aiXplain Joins the 2025 CB Insights AI 100: Building the Future of AI Agents
It’s easy to get lost in the noise of AI hype; new models, bigger benchmarks, flashier demos but beneath the buzz, a quieter question keeps coming up: How do we actually put AI to work?
One answer gaining momentum is the shift towards AI agents – systems that don’t just generate outputs, but can reason through tasks, take action, adapt over time and autonomously take decisions, giving humans more time to be creative and optimize their time. Agents turn raw model capabilities into structured, useful systems, bridging gap between intelligence and execution.
This shift is happening now for two reasons:
First, LLMs have matured—they are faster, cheaper, and more reliable in following structured logic, making them viable cores for goal-oriented agents. Second, enterprises are ready. They have moved past experiments and now face the operational challenge of deploying and managing agents in production. And for that, they don’t need just frameworks, they need platforms.
That’s where aiXplain comes in. Our focus has been on enabling teams to build and deploy these agents faster, more securely, and without needing to stitch everything together from scratch. We offer a unified platform designed not just for prototyping, but for orchestrating, scaling, and monitoring agents in enterprise environments.
That work and the growing need for it is exactly what CB Insights recognized when they named aiXplain to their AI 100 list for 2025, under the Agent Building & Orchestration category. The AI 100 highlights the 100 most promising private AI companies worldwide, and this year’s inclusion of the Agent Building & Orchestration category signals a clear shift: from model obsession to building usable, trustworthy systems that can operate at scale. However, this isn’t just about recognition. It’s about what the recognition represents, a growing shift in how enterprises are thinking about AI. Not as individual tools or copilots, but as operational platforms built to manage intelligent systems at scale.
Why Agent Building & Orchestration Matters Now
Agent frameworks are no longer experimental, they’re becoming core infrastructure. Real-world AI requires systems that can reason through tasks, call APIs, retrieve data, take action, and know when to stop. That’s orchestration, and it’s where real-world outcomes are won or lost.
AI agents give enterprises a competitive edge by automating repetitive tasks, scaling effortlessly, and enabling faster, data-driven decisions. They reduce costs, free up teams for higher-value work, and deliver consistent, real-time insights across operations. With always-on, accurate responses, they also improve customer experience and support seamless growth—without added complexity.
Beyond Point Solutions: The Shift to Agentic Platforms
As enterprises scale their AI adoption, they’re moving beyond fragmented tools and frameworks. What is needed now is a platform, one that brings centralized governance, modular design, and operational scalability. AI agents are evolving from isolated copilots to interconnected systems that plan, reason, and act across workflows. Managing fleets of agents requires more than orchestration, it demands an operational layer that ensures security, observability, and alignment with enterprise goals. Without it, organizations face fragmented logic, compliance risks, and limited scalability.
aiXplain’s Agentic Stack: Infrastructure for Enterprise-Grade Agents
Built around the principle that modularity enables scalability, the aiXplain Agentic Stack is an end-to-end platform designed to help enterprises build, govern, and distribute AI agents across any infrastructure. The aiXplain Agentic Stack is composed of five integrated layers designed for enterprise-grade agent deployment. The stack includes five integrated layers:
- Intelligence layer: Connects agents to enterprise data, tools, and systems using a communication protocol for executing real business logic
- Builder layer: Offers SDK and no-code tools to create modular agents and multi-agent systems, including support for vector and graph RAG
- Orchestration layer: Manages real-time planning and execution with vendor-agnostic deployment across cloud, hybrid, or on-prem environments
- Governance layer: Includes micro-agents like Inspector and Bodyguard for observability, compliance enforcement, and self-healing execution
- Application layer: Enables publishing, reusability, and cross-department alignment of agents, ensuring consistency with enterprise policies
What this unlocks:
- Builders can rapidly create, test, and deploy agents using business logic and enterprise data
- IT teams maintain governance, security, and flexibility with full observability and control
- Admins manage access, cost, and usage policies
- Auditors get full traceability and runtime visibility
- Business departments benefit from reusable, centralized, and customizable agents aligned with enterprise strategy
The Broader Landscape: Agent Builders and Beyond
The 2025 AI 100 list shows where AI is headed: beyond foundation models and into usable systems. AI agents, once seen as developer-side experiments, are now recognized as strategic infrastructure. Across the list, companies are converging around a clear goal of making AI work reliably in the wild. It’s not just about building smarter models, but about building systems people can actually use.
The Future of AI Agents
AI agents are quickly becoming the architecture that ties everything together. As adoption grows, agent frameworks are evolving beyond task orchestration into embedded systems capable of understanding context, making decisions, and operating autonomously across workflows. What’s ahead isn’t just more powerful AI, it’s AI that’s actually usable, trustworthy, and built for the real world.
Conclusion
We started with vanilla agents and quickly moved to agent frameworks, to arrive in less than a year to agentic platforms designed to not only help build and deploy agents, but manage, govern and distribute agents in an effective and secure way.
Agentic AI is gaining real traction not just in dev experiments, but in systems businesses are beginning to trust. Being named to the CB Insights AI 100 List for 2025 reinforces the direction we’ve been building toward: AI that’s structured, usable, and ready for the real world.
At aiXplain, we’re committed to making this shift accessible. That means building the infrastructure to support scalable agent deployment and also investing in learning resources and workshops to upskill both builders and business users. Our free course walks through the fundamentals of AI agents, dives into practical use cases like agentic RAG, and introduces no-code and SDK-based tools to help teams get started quickly and confidently.
Ready to build what’s next with AI agents?
Whether you’re a developer ready to build with aiXplain’s agentic stack, or a business leader looking to automate workflows, reduce risk, and scale securely, our team is here to help. Get in touch to explore how aiXplain can tailor AI agents to your data, tools, and goals so you can future-proof operations, accelerate innovation, and lead with intelligence.
Let’s build agents that do more than respond.
Let’s build agents that drive results.
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