Newton Asare realized that AI agents had evolved from being mere tools to becoming more like teammates, as he shared with TechCrunch. This insight emerged when Asare and Kiran Das, both serial entrepreneurs, noticed they were utilizing AI agents for tasks typically handled personally. Asare began to envision a future where managing AI employees would become essential.
“If that’s true, there will be a need for a formal system to manage them, including onboarding, coordination, and oversight,” he noted.
Last year, they launched Reload, an AI workforce management platform, introduced its initial AI product, Epic, alongside securing a $2.275 million investment round led by Anthemis, with contributions from Zeal Capital Partners, Plug and Play, Cohen Circle, Blueprint, and Axiom.
Reload enables organizations to manage AI agents across various teams and departments. It allows companies to connect agents from different developers, assign roles and permissions, and monitor their tasks. “Reload serves as the record system for AI employees, ensuring visibility, coordination, and oversight as agents work across functions,” said Asare, CEO.
Currently, teams use multiple agents simultaneously for tasks like coding and debugging. However, these agents often focus solely on their immediate tasks without retaining long-term knowledge of a product’s purpose or the reason behind specific instructions, operating with only short-term memory.
Eventually, agents can lose context, or the system may deviate from its intended purpose. Epic, built on the Reload platform, serves as an architect with other coding agents, consistently defining a product’s needs and constraints while keeping agents aware of their tasks, ensuring system consistency.
“In software development, coding agents generate code but lack long-term shared system understanding,” Asare explained. “Epic complements these agents by defining systems upfront and maintaining shared context as it evolves, enhancing their efficiency.”
Epic integrates into existing coding environments. It can be used as an extension in AI-assisted code editors like Cursor and Windsurf, working alongside other agents.
“When initiating a project, Epic assists in creating core system components like product requirements, data models, API specifications, tech stack decisions, diagrams, and structured task breakdowns,” Asare said, highlighting that these elements form the foundation for coding agents.
“As development advances, Epic preserves structured decision memory, code changes, and patterns,” he added. “Switching coding agents doesn’t affect your structure or memory. If various engineers use different agents on the same project, they all work from a shared source of truth.”
Previously, Asare and Das co-founded a company that was acquired, making this their second venture together.
The AI infrastructure industry is competitive, with rivals like LongChain, focusing on AI agent deployment and memory management, and CrewAI, supporting enterprise AI agent management.
Das pointed out that Epic is distinct because it “defines the system upfront and maintains project-level context across agents,” concentrating on maintaining AI employee infrastructure. “Existing workforce systems weren’t designed for AI agents as teammates,” added Das, the company’s CTO. “That’s our focus.”
The new funding will aid in hiring and product development, particularly expanding the infrastructure needed for an increasing number of AI agents. “We’re creating for the next work era,” Asare stated.
*This article was updated to include additional investors in the round.*