Articles tagged "comparison".
7 articles. Sorted newest first.
Agent SDK Comparison: ONTO vs Claude vs OpenAI vs Google ADK (2026)
An honest head-to-head of the four major agent SDKs — where each wins, where each loses, and how to pick the right one for your project.
ONTO vs LangChain: When Typed Memory Beats Chains
LangChain is the largest agent orchestration ecosystem in the world. So why pick ONTO instead? A direct comparison on memory, planning, consent, and operational concerns.
ONTO vs LlamaIndex: Agents vs RAG, Explained
LlamaIndex is the most popular RAG framework. ONTO is an agent SDK. They solve adjacent problems — but treating them as substitutes leads to bad architecture. Here's how to pick.
ONTO vs Mem0: Choosing a Memory Layer for AI Agents
Mem0 is a popular dedicated memory layer for LLMs. ONTO is an agent SDK with memory built in. What's the difference, and which one is right for your project?
ONTO vs Letta (MemGPT): Two Approaches to Long-Term Agent Memory
Letta (formerly MemGPT) pioneered the idea of agents managing their own memory through tool calls. ONTO takes a typed-graph approach. Same problem, different solutions.
ONTO vs CrewAI: Multi-Agent Without the Black Box
CrewAI made multi-agent orchestration accessible. ONTO takes a different shape — subagents under explicit consent scopes, a depth budget, and rolled-up cost. Which fits your problem?
ONTO vs AutoGen: Human-in-the-Loop, Done Right
AutoGen pioneered conversational multi-agent and human-in-the-loop patterns. ONTO takes a different approach to the same problem — Plan Mode as a runtime invariant. Here's how they compare.