We're building the human and physical infrastructure behind the world's AI.
Whether it's high-quality training data, managed workforce operations, or physical AI — we focus on building the infrastructure that lets AI companies scale with confidence.
Key Advantages
“We didn't set out to build a data company or a robotics company — we set out to build the human layer every AI system eventually needs. Everything else follows from that.”
Founder & Director, Dream Jobs Hub LLP
Egocentric capture of wire identification, routing, and termination inside a junction box — precise hand-eye coordination in a confined workspace.
Includes
Mark Head Prototype
Showcasing Mark's visual perception and robotic design, this feature highlights our humanoid sensor array, camera stack, and head-control systems that power safe physical AI interaction.
Our Journey
23rd February 2023
Established with a mission to modernize enterprise talent acquisition through intelligent data.
3rd October 2025
Launched proprietary AI matching engine, reducing average time-to-hire by 55%.
6th January 2026
Expanded operations to 12 cities with 5,000+ enterprise clients across technology, finance, and manufacturing.
28th February 2026
Extended services to Southeast Asia and the Middle East with region-specific talent intelligence.
16th May 2026
Introduced comprehensive workforce analytics and predictive retention tools for enterprise HR teams.
28th June 2026
Released DHUB v4 — a fully integrated talent operating system trusted by 650+ enterprise clients globally.
Dream Jobs Hub LLP (DHUB) is an AI enterprise headquartered in Vizianagaram, Andhra Pradesh, combining a large-scale human workforce network, a proprietary AI model, and physical AI/robotics (Mark) into one integrated company.
Powering global AI development through high-quality data, managed operations, and next-generation robotics — while building toward Mark and DHUB's own AI model.
We'll push back on a deadline before we push out bad data.
Our workforce systems are designed for 10x volume, not just today's.
AI needs a human layer underneath it. That layer is our whole business.
Roadmaps, milestones, limitations — we'd rather be accurate than impressive.
