Reload launches Epic to bring shared memory and structure to AI agents

The start-up says AI agents now work like teammates, prompting the creation of Epic, a tool that preserves system context across coding environments.
Reload launches Epic to give AI agents shared memory, helping companies maintain consistent product understanding and long-term context instead of relying on short-term prompts.

Founders of the Reload platform say AI is moving from simple automation toward something closer to teamwork.

Newton Asare and Kiran Das noticed that AI agents were completing tasks normally handled by employees, which pushed them to design a system that treats digital workers as part of a company’s structure instead of disposable tools.

Their platform, Reload, offers a way for organisations to manage these agents across departments, assign responsibilities and monitor performance. The firm has secured 2.275 million dollars in new funding led by Anthemis with several other investors joining the round.

The shift toward agent-driven development exposed a recurring limitation. Most agents retain only short-term memory, which means they often lose context about a product or forget why a task matters.

Reload’s answer is Epic, a new product built on its platform that acts as an architect alongside coding agents. Epic defines requirements and constraints at the start of a project, then continuously preserves the shared understanding that agents need as software evolves.

Epic integrates with popular AI-assisted code editors such as Cursor and Windsurf, allowing developers to keep a consistent system memory without changing their workflow.

The tool generates key project artefacts from the outset, including data models and technical decisions, then carries them forward even when teams switch agents. It creates a single source of truth so that engineers and digital workers develop against the same structure.

Competing systems such as LongChain and CrewAI also offer support for managing agents, but Reload argues that Epic’s ability to maintain project-level context sets it apart.

Asare and Das, who already built and sold a previous company together, plan to use the fresh capital to grow their team and expand the infrastructure needed for a future in which human workers manage AI employees instead of the other way around.

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