When SaaS ventures into the shopfloor

India’s manufacturing sector is emerging as a new frontier for SaaS and AI startups. Beyond just digitising manufacturing workflows, the startups are using AI to connect fragmented systems, automate quality inspection, optimise production and inventory, and support product design and development.

According to Tracxn data, the startups in this segment raised $198.74 million between 2019 and 2026, with funding peaking at $77.8 million across 16 rounds in 2024. So far in 2026, the sector has raised $12.6 million across eight rounds.

“Manufacturing is increasingly becoming software- and AI-driven, with technology improving productivity, quality and costs,” says Abhishek Prasad, Managing Partner of venture capital firm Cornerstone Ventures.

Ravi Bulusu, co-founder and CEO, Enmovil

Enmovil, for instance, operates an AI-native supply-chain platform that connects planning, logistics and execution. CADDIE, its agentic AI layer, continuously monitors these workflows, identifies risks, and recommends or triggers the next best action.

Co-founded in 2015 by former NVIDIA and Oracle executives Ravi Bulusu, Nanda Kishore and Venkat Moganty, the company has raised $6 million in Series A funding.

It works with more than 60 enterprises, including nearly 35 Fortune 100 companies, across the automotive, manufacturing, FMCG, chemicals, logistics and energy sectors.

“Manufacturers struggle because data and decisions are fragmented across ERP, WMS, TMS, spreadsheets, transporters and plant-level systems,” explains Bulusu, CEO of Enmovil. This creates a gap between planning and execution on the ground, he adds.

The company’s current focus is in the areas of inventory intelligence and logistics planning, including demand forecasting, inventory optimisation, capacity and production planning, despatch planning, fleet allocation and freight reconciliation.

“Customers increasingly do not want isolated solutions. They want one intelligence layer that can forecast demand, translate it into inventory and capacity decisions, plan the movement, monitor execution and reconcile the financial outcome,” Bulusu says.

Enmovil follows an enterprise SaaS model, with customers subscribing to its intelligence layer and relevant modules. Pricing can be linked to sites, users, vehicles, shipments, SKUs or transaction volumes, while implementation and integration can attract separate fees.

In the area of quality inspection, SwitchOn, founded in 2017, uses computer vision and AI to automate checks and reduce manufacturing defects. Its product Deep Inspect is deployed directly on manufacturing lines.

Aniruddha Banerjee, co-founder, SwitchOn

Defect rates have reduced from around 3 per cent to less than 0.05 per cent, he says, while line productivity increases by around 5 per cent due to fewer micro line stops.

The company has raised close to $14 million funding till date. Its clients include medium and large enterprises (above ₹500 crore revenue) across India, Europe, the US and Southeast Asia.

On the shopfloor, Jidoka’s turnkey solutions are designed to inspect products as they move through manufacturing lines, as well as guide operators through the assembly processes.

At Britannia, the company says its system inspects around 12,000 biscuits a minute and automatically ejects defective products.

The eight-year-old startup has raised about $2.2 million across three rounds and says it has doubled its revenue each year for the past three years.

It has around 50 customers globally across the automotive, food, consumer goods and beverages segments.

Sekar Udayamurthy, co-founder and CEO, Jidoka

Its business model combines hardware sold as capital expenditure, software subscriptions and implementation services. Overseas it has offices in the US, Europe and Japan, and targets achieving at least 50 per cent of its revenue from international markets over time.

Groyyo, launched in 2021, operates in the apparel and fashion industry by combining a technology platform with a supply chain business. Its customers include large fashion brands and the factories of small and medium enterprises across the country.

Subin Mitra, co-founder and CEO, Groyyo

At the front-end the company runs an AI-led design studio, while at the back-end it operates a system that provides hour-by-hour and SKU-level visibility into factory operations, including cutting, stitching and packing. The company manages the supply chain end-to-end, from curating designs and finding suppliers to logistics and quality management.

The company has raised ₹90 crore in a Series B round and eyes ₹110 crore more over the following quarters. It targets a top line of ₹800-850 crore in FY27, as against around ₹500 crore in FY26, while remaining PAT-positive.

AI has sped up the company’s work with fashion brands, Mitra says. It can today provide a customer a new collection or range every 10 days, compared with 30 earlier.

“The overall supply chain is a lot faster, at least by 20-25 per cent, and we bring a lot more visibility into the supply chain,” Mitra says.

The end of a manufacturing era marked by spreadsheets, manual inspections, phone calls and fragmented systems appears nearer than ever, as startups build domain-specific products to automate workflows.

“Startups are more product-led, specialised, and faster to innovate. They can reimagine workflows rather than simply digitise them,” Prasad of Cornerstone Ventures points out, adding that this is where domain-specific AI products can have an advantage over large IT companies.