Why not use one chatbot for everything?

One model doing every step tends to do each one a little worse. Separate agents with one job each are easier to test, easier to fix, and easier to trust.

Can the agents use our tools?

Yes, through controlled tool access. Each agent gets only the tools and data its step needs, and every action it takes is logged so you can see what it did.

Do we install anything?

No. The workflow runs on LTFI, which we host and operate for you. Your team works with the output and approves the decisions that need a person.

Multi-agent AI workflows

Automate

Many specialists, one pipeline, not one chatbot doing everything.

A multi-agent workflow splits a job across several specialized AI agents, each with one task, a clear handoff, and a point where it stops. It is for teams trying to make one chatbot research, write, check, and publish, and getting uneven results. Kief Studio designs the agents, the handoffs, and the checks between them, connects them to your tools, and runs the workflow for you on LTFI.

What we do

Break the job into steps and decide which ones an agent should own.
Give each agent one task, the tools it needs, and a stop condition.
Put checks between agents so mistakes are caught before they move on.
Keep a person in the loop for decisions and exceptions, and run it on LTFI.

Who it is for

Teams with multi-step work, such as research, drafting, review, and publishing, where each step has its own rules.

When to look elsewhere

A demo agent with no stop condition and no person who can step in. If one well-built automation does the job, we will build that instead.

What we can stand behind

We wrote DeSlop. Thousands of developers use it to strip the slop.
No shared hosting. Dedicated infrastructure.
Security is a byproduct of good engineering.