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Proptech startup Inkers Technology raised $3 M Series A funding

Ashish Kasholia of Lucky Investments is leading the $3 million Series A funding round for prop-tech startup Inkers Technology.

Sailing Stones Technologies and other investors had previously contributed $2.03 million to the Bengaluru-based company.

According to a press release from Inkers, the money raised will be used to broaden its customer base and improve its range of products.

Manish Giri, Srikanth Kandada, and Rohan Shravan co-founded Inkers with the goal of advancing the digital transformation of the construction sector by resolving important issues and facilitating long-term expansion for infrastructure projects in India and abroad. In order to optimize the incoming data, the company uses a comprehensive and integrated video processing pipeline that makes use of computer vision, deep neural networks, hardware-level acceleration, and special frequency domain encoders.

Inkers claims that Observance, its flagship product, is an AI-powered platform made to process and turn complex construction data—including point cloud data, photos, BIM models, and project schedules—into useful insights. Construction teams can proactively detect possible problems, optimize workflows, and save a substantial amount of time and money by enabling quick and accurate conversion into Building Information Modeling (BIM).

Real-time construction updates, early structural defect detection, and quicker BIM conflict resolution are made possible by Observance’s hyper-accurate as-built 3D models enhanced with thermal maps. Within 24 to 48 hours, the platform can produce detailed analytics, as-built models, defect reports, and schedule updates after scanning an area up to 100,000 square feet in an hour.

According to Inkers, its product has already been implemented at more than 150 locations in Bangalore, Hyderabad, Chennai, Kolkata, and the National Capital Region. It has scanned more than 250 million square feet of construction site and processed more than 2 petabytes of data.

 

 

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