AI NewsReload wants to give your AI agents a shared memory

Reload wants to give your AI agents a shared memory

5:48 AM IST · February 20, 2026

There came a point when Newton Asare realized AI agents weren’t just tools anymore. “They were operating more like teammates,” he told TechCrunch. The realization crystallized when Asare and Kiran Das, both serial founders, noticed they were using AI agents to perform tasks they usually would have done themselves. Asare said he came to believe that the future lay in people managing AI employees. “And if that’s true, we’ll need a real system to manage them, with structure around onboarding, coordination, and oversight for digital workers,” he added. Last year, the duo launchedReload, an AI workforce management platform. On Thursday, the company announced itsfirst AI product, Epic, alongside a $2.275 million round led by Anthemis, with participation from Zeal Capital Partners, Plug and Play, Cohen Circle, Blueprint, and Axiom. Reload is a platform that lets organizations manage their AI agents across teams and departments. Companies can connect agents, regardless of who built them (whether by a third party or internally), assign them roles and permissions, and track the work they perform. “Reload acts like the system of record for AI employees, providing visibility, coordination, and oversight as agents operate across functions,” said Asare, the company’s CEO. Right now, he observed, teams are using multiple agents simultaneously for tasks such as coding, debugging, and refactoring. The problem is that these agents are often focused solely on whatever they were prompted to do and don’t necessarily retain long-term memory of what a product is or why they were told to perform a specific function. They operate, in other words, with only short-term memory. Over time, an agent can lose context, or the system can evolve away from its original intent. That’s why Reload is launching Epic. Built on top of the Reload platform, it serves as an architect alongside other coding agents, continuously defining a product’s requirements and constraints, and reminding agents what they are building and why, to keep a system consistent as it develops. “In software development specifically, coding agents can generate large amounts of code, but they don’t preserve shared system understanding over time,” Asare said. “Epic complements those agents by defining the system upfront and maintaining shared context as it evolves. It doesn’t replace coding agents; it makes them more effective.” Epic is designed to live inside the coding environments where developers already work. It can be installed as an extension in AI-assisted code editors like Cursor and Windsurf, running alongside other agents inside these tools. “When a team starts a project, Epic helps create the core system artifacts such as product requirements, data models, API specifications, tech stack decisions, diagrams, and structured task breakdowns,” Asare said, adding that these are the foundations that coding agents build against. “As development progresses, Epic maintains a structured memory of decisions, code changes, and patterns,” he continued. “If you switch coding agents, your structure and memory follow. If multiple engineers use different agents on the same project, everyone builds against the same shared source of truth.” Asare and Das previously had a company together that was acquired and this is their second company together. The AI infrastructure space is crowded. Competitors include LongChain, which helps with AI agent deployment and memory management, and CrewAI, which helps enterprises manage their AI agents. Das said Epic is different because it “defines the system upfront and maintains shared project-level context across agents and sessions,” with a focus specifically on building infrastructure to maintain AI employees. “Traditional workforce systems weren’t designed for AI agents operating as teammates,” said Das, who serves as the company’s CTO. “That’s the layer we’re focused on.” The fresh capital will go toward hiring and product advancement, specifically expanding the infrastructure needed to support a growing number of AI agents. “We’re building for the next era of work,” Asare said. This piece was updated to add the other investors in the round.