Casper Labs

CasperLabs, which now also operates under Prove AI, embarked on its journey in 2018, co-founded by Mrinal Manohar, Medha Parlikar, and Steve Careaga. What began as a vision to address the limitations of existing blockchain technology quickly evolved into a mission to build a platform truly ready for enterprise and developer adoption. Mrinal Manohar, with a background spanning computer science and Wall Street, along with Medha Parlikar, a seasoned software engineering leader, identified critical gaps in the blockchain landscape that hindered widespread business integration. They envisioned a future where blockchain could seamlessly integrate into existing IT architectures, offering scalability, security, and developer-friendliness – attributes often found lacking in earlier iterations of the technology.

The early days were focused on intensive research and development, culminating in the creation of the Casper Network, a layer-1 proof-of-stake blockchain. This wasn't just another blockchain; it was meticulously engineered from the ground up, with every line of code designed to meet the rigorous demands of enterprise use cases. Key innovations included features like upgradeable smart contracts, predictable network fees, on-chain governance, and flexible permissions – all tailored to empower businesses and developers. The company facilitated the Casper Testnet throughout 2020, a crucial phase that allowed for rigorous testing and community feedback. The mainnet officially launched in March 2021, marking a significant milestone in CasperLabs' evolution. Since then, CasperLabs has transitioned from primarily a development-focused entity to a comprehensive software and professional services company. They actively work with enterprises across various sectors, including IPwe for patent management and Metacask for modernizing the whisky market, providing end-to-end solutions and support for building on the Casper Network. The journey continues with a strong emphasis on AI governance, highlighted by collaborations with industry giants like IBM to enhance transparency and auditability in AI systems.