The next frontier in agentic AI requires systems that reason about their own correctness, learn from failure, and scale under formal guarantees.
Large Language Models removed constraints in content generation, workflow planning, and decision making.
Mission-critical systems demand reliability, long-horizon stability, and provable correctness.
Our Thesis: Solve scalable correctness, unlock scalable autonomy. When systems verify their own behavior, intelligence scales safely.
Enterprises are racing to deploy autonomous agents in high-stakes environments—finance, healthcare, manufacturing—without verification infrastructure. Early failures will set the entire field back.
Proof assistants like Lean have reached production maturity. LLMs can now translate natural language to formal specifications. The convergence of AI and formal methods is happening now.
With world-class talent in mathematics, logic, and software engineering, India is uniquely positioned to lead in verified AI—before the paradigm solidifies elsewhere.
The next 2-3 years will determine whether autonomous AI becomes trustworthy infrastructure or triggers an agent winter. We're building the foundations now.
Emergence Autonomous Systems Lab advances self-improving AI by making verification a foundational principle.
We build provably reliable systems that accelerate discovery and engineering, unlocking material advances for humanity. Our goal: make verification-native autonomy the default paradigm, so reliability scales with capability and trustworthy AI becomes infrastructure rather than exception.
5-Year Milestones: Establish India as a global hub for verified autonomy research. Deploy verification-first systems in semiconductors and enterprise data pipelines. Train 1,000+ practitioners in formal methods and agentic AI. Publish breakthrough research bridging Lean proof systems with autonomous agents.
Shift humans from operators to architects of self-sustaining systems
Enable science and engineering to advance predictably, not drift
Expand autonomy without sacrificing reliability
Scalable autonomous AI demands both collaborative agent-level checks and mathematical guarantees. We bridge these paradigms:
Agents verify the work of other agents over long horizons—collaborative correctness checks at the system level.
Mathematical proofs using tools like Lean ensure provable correctness with machine-checkable guarantees.
Emergence AI
Leading the lab's research agenda in verification-native autonomous systems, bridging cutting-edge AI research with formal verification methods for mission-critical applications.
Indian Institute of Science (IISc)
Renowned mathematician and pioneer in automated theorem proving and formal verification. Leading research in applying proof assistants to AI systems.
Our research advances the science of verified autonomous systems through rigorous publications, open-source tools, and collaboration with the global research community.
Peer-reviewed papers on verification-first agent architectures, formal methods for AI safety, and Lean-based system verification
Coming Soon →Deep dives into our research, tutorials on formal verification with Lean, and insights from deploying verified systems
Coming Soon →Tools and libraries for building verification-native agents, bridging LLMs with proof assistants
Coming Soon →Agent architectures where planning, memory, and learning are guided by correctness constraints.
Systems that transform real-world specifications into structured domain knowledge suitable for machine-checkable verification.
Advancing the use of proof assistants—especially Lean—to verify data pipelines, workflows, and agent behavior.
Initial focus on semiconductors and complex data transformation pipelines, with tools designed to generalize across industries.
Open-source tools and applied systems that advance the global state of the art and help companies deploy autonomous AI safely at scale.
Based in India, the lab bridges research, industry, and public institutions—converting frontier ideas in agentic AI and formal verification into deployable systems, open tools, and trained talent.
Advancing verified autonomy as a science
Deploying systems in semiconductors and enterprise
Partnering with institutions for national-scale impact
Practical workshops on proof assistants and formal verification techniques
Collaborative sessions exploring frontier problems in verified autonomy
Building real-world autonomous systems with verification constraints
Long-term partnerships with Indian universities and research centers
We're looking for researchers, engineers, and partners who share our vision of verification-native autonomous systems.