What if you could build and manage AI agents without diving deep into cloud setup or writing complex code?
That’s exactly where today’s new generation of AI agent platforms steps in. Two of the most talked-about solutions are Amazon Bedrock AgentCore and Knolli, each serving a unique role in how businesses and creators develop and manage intelligent digital assistants.
AWS AgentCore acts as the foundation layer, offering the power of enterprise-grade AI infrastructure, secure runtime environments, and scalable processing.
On the other hand, Knolli provides the user-facing management layer — a simple way to design, launch, and control AI copilots through a visual interface, with built-in content integration, workflow coordination, and analytics.
When combined, these two platforms represent the next evolution of AI system integration - a world where technical performance meets everyday usability.
Why does this matter? Because the AI agents market is exploding. The global market for AI agents is projected to hit roughly That kind of growth signals a major shift—from prototypes to production, and from isolated bots to fully-functional agents tied into workflows., up from about US $5.4 billion in 2024, growing at roughly a 45–46 % CAGR through 2030. Source
That kind of growth signals a major shift—from prototypes to production, and from isolated bots to fully-functional agents tied into workflows.
This blog delves into what AgentCore and Knolli each offer, compares their key features, and guides you in choosing which platform makes sense for your team.
Let’s begin by exploring the underlying capabilities of Amazon Bedrock AgentCore.
Amazon Bedrock AgentCore is a new system developed by AWS (Amazon Web Services) that helps businesses run and manage AI agents in a secure, scalable environment. It acts as the operational backbone for agents—handling complex functions such as task coordination, context management, and tool integration—so developers and teams can focus on logic instead of infrastructure.
AgentCore is part of the broader Amazon Bedrock ecosystem, which already provides access to major foundation models like Anthropic Claude, AI21 Labs Jurassic, and Amazon Titan.
What sets AgentCore apart is that it’s built specifically for long-running, multi-step agent tasks that need reliability, security, and observability—features that go beyond standard model inference.
According to the official AWS announcement, AgentCore helps teams “securely launch, scale, and monitor production-grade agents” using any framework or model. It provides a full set of modular services that can work independently or together:
These capabilities make AgentCore especially valuable for enterprises that want to move from AI prototypes to production-ready systems.
Instead of building their own infrastructure, organizations can use AgentCore to manage agents that perform customer support, content generation, data analysis, and workflow automation at scale.
While Amazon Bedrock AgentCore provides the technical foundation for running and scaling AI agents securely in the cloud, most users and teams still need an easier way to design, manage, and interact with those agents on a daily basis.
That’s where Knolli comes in — it bridges the gap between backend capability and user-friendly creation. Instead of writing code or configuring AWS environments, Knolli allows creators, businesses, and developers to visually build and control AI copilots that can still leverage the raw power of AgentCore in the background.
Let’s explore in detail:
Knolli is a no-code AI copilot builder that helps anyone, from content creators to enterprise teams, design, brand, and deploy AI assistants without writing a single line of code.
Instead of configuring servers or complex APIs, Knolli gives users a simple, visual workspace to create their own knowledge-based copilots that can answer questions, perform tasks, and even generate revenue.
Knolli works as a front-end control layer that complements systems like AWS AgentCore. While AWS provides the infrastructure and secure runtime, Knolli focuses on ease of creation, customization, and usability, making advanced AI accessible to everyone.
Knolli allows users to:
Here’s a quick look at Knolli’s key capabilities:
By combining ease of use with enterprise-level capability, Knolli enables users to launch professional AI copilots in hours instead of weeks. For many teams, it serves as the user-friendly front door to backend systems like AWS AgentCore — blending creative control with cloud-grade reliability.
Now that we’ve seen what Knolli and AWS AgentCore each bring to the table, let’s put them side by side to understand how they differ, where they overlap, and how using them together can unlock even more power.
While both Knolli and AWS AgentCore are designed to work with AI agents, they solve different problems within the same ecosystem.
AgentCore is the foundation — a backend system that securely runs, scales, and manages AI agents inside the AWS cloud.
Knolli, on the other hand, is the control center — a no-code platform that lets users build, brand, and operate those agents through an intuitive interface.
In short:
Here’s a detailed, side-by-side comparison:
If we imagine AI development as a car factory:
Using them together gives businesses both enterprise reliability and user-level accessibility — Knolli for managing and presenting copilots, and AgentCore for executing them in the cloud.
The world of AI agents is rapidly evolving — shifting from simple conversational tools into intelligent digital collaborators capable of reasoning, planning, and executing complex tasks.
As businesses adopt platforms like AWS AgentCore and Knolli, AI is no longer limited to answering questions; it’s beginning to take action, learn context, and work alongside humans in meaningful ways.
According to McKinsey’s analysis of Agentic AI trends, artificial intelligence is entering an era where systems can plan, reason, and act independently, instead of simply generating responses.
McKinsey highlights that the organizations seeing the biggest impact from AI are those building and managing networks of cooperating agents—for example, one agent might research, another might write or analyze, and another might make recommendations or automate actions (Source).
Platforms like AWS AgentCore are already structured for this future, providing secure runtime environments where multiple agents can run concurrently and exchange data safely.
At the same time, Knolli empowers users to visually design how these agents collaborate — creating end-to-end workflows that connect logic, action, and user intent without writing any code.
The next generation of AI agents will not only analyze information but also take action on it.
With the help of tool integration gateways and memory systems offered by AgentCore, agents can now execute tasks like generating reports, updating CRM systems, or managing cloud operations automatically. Knolli complements this by allowing teams to define these behaviors visually — linking knowledge inputs (like documents or FAQs) with specific outputs (like automated responses or content creation).
This bridge between knowledge and execution is what’s making agent technology valuable beyond experimentation.
As AI becomes more embedded in daily work, personalization will be key.
Users expect agents that understand their tone, preferences, and history.
Through custom branding, voice, and workflow design, Knolli enables businesses to give each AI copilot its own “personality,” creating more natural, on-brand experiences.
Meanwhile, AWS AgentCore’s identity and memory modules allow for persistent context across sessions — so agents remember users, preferences, and data securely over time.
Together, they form the backbone for context-aware, trustworthy, and adaptive AI systems.
AI isn’t just transforming enterprises — it’s opening new opportunities for individuals.
Platforms like Knolli are turning AI agent creation into a creator-friendly industry, where educators, consultants, and influencers can launch their own branded copilots and monetize their expertise.
This shift is part of a broader movement toward democratized AI entrepreneurship, where creativity and accessibility matter as much as engineering.
As the AI ecosystem matures, choosing the right platform becomes critical.
So, how do you decide between Knolli and AWS AgentCore — or know when using both together makes the most sense?
Let’s explore this in detail:
If your main focus is on designing, deploying, and managing AI copilots quickly without diving into code, Knolli is the right fit.
It’s built for creators, startups, and teams that want to turn ideas into working AI products — fast.
Knolli’s strengths include:
In short, Knolli is for anyone who wants to focus on user experience and creative control — not backend setup or server management.
If your organization already uses AWS services or needs full control over infrastructure, scalability, and data security, AgentCore is the better option.
It’s designed for developers and enterprises that need to run AI agents reliably across multiple systems, with enterprise-grade compliance and automation capabilities.
AgentCore’s advantages include:
If your team prioritizes governance, security, and cloud-native performance, AgentCore is the platform that fits those requirements.
For many teams, the most powerful setup is a hybrid approach — using Knolli for front-end design and management of copilots, and AgentCore for backend execution and scaling.
This combination allows creators and enterprises to benefit from both:
Here’s what that looks like in practice:
In the end, building and managing AI agents shouldn’t feel like configuring servers — it should feel like creating ideas that work for you.
AWS AgentCore gives teams the reliable foundation they need to run and scale agents, but Knolli turns that power into something everyone can use — visual, fast, and human-friendly. It bridges the gap between technical complexity and creative control, giving you the tools to design AI copilots that don’t just function — they understand and represent you.
If you’re ready to move from experimenting with AI to actually deploying copilots that deliver measurable impact —
Start building your first AI copilot today at Knolli.ai.
Create smarter workflows, launch branded AI copilots, and shape the future of how people interact with intelligence — all without writing a single line of code.
