India Series A Weekly Funding Roundup (Mar 24-31, 2026): $37.0M Raised Across 2 Deals

Table of Contents

Two India-based startups raised a combined $37M in Series A rounds during the week of March 24–31, 2026. The deals spanned AI model training infrastructure and construction equipment rental , different industries, but both built around India's structural advantages: deep technical talent and a rapidly growing physical infrastructure market.

The week's larger deal, Deccan AI's $25M raise, signals something specific: frontier AI labs are no longer the only buyers of expert-level AI training services. Enterprises are now spending on fine-tuning and evaluation too, and Deccan's India-centric model is positioned to serve both. MTandT Rentals' INR 100 crore close from ValueQuest rounds out the week, targeting the fragmented equipment ownership problem across India's construction and infrastructure sectors.

1. Deccan AI Raises $25M To Scale Expert AI Post-Training From India

Deal Overview

• Stage: Series A (first institutional round)
• Sector: AI infrastructure / post-training services
• Geography: San Francisco HQ, Hyderabad operations
• Round size: $25M
• Lead investor: A91 Partners, with Susquehanna International Group (SIG) and Prosus Ventures participating

Investor Profile

A91 Partners is a Bengaluru-based growth-stage fund known for backing Indian companies with global ambitions. SIG is a quantitative trading and investment firm with a long history of early bets on data-intensive businesses. Prosus Ventures, the VC arm of the Dutch-listed Prosus group, has backed some of India's most prominent tech companies. The combination of an India-focused lead with global financial and tech investors reflects Deccan's dual positioning: India-rooted, globally oriented.

Company and Leadership

Deccan AI was founded in October 2024 by Rukesh Reddy. In its first year, the company grew 10x, reaching double-digit million-dollar ARR with around 125 employees. Customers include Google DeepMind and Snowflake. The pace , from founding to a $25M Series A in roughly 18 months , is unusual even by AI startup standards.

Problem and Opportunity

Training a frontier AI model requires more than raw compute. It needs human feedback ,, expert evaluation of model outputs across complex reasoning tasks: code, math, formal logic. General-purpose crowd annotation platforms handle basic labeling, but they fall short when tasks require PhD-level domain knowledge. That gap is what Deccan fills.

As AI labs push models into harder reasoning domains, demand for expert evaluators grows. Enterprises fine-tuning models for internal use face the same problem at smaller scale. Deccan's timing tracks directly with this shift in the market.

Product and Technology

Deccan provides RLHF, expert evaluation, fine-tuning, and advanced data generation for AI labs and enterprise LLMs. The company runs a contributor network of over 1 million members, with 5,000–10,000 active monthly contributors , mostly India-based IIT and IISc graduates and PhD researchers. This isn't commodity annotation. The work requires people who can spot subtle reasoning errors in graduate-level mathematics or evaluate multi-step code generation.

The platform was purpose-built for agentic workflows and multi-model evaluation, not adapted from a legacy labeling tool. That architectural decision matters as AI systems grow more complex and evaluation requirements shift from single-turn outputs to multi-step agent behaviors.

Use of Proceeds and Vision

Capital goes toward expanding enterprise AI offerings, growing the Hyderabad operations hub, and building out platform capabilities for deploying and evaluating AI systems. Deccan is also moving beyond frontier AI labs into broader enterprise customers , a market where the competition is less concentrated and sales cycles differ significantly.

Market Context

The global AI training data market is projected to reach $6.1B by 2028. Deccan competes with Mercor, Scale AI's Outlier platform, Turing, and Surge AI. Where most of those players compete on breadth and volume, Deccan competes on depth and quality. The India-centric expert talent model gives it a structural cost advantage that's difficult to replicate in Western markets, where comparable researchers command multiples of the cost.

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2. MTandT Rentals Secures INR 100 Crore To Expand Equipment Rental Platform

Deal Overview

• Stage: Series A
• Sector: Equipment rental / construction tech
• Geography: India
• Round size: INR 100 crore (~$12M)
• Lead investor: ValueQuest S.C.A.L.E Fund II

Investor Profile

ValueQuest is an India-focused investment firm running the S.C.A.L.E Fund II, which targets high-growth small and mid-cap businesses. The fund's thesis centers on companies building scalable, asset-light models in traditionally fragmented Indian industries. MTandT fits that thesis , equipment rental aggregation in construction is a category with a large market and thin existing digital infrastructure.

Company and Leadership

MTandT Rentals operates a tech-enabled equipment rental marketplace for India's construction and infrastructure sectors. The platform connects equipment owners with contractors needing short-term access to machinery , excavators, cranes, compactors, and similar capital equipment. Specific founding team and leadership details weren't disclosed publicly at the time of the raise.

Problem and Opportunity

Construction equipment in India is highly fragmented. Most equipment sits on the books of small contractors or individual owners who use it sporadically. When a project needs a specific machine, procurement is largely informal , phone calls and referrals rather than a marketplace. This creates underutilization on the supply side and availability uncertainty on the demand side. A rental platform with real-time inventory visibility addresses both.

India's infrastructure push , national highways, metro rail, large housing programs , creates a sustained demand backdrop. Equipment rental is a natural fit for project-based work where purchasing and maintaining depreciating assets doesn't make economic sense for most contractors.

Product and Technology

MTandT's platform digitizes the equipment rental process: listing, discovery, booking, and payment. The tech layer adds what informal markets can't offer , verified equipment condition, standardized pricing, and utilization tracking. As the marketplace scales, data on availability, pricing, and demand patterns becomes a competitive asset for pricing optimization and supply planning.

Use of Proceeds and Vision

The INR 100 crore raise will fund expansion of the tech platform and growth of the rental marketplace across construction and infrastructure segments. The company is building toward broader coverage of equipment categories and geographies within India.

Market Context

India's construction equipment market runs into the billions of dollars and grows with ongoing infrastructure investment. Equipment rental as a share of total equipment use remains low compared to mature markets like the US and Europe, where rental penetration exceeds 50%. That gap is the opportunity. Competitors include regional rental companies and informal aggregators, but a tech-enabled national platform with standardized quality and availability holds a real structural advantage at scale.

Lessons For Founders

• Structural advantages compound. Deccan AI's access to India's elite technical talent isn't just a cost story , it's a quality story. IIT-level evaluators handle tasks that commodity annotation platforms can't. Build around what your geography does best, not just what's cheapest.
• Revenue before institutional capital changes the raise. Deccan reached double-digit ARR before taking any VC money. That capital efficiency changed the terms of their Series A and the caliber of investors who engaged. Saying no to early dilutive capital is a negotiating strategy, not just a survival tactic.
• Born-for-the-problem architecture matters. Deccan's platform was designed for agentic, multi-model evaluation from day one , not retrofitted from legacy labeling tools. As requirements evolve, retrofitted systems create technical debt. New entrants should build for where the market is going, not where it started.
• Fragmented physical markets still produce strong investment cases. MTandT's raise is a reminder that not every fundable problem is digital-native. Construction equipment rental in India has real inefficiencies a marketplace can solve. The pattern , fragmented supply, unmet demand, informal coordination , still works across many traditional industries.
• Tier-1 customer logos at Series A carry real weight. Google DeepMind and Snowflake as Deccan customers told investors something revenue numbers alone can't: the quality bar is being met at the frontier. An early reference customer in a hard-to-impress category is validation that's difficult to replicate on a slide deck.