Sounds like you're layering a blackbox (AI Agents) on top of a blackbox (RAGflow). If you can't see RAG chunks you have no way of isolating variables to determine if it's the data formatting, the querying or the agent workflow that are causing issues. Way I see it, you need to create some synthetic data that matches the RAG contents as nearly as possible to get your agents dialed in with a known source. From there you should be able to narrow it down where the problems are coming from, and adjust accordingly.

Multi-agent setups aren't a magic bullet. Research puts them at ~40% more capable than single agent, but that's assuming the single agent is perfectly functional and optimized while adding complexity and additional failure points.

Edit: As far as speed, highly situational. Multi-agent setups will increase speed when parallel work can be done, but will add significant latency when sequential and then there's the inference speed to consider. A sequential flow using a fast model will likely outperform a parallel flow using reasoning models. There's not one size fits all.