Kealu
Kealu is an AI research and product-development company building Vector, an engineering assurance platform that makes agentic AI-generated code trustworthy and auditable. The platform coordinates intent, independent verification, traceable evidence, and human oversight across engineering workflows, with a Chief Agent Engineer coordinating agent swarms and an Engineering Terminal for human supervision. It is currently offered through bounded early-access and enterprise-pilot engagements for consequential software.
- Artificial Intelligence
- Developer Tools
- AI Agents
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Software engineering is shifting from a world where code was expensive to produce to one where code is expensive to trust and accept. As AI agents generate more code autonomously, organizations lack a reliable basis for verifying that the work is correct, safe, and aligned with intent, especially for consequential systems where failure can affect safety, security, health, or material financial outcomes.
Solution
Kealu provides the Agentic Engineering Assurance Layer, a platform called Vector that governs how agentic engineering work is performed and evidenced so humans can trust and accept the resulting work. Vector connects intent, independent verification, traceable evidence, and human oversight throughout the engineering workflow, coordinating agent swarms across ultra-long-horizon tasks while maintaining shared context. A Chief Agent Engineer coordinates agents and tools, prepares evidence, and escalates exceptions to human authorities, while an Engineering Terminal gives users a workspace to explore context, monitor activity, inspect assurance evidence, and act on risks and decisions. The platform is designed for interoperability across existing engineering toolchains, keeping humans in the loop with the context and evidence needed to intervene and make consequential decisions.
Target Audience
Primary customers are engineering organizations developing consequential software—systems where failure can affect safety, security, health, or material financial outcomes—that need to trust and accept AI-generated code through enterprise pilot programs and early-access engagements.
Features
- Chief Agent Engineer coordinates agent swarms across ultra-long-horizon engineering tasks, maintains shared context across connected agents and tools, prepares evidence, and escalates exceptions to appropriate human authority
- Engineering Terminal workspace for overseeing agentic engineering, including exploring context, monitoring agent activity, inspecting assurance evidence, and acting on risks, exceptions, and decisions
- Human-in-the-loop design that keeps humans involved throughout the workflow with context and evidence to guide work, intervene when needed, and make consequential decisions
- Interoperability across existing engineering toolchains, connecting agentic workflows and assurance evidence
- Backed by Kealu Labs research into multi-agent orchestration, shared context, architecture preservation, independent verification, and evidence-based assurance
- Model research and development spanning trillion-parameter ultra-large AI models alongside smaller, domain-specialized models designed to run locally, giving organizations flexibility over deployment and data processing