A chat interface does not tell the whole story
A chatbot is a conversational interface. An AI agent combines a model with instructions, tools and context to pursue a result. These can overlap: a chat application may provide tools, memory or tracked tasks. A product label alone does not establish its capabilities.
Ask a concrete question: after your request, should the system simply answer, or organise work whose steps and output you can inspect? What is an AI agent? explains the elements of that working role.
Choose based on the work
| Your need | What to check |
|---|---|
| Rewrite a passage or explain a concept | Answer quality and the ability to correct the exchange |
| Search your documents | Accessible sources, retrieval and access controls |
| Produce a report in several steps | Plan, available tools, progress tracking and an identifiable output |
| Divide research and review | Actual delegation, individual contributions and consolidation |
| Return to work later | Saved state, relevant memory and sources that remain valid |
A conversation may be enough for a one-off request. A tracked mission helps when several actions must produce a verifiable result. Adding agents also requires reviewing their contributions and monitoring costs: more roles do not guarantee a better answer.
Example: preparing a research brief
You need to decide whether a mobile repair service merits a pilot. A conversation can help frame the questions or rephrase existing notes. A mission can organise research, identify contradictions and produce a synthesis with sources.
When a separate check is useful, another agent can receive that contribution before the coordinator combines the results. Multi-agent collaboration explains this division. The Atelier Horizon kit provides synthetic material for your own trial; it is not a result already produced by Galaris.
Test before delegating more
Prepare a question with known sources and a fact to correct. Check whether the system cites the right material, distinguishes facts from assumptions and incorporates your correction. For a mission, also inspect progress and the destination of the final document.
If you expect continuity between pieces of work, explicitly test agent memory. Conversation history and durable knowledge serve different needs. Measure your review time as well: a longer answer is not necessarily a more useful result.
Where does Galaris fit?
Galaris is a self-hosted agentic OS: model access with tracking, agents, memory, tools and applications share one foundation. You can use its agents through its applications, messaging channels or external clients. Start with one agent, then organise a team when responsibilities justify it. The project is in alpha: evaluate the capabilities you need on your own case.
Your model and connected service choices determine external data flows and part of the cost. Review self-hosting and data before preparing an instance, then build an AI agent team to define your first piece of work.