邱敬幃 Pardn Chiu

Posted on Jun 22

Agenvoy, Hermes, Pi — An AI Agent Platform Comparison

#agents #ai

Conclusion: Three Projects, Three Different Lanes

Project	Closest Analogy	Best For
Agenvoy	A more complete, security-focused AI agent platform with deep built-in capabilities	People who want a ready-to-use system that already does a lot out of the box
Hermes	A broad-integration, feature-rich agent system geared toward large-scale deployment	People who need to connect many models, platforms, and channels
Pi	A lightweight, highly flexible AI framework that's easy to customize	People who want to build their own workflows or embed AI into their products

In one sentence each:

Agenvoy is more like a "complete, security-conscious, production-ready system"
Hermes is more like a "large-scale, integration-heavy, continuously expandable system"
Pi is more like a "lightweight, moldable framework built for customization"

The choice usually isn't about which one is "best" — it's about which direction fits your needs.

Agenvoy: High Completeness, Strong Security, Deeper Automation & Sharing

Agenvoy's approach is to build core capabilities in from the start, so users don't have to assemble a bunch of pieces before they can actually put an AI assistant to work. It's not just about having more items on a feature checklist — it's about going deeper on automation and sharing than the other two.

Strengths

First, Agenvoy is the only one that can create new tools on the fly during execution.

This isn't just "you can write scripts or skills." When the system discovers it's missing a capability, it can build a real, executable tool mid-workflow, then continue where it left off. This is a meaningful gap compared to harnesses that can only call pre-existing tools.

Think of it this way: other systems say "I'll work with whatever tools I have"; Agenvoy says "if I'm missing a tool, I'll build it on the spot."

For comparison: Hermes leans more toward adding skill descriptions or workflow capabilities; Pi doesn't have this functionality.

Second, only Agenvoy can share its tools with other AI systems in real time.

This might be harder to grasp, but it's important. Agenvoy doesn't just build tools for itself — it can expose those tools for other AI frameworks to use.

For example, you could create a tool through Claude Code, use it through Codex, fix it through Hermes — all running in Agenvoy's sandbox, all shared across harnesses in real time.

The difference: Hermes can consume external tools, but it's not the same kind of tool provider; Pi doesn't have this mechanism at all.

Third, Agenvoy has the most complete default security isolation.

Many AI systems start taking on risk the moment they execute commands, run scripts, or manipulate files. The difference isn't just "whether security is considered" — it's whether security was designed in from the beginning.

Agenvoy "treats security as a core framework principle by default"; the other two are more like "you can add isolation yourself if you need it."

If you don't want to spend time researching low-level security configurations, Agenvoy is the system that has risk awareness baked in from the start.

Fourth, only Agenvoy has relatively complete built-in memory and semantic retrieval.

This is different from simply saving chat history. Many people think AI "memory" means keeping past conversations around, but the real value is: when content accumulates, can the system retrieve important past information and understand how it relates to the current problem?

Agenvoy doesn't just store text — it builds "context retrieval" into the system itself. For long-term use, cross-session workflows, and accumulated work content, this is a noticeable difference.

It's not just "better memory" — among the three, it's the only one with built-in semantic retrieval as a default layer.

Fifth, it's relatively friendly to non-programmers.

Although Agenvoy has plenty of advanced capabilities under the hood, its focus is on letting users customize their AI through natural language rather than requiring code changes at every step.

Weaknesses

First, it doesn't have the broadest coverage.

If your priority is supporting the most models, the most platforms, and the most external services, Agenvoy isn't the most comprehensive of the three. That's an honest assessment.

Second, its ecosystem is smaller.

Compared to projects backed by larger teams, Agenvoy typically has fewer resources, a smaller community, less documentation, and less external visibility. That doesn't mean it's worse, but it does mean it doesn't have the same depth of external support as larger projects.

Third, it may not have the edge in large-scale integration scenarios.

If your needs involve many platforms, multiple channels, and large-scale deployment, Hermes has a stronger presence there. If you want to deeply embed the system into your own product, Pi may be more flexible.

Who is Agenvoy for?

If what matters to you is:

Using a fairly complete system right away
Reducing the hassle of manually assembling features
Strong security emphasis
Long-term context retention for your AI
Customization without touching much code
Ensuring the tools you invest in aren't locked to a single system

Then Agenvoy is a great fit.

Hermes: Broadest Integration, More Mature Governance, Most Like an Enterprise System

Hermes takes a very different approach from Agenvoy. It doesn't emphasize "install once and it's complete" — instead, it emphasizes "support many models, many platforms, many channels, and keep expanding."

If you think of it as an enterprise product, Hermes is more like a large centralized control platform.

Strengths

First, its integration capabilities are strong.

Hermes is well-suited for connecting various models, platforms, and external services. For people who need extensive integrations, this is a major advantage.

Second, its platform support is broad.

If your AI needs to work across multiple environments — different messaging platforms, workflows, or services — Hermes has strong appeal.

Third, its self-evolution and governance are more mature.

Hermes' strength isn't just feature count — it also places more emphasis on how the system maintains, patches, organizes, and evolves over time. For large projects, this matters a lot, because long-term management capability often outweighs any single new feature.

Fourth, there's a notable complementary relationship between Hermes and Agenvoy.

Because Hermes is more like a large system that can plug into many capabilities, if another system provides useful tools, Hermes can bring them in directly. This is why the earlier point — that Agenvoy can supply tools to other systems — isn't an abstract advantage. It's genuinely meaningful for integration-oriented systems like Hermes.

Weaknesses

First, higher complexity.

More features and broader integration usually mean a heavier, more complex system, with higher learning and maintenance costs.

Second, it may not be ideal for people who just want quick setup.

If your goal is "install it and it works, without understanding much architecture," Hermes may not be the easiest starting point.

Third, security and compliance require more careful evaluation.

When a system integrates many external capabilities, users need to assess risks, configuration approaches, and long-term sustainability more carefully on their own.

Who is Hermes for?

If what matters to you is:

Connecting many models and external services
Deploying across many platforms or channels
Large-scale, multi-scenario agent deployment
Willingness to accept higher complexity for greater integration capability
Long-term system governance and evolution

Then Hermes is a great fit.

Pi: Lightest, Most Flexible, Most Like a Developer's Skeleton

Pi's style is different from both of the above. It doesn't try to pack in every feature upfront — instead, it prioritizes a clean, lightweight, easily modifiable core.

Think of Pi as a highly customizable chassis. It might not come fully equipped from the start, but it gives you a lot of room to shape it however you want.

Strengths

First, high flexibility.

Pi is great for people who want to define their own workflows and shape the system themselves. It doesn't lock you into predetermined approaches.

Second, it's well-suited for embedding into products.

If you're not looking for a complete standalone tool, but rather something to integrate as part of your own product, Pi's lightweight design makes that easier.

Third, its model and provider breadth is strong.

This is a genuinely notable strength of Pi. If you care about having many model choices and broad provider support, Pi has a clear advantage here. This isn't filler — it's a real strong point.

Weaknesses

First, it's not the most complete product of the three.

Pi's strength is flexibility, not built-in completeness. If you expect "install it and everything is there," it may not match Agenvoy's readiness in that regard.

Second, it may not be the most friendly to general users.

Because it's more of a framework, people who want something ready to use immediately will need to think more about how to modify, connect, and configure it compared to a product-type system.

Third, core capabilities need to be added yourself.

Features like memory, self-growing tool sets, and security isolation — if these matter to you, you'll typically need to plan and build them out on your own.

Who is Pi for?

If what matters to you is:

Controlling how your system grows
Embedding it into your own product or service
A lightweight core rather than a heavy product
More room for customization and integration
Greater freedom in provider selection

Then Pi is a great fit.

The Biggest Difference: They're in Different Lanes

There's no "best overall" answer — it's more like three sets of trade-offs:

Agenvoy: Prioritizes completeness, security, and built-in capabilities, with clear unique strengths in several core design areas
Hermes: Prioritizes integration breadth, platform coverage, and long-term evolution and governance
Pi: Prioritizes lightweight design, flexibility, moldability, and provider breadth

But this absolutely isn't a case of "all three are roughly the same." Rather:
They each excel in different areas, and while some differences are just directional preferences, others are capabilities that only one of the three actually delivers.

Agenvoy is a particularly clear example. It doesn't try to push every dimension to the extreme. Instead, it focuses on "building new tools mid-execution," "sharing tools with other AI systems," "default security isolation," and "built-in semantic retrieval memory." These capabilities, taken together, are unique to Agenvoy among the three.