Democratizing AI Agents: nemo’s Approach to Meeting Audiences Where They Are for Everyday Business Workflows
nemo was conceived to address a gap many organizations encounter as artificial intelligence moves from experimentation into everyday operations. “The AI platforms I’ve come across often encompass some level of code; they aren’t inherently no-code,” explains Blas Giffuni, Head of North America at Navigamo. “This still excludes a section of the population that may not have any knowledge of code.”
A periphery built by Navigamo, which is a consultancy focused on digital visibility and applied AI adoption, nemo positions itself as a democratized, no-code way for teams to deploy AI agents directly into their workflow without the technical expertise or dedicated AI teams at the corporate level. “We’ve created a simplified process where anyone who knows how to send an email can create an AI agent using nemo,” Giffuni notes. “It is designed to be truly no-code.”
Giffuni highlights that nemo is designed for accessibility, allowing users to create agents through written instructions, uploaded documents, and contextual guidance rather than code. “These agents are designed to help people become better and more efficient,” he says, adding that the intent is not to replace the workforce but rather augment it and support it.
Launched in August 2025, nemo entered the space with an already established wide clientele, according to Giffuni. This, he credits to a belief that while interest in AI is widespread, ownership of AI within organizations remains scarce. By 2030, AI-powered agents could generate up to $2.9 trillion in US economic value per year. Yet today, only 11% of organizations have agents in production, with 40% of agentic AI projects predicted to fail by 2027 due to automation using broken systems.
As a result, Giffuni believes that employees may often manage fragmented processes, switching between emails, documents, and multiple browser tabs to complete routine tasks. nemo seeks to bridge that gap, consolidating predictable and repeatable process steps into agents so that people can focus on higher-value work.
Functionally, nemo allows users to build agents tailored to specific roles, teams, or company-wide use cases. Agents can be trained on internal documents, websites, and approved materials, enabling consistent outputs aligned with the organizational context.
Giffuni notes that this structure can allow companies to deploy a single shared agent or multiple specialized agents, depending on operational needs.
In practice, nemo can manifest as an AI admin intern, virtual customer service representative, marketing assistant, or campaign development manager.
The platform also incorporates a flexible, multi-modal architecture, designed to connect to multiple AI systems, selecting models based on task requirements. “If you’re married to a single LLM, you’re missing a whole lot,” Giffuni says. “We can connect our models to other existing LLMs, curating a database of multiple AI productivity tools without being tied to any one LLM.”
He explains that content creation, research, and analytical workforces may require different strengths, yet nemo is designed to accommodate that variation, positioning itself as an end-to-end tool. This approach, Giffuni emphasizes, can enable organizations to maintain a consistent tone and voice across outputs, which could be critical to establishing a cohesive brand identity.
From a business operations standpoint, nemo positions itself as an alternative to static interfaces, providing interactive experiences for handling routine questions and escalating complex issues to human staff. “Let people handle the critical parts that need to be handled by people,” Giffuni says, noting that customer trust often depends on timely, personal follow-up rather than automated responses alone.
Over the next several years, nemo is expected to integrate with additional platforms and business systems while preserving its core simplicity. “We’re deliberately resisting the temptation to bolt on every possible feature,” he says. “Right now, there are many tools out there already; what there isn’t, though, is simplicity.” The goal is to maintain a clean, intuitive interface layered over complex infrastructure, ensuring that increased capability does not come at the expense of usability.
Ultimately, the platform reflects a human-centric philosophy toward AI adoption. Rather than positioning technology as an end in itself, nemo frames itself as an enabler of better processes and more meaningful work.
