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February 23, 2026Reload, an AI workforce management startup, has raised $2.275 million and launched Epic, its first AI-native product designed to help organizations manage and retain memory across AI agents.
The round was led by Anthemis, with participation from Zeal Capital Partners, Plug and Play, Cohen Circle, Blueprint, and Axiom.
The startup plans to use the new capital for hiring and product development, particularly to scale the infrastructure needed to support a growing number of AI agents.
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Meet Reload, the Operating System for AI Employees
Founded in 2025, Reload is an AI platform designed to coordinate multiple agents across teams and departments. Serial entrepreneurs Newton Asare and Kiran Das had an epiphany when they noticed that AI agents were not just tools anymore. Rather, they were used to perform tasks that individuals usually would have done themselves.
“They were operating more like teammates,” Asare told TechCrunch. “And if that’s true, we’ll need a real system to manage them, with structure around onboarding, coordination, and oversight for digital workers.”
This belief led Asare and Das to build Reload, a platform that enables companies to integrate AI agents into their workflow. The platform allows businesses to connect AI agents, assign roles and permissions, and track their performance across various functions.
Reload as a platform enables organizations to 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.
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Reload’s First Product, Epic, is Acting as an Architectural Partner for Coding Agents
Development teams today often run multiple AI assistants in parallel for coding, debugging, and refactoring. However, these agents typically work from short-term prompts and lack a deep understanding of the product they’re contributing to. As systems evolve, this lack of long-term memory can cause agents to lose context or stray from the original design intent.
Epic, Reload’s first AI product, addresses this gap by acting as an architectural partner for coding agents. Its role is to define and maintain the product’s requirements and constraints, and remind other agents what they’re building and why. This keeps the system coherent as it grows.
Epic integrates seamlessly into existing developer workflows, installing as an extension in AI-assisted code editors like Cursor and Windsurf. When a team starts a new project, Epic helps generate core system artifacts, including product requirements, data models, API specifications, and tech stack decisions.
These artifacts serve as a reference layer for coding agents, and Epic maintains a structured memory of decisions, code changes, and patterns as development progresses.
This approach allows teams to swap out coding agents without losing context, and ensures everyone – human and AI – is aligned on the same system design. Epic’s focus on shared project-level context and infrastructure support for AI employees sets it apart from other AI agent platforms.
Asare and Das had previously teamed up to build a company that was acquired, so this is their second company together. The AI infrastructure space is bustling with competition, including LongChain and CrewAI, which offer AI agent deployment and management solutions.
However, Das emphasizes that Epic stands out by defining the system upfront and maintaining shared project-level context across agents and sessions. “Traditional workforce systems weren’t designed for AI agents operating as teammates,” Das explains, highlighting Reload‘s focus on building infrastructure to support AI employees.
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The new funding will drive hiring and product development, specifically expanding the infrastructure to support a growing number of AI agents. “We’re building for the next era of work,” Asare says, outlining the company’s ambitious vision.
Main Image: Newton Asare and Kiran Das, Reload Co-Founders. Image Credit: Reload

