Kudra vs TangoEye

Kudra automates the extraction and analysis of data from complex documents, turning raw files into verified, actionable insights with precise visual references. It processes various document types such as financial reports, legal contracts, invoices, resumes, and safety data sheets, supporting over 20 languages.

What distinguishes Kudra is its combination of deterministic workflows and embedded AI agents, which together provide both reliability and flexibility. This hybrid approach ensures high accuracy with provenance tagging, allowing users to trace extracted data back to its exact location in the source document.

Kudra offers customizable workflows and supports custom AI model training to tailor the solution to specific business needs. It integrates with popular platforms like QuickBooks and Google Drive and provides options for on-premise deployment with enterprise-grade encryption, making it suitable for regulated industries.

The platform serves multiple sectors including finance, legal, logistics, insurance, human resources, and commercial real estate. Its architecture delivers data with bounding box locations and confidence scores, ensuring auditability and trust in automated document processing.

TangoEye is in-store retail analytics and automation software that turns existing CCTV cameras into footfall, zone, and conversion data. Instead of manual clickers or new sensor hardware, it plugs into the camera network retailers already run. The platform splits into four modules: Tango Traffic for walk-in counts, Tango Zone for shelf and area heatmaps, Tango RevOp for missed-sale tracking, and Tango StoreOps for camera and network uptime.

Most retail analytics vendors sell dedicated counting sensors or gate hardware. TangoEye's pitch is pure software on top of cameras that are already mounted, which keeps rollout cost lower and avoids ripping out existing infra. That trade-off means you need working CCTV coverage and bandwidth at each store, but you skip the cap-ex cycle of installing parallel sensor networks.

Retail operations teams use it to see bounced visitors, engaged shoppers versus casual walk-ins, and zone-level dwell time without standing at the door with a tally counter. Brand leaders at multi-store chains like Lenskart and Nykaa, listed on TangoEye's site, get a shared view of conversion leaks and infrastructure blind spots across locations. Store managers get hourly alerts when cameras or networks drop so footfall data does not silently go missing.