue breakdown across business segments? (Pravesh Saxena)
- Answer: 60% education (including ERP + online examination), 40% manufacturing; compared to last quarter declined ~20-25% due to Q1 seasonal weakness (Bhaveshkumar Gadhethriya)
AI Technology Stack
- Question: What AI models or RAG used in Zero Touch? (Pravesh Saxena)
- Answer: Combination of AI + mechatronics + robotics; uses proprietary open-source LLaMA LLM with custom algorithm layers; no third-party APIs (Bhaveshkumar Gadhethriya)
Order Book
- Question: What is the current order book position? (Kapil Advani, Pravesh Saxena)
- Answer: ₹75 crore order book as of May 30, 2026 covering next 2 years - includes new orders and long-term government contracts/ARR (Bhaveshkumar Gadhethriya)
Intangible Assets
- Question: Total intangibles and expected peak amount? (Kapil Advani)
- Answer: ₹10 crores currently including Zero Touch hardware/software and AI engines; expected 10-20% increase; no defined peak as AI investments are ongoing (Bhaveshkumar Gadhethriya)
Cost Base & Margins
- Question: Is employee cost increase a one-time or ongoing? (Prashant)
- Answer: Elevated cost will continue at similar range; may increase further if additional sales team expansion needed (Bhaveshkumar Gadhethriya)
- Question: Expected EBITDA margin target? (Prashant)
- Answer: Target 42-46% range, consistent with last 3 years performance; adding products with higher margins only (Bhaveshkumar Gadhethriya)
AI LLM Roadmap
- Question: Timeline and revenue model for AI LLM? (Kapil Advani)
- Answer: Beta launch Q3 FY27, revenue by March 31, 2027; initially free tier with per-user/per-query plans post-adoption; 15-20% additional capitalization expected for training (Bhaveshkumar Gadhethriya)
Key Takeaway
Infinity Infoway delivered another strong quarter with Q1 FY27 revenue of ₹6.89 crores (>100% YoY growth), EBITDA of ₹3.44 crores (115% YoY growth), and PAT of ₹2.01 crores (93% YoY growth), though Q1 seasonality drove ~20-25% QoQ decline. The company achieved major operational milestones including India's first AI-based higher education project (₹11 crore order), highest MP admission portal traffic (117 million views, 2.8 million unique users), and patent approval for Zero Touch machine with 150 units developed. Strategic priorities include Zero Touch commercialization targeting 20-22% revenue contribution within 2 years with 55-60% EBITDA margins, AI LLM beta launch in Q3 FY27 with revenue by March 2027, and disciplined acquisitions in technology/education/fintech/AI/data center. With ₹75 crore order book, management remains confident in sustaining 42-46% EBITDA margins while expanding sales presence across India. Key watch points include conversion of Zero Touch pilot orders to commercial tenders, employee cost trajectory, and higher AI-related intangible capitalization.