Estate Ease
Agentic AI for Real Estate
Replace agents with AI that thinks, negotiates, and closes.
Smarter decisions.
Instant insights.

Zero commission.
Currently we are in product development. Stay tuned!

Trusted Agents

Security and confidentiality are critical for AI agents - they process, store, and act on sensitive data, often making decisions that impact individuals, enterprises, and governments.
NoirAgent Logo — End-to-end content encrypted.
Prompting, embedding, Neural encrypting, communicating, inferring, Neural decrypting. Repeat.
Security Guarantee —AI Providers observe no content - prompts, responses—
  • Regulations Compliance
  • Intellectual Property and Data Security

Power Every Task — with Privacy, Security, and Trust

Lightweight
Optimized resource consumption on mobile devices, personal computers, and enterprise clouds.
Cost Effective
Reduce operation and maintanance cost by 10x with leading-AI and customized models to your needs.
Adaptive
Fine-tuned with RL integrated with RAG to build sustainable, successful AI programs from your data.
AI Use Cases

Built on Breakthrough AI Research

Estate Ease is built on cutting-edge research in AI, security, and privacy. Our team of experts solve challenging problems to protect and unlock your values.

Meet the Team

Team Member
Ninad Dhoble

CEO & Co-Founder

Ninad drives product strategy, commercialization planning, and user adoption efforts. He oversees customer discovery, pricing model development, and manages early adopter engagement with buyers, sellers, and small brokerages. Ninad will also lead all aspects of IP management and downstream go-to-market strategy.
Team Member
Sreedevi Mohan Reddy

CTO and Co-Founder

Sreedevi is the technical founder of Estate Ease. She leads the development of the agentic behavioral reasoning engine, federated learning architecture, and proof-of-concept system. Her responsibilities also include aligning technical milestones with the project plan and managing the collaboration with Univ of Westminster.
Team Member
Dr. Natalia Yerashenia

Research Lead, University of Westminster

Dr. Yerashenia is a tenured professor professor at University of Westminster and an expert in federated AI, spatio-temporal modeling, and privacy-preserving data systems. She will lead the academic research track of the project, including behavioral signal extraction, multi-agent modeling, and federated parameter sharing. She will supervise 1–2 Ph.D. students whose work will directly contribute to the technical core of the project.

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