Ha-Blar: to talk: “For millions of years, mankind lived just like the animals. Then something happened which unleashed the power of our imagination. We learned to talk and we learned to listen. Speech has allowed the communication of ideas, enabling human beings to work together to build the impossible. Mankind's greatest achievements have come about by talking, and its greatest failures by not talking. It doesn't have to be like this. Our greatest hopes could become reality in the future. With the technology at our disposal, the possibilities are unbounded. All we need to do is make sure we keep talking.” - Stephen Hawking
At Blar we believe in a future present where AI and humans interact daily. AI is not a transitory technology, it’s not a technology that will arrive in 20 years, it’s a technology that’s already here and it’s here to stay. We are committed to delivering AI agents that behave like one more co-worker inside a company, workers that are aware of the entire context within a business, workers that adapt and learn, workers that will revolutionize how we interact with our code bases and overall technology systems.
At Blar, we exist to create AI co-workers. Today, it’s almost inevitable that AI systems will work alongside humans. While many are addressing key challenges like AI reasoning, memory, and interaction, one crucial aspect is often overlooked: context. As cliché as it sounds, our mantra is: “Context is all you need.”
There’s a reason why an engineer with years of experience at a company can deliver more value than a newcomer, even if that newcomer is exceptionally talented. The veteran possesses something far more valuable than raw intelligence—they have context: an understanding of the business, the systems, the people, and every nuance that defines the organization.
This is precisely the challenge we're tackling. Today, we have an AI genius that has “memorized” the entire internet but lacks insight into your company’s specific needs. This day-one genius has immense potential to deliver value, yet it misses a crucial element of the equation: context.
Our hypothesis is simple: Can we deliver an AI system that understands a codebase as deeply as a senior tech lead would? Can we empower every developer in an organization with a personalized AI engineer—one who not only knows every line of code but also understands the purpose behind it?
Imagine an engineer who’s available 24/7, tirelessly monitoring the codebase, always ready to flag potential issues before they escalate. An engineer who can instantly diagnose problems, optimize performance, and ensure the system remains secure—anticipating issues and providing solutions in real time. This AI co-worker would be a constant vigilant presence, always learning, adapting, and collaborating with the team to ensure the codebase evolves seamlessly and efficiently.