Single AI chat
- One model at a time
- You move context manually
- You decide every handoff
- You check and retry yourself
Tell Nolo what you want to achieve. It can assign the work, use different models, run tasks in parallel, check the results, and keep the context moving.
Models change. Your way of working should not have to start over.
Different tasks need different team shapes. Agents can maintain their own relationships—you stay focused on whether the problem is solved.
Example · coding delivery
A common pattern—a strong model plans and coordinates, faster and cheaper models build in parallel, and a specialist model reviews before release. Not the only way to run a multi-agent team.
A common pattern—a strong model plans and coordinates, faster and cheaper models build in parallel, and a specialist model reviews before release. Not the only way to run a multi-agent team.
Demo data is shown here until real run metrics are available for the agents, models, duration, and cost.
Keep the simplicity of one request, while Nolo handles the parts that usually force you to jump between models, tools, and conversations.
Set the role, capabilities, and models—minutes later you have a partner to work with. It can deliver docs, pages, images, and video, not just chat.
Build a partnerSet your rules once. Context carries across sessions and gets more aligned over time.
Define the role, attach knowledge and skills, then enable search, docs, MCP, and more.
Use platform models, your API keys, or CLI agents per task. The same agent can ship docs, pages, images, and video—not chat alone.
Docs, apps, images, video, and 3D—give an idea, build it together.
For people already playing with agents and trying to ship real work—not just prettier prompts.
Yes. Rules, attached knowledge, and dialog history stay on the agent. When multiple agents collaborate, context flows as needed instead of restarting from zero every task.
The practical questions that matter once you want AI to do more than answer a prompt.
Yes. Rules, attached knowledge, and dialog history stay on the agent. When multiple agents collaborate, context flows as needed instead of restarting from zero every task.
The Nolo client never collects your conversations or personal data, and its source code is fully public. Every official release maps to an exact version in the public repository, so anyone can inspect and verify it.
AI can research, execute, compare, verify, and move in parallel.
Why you do it.What good looks like.What you truly want to create.