Top Tech Startups in India in 2026

21K creates a learning environment that helps develop intellectually-curious, independent-minded young adults who can relate knowledge to life, beyond school. There is a clear shift from rote-learning to an enriching curriculum that goes beyond textbooks. Even the assessment system ensures that the child isn’t burdened with unhealthy expectations but instead enjoys the journey of learning.

Quash is an Agentic tool that automates QA for mobile apps. It identifies, reports, and resolves bugs, reducing manual QA efforts. Devs focus on building while Quash accelerates bug fixes, delivering faster, reliable apps.

Omnifi is an outsourced finance operations company building the AI layer on top of the work we already do. Today, we manage finance back-office operations — AP, AR, payroll, GL, month-end close, treasury, and compliance reporting — for mid-market, multi-entity US companies, delivered through a dedicated India-based team, inside the systems clients already use (Bill.com, QuickBooks, Procurify, Paylocity). We're the team doing the work, not a tool nobody adopts. The problem: traditional outsourcing solves cost but not scale — growth means more headcount. Traditional software solves neither — it requires the client's own team to configure and maintain it. Neither delivers finance operations that scale without headcount scaling too. What we're building: an AI-native platform combining our operational work with AI agents that take over its repetitive parts: AI agents for AP processing/matching, AR collections, reconciliation, close, and reporting A web application serving as both a management cockpit and a client engagement layer Data infrastructure to structure and analyze clients' financial data This is built on our existing business, not a replacement — we already have the clients, delivery team, and operational knowledge. We're automating workflows we already run. Where we are: early-stage. No platform in production yet — the operating business exists, and we're now building the technology layer. Foundational work: architecture, first agents, first version of the app. The team: a founder who holds client relationships and built the business, a partner on product/go-to-market, and finance operations leaders in India running delivery. Missing: the engineering capability to build the platform. The role: no mature engineering org or scoped backlog. A working business, a clear problem, no platform yet. You'll help write the spec, not implement someone else's.

Quantyx Global is a medico-legal services company helping law firms across the United States, Canada, and Australia streamline one of the most time-consuming parts of personal injury, workers' compensation, and insurance defense practice: medical record review. Every case built on medical evidence starts with hundreds, sometimes thousands, of pages of clinical records, physician notes, diagnostic reports, and treatment histories. Reviewing and organizing this information manually is slow, expensive, and prone to human error, yet it's foundational to building a strong case. We built Quantyx Global to solve that problem. Our platform combines AI-accelerated processing with physician-reviewed accuracy to deliver medical chronologies, clinical summaries, and demand letter support that law firms can trust and use directly in case preparation. We compress what traditionally takes paralegals days or weeks into a fast, fixed-price, court-ready deliverable, without sacrificing the clinical judgment that only trained medical reviewers can provide. We designed our workflow around the realities of legal practice: fixed, itemized pricing with no hidden ranges, fast turnaround times, and strict compliance with HIPAA and PIPEDA standards for handling sensitive health information. Every file is processed under strict confidentiality protocols, with secure, role-based access controls built into our infrastructure from the ground up. Quantyx Global was founded on a simple belief: legal teams shouldn't have to choose between speed and accuracy when it comes to medical evidence. Attorneys need clarity, not noise, and our job is to give them a clean, defensible timeline of a client's medical history so they can focus on building the strongest possible case.

EazyML, the first machine learning platform to predict outcomes from textual data. And the best part? It's transparent! Easiest-to-use ML platform.