How do we get a proactive AI agent built and secured for our team?
Alknoma, in the proactive agent space, builds and secures a proactive AI agent for your team in four steps: you name the work it should carry, we build it inside the tools your team already uses, we run it through simulated days of work with Minutehand until it carries the work right, then it goes live with your people.
1. Name the work
One recurring piece of work, from the event that starts it to the moment it is confirmed done. A question that goes unanswered. A ticket that needs shepherding from opened to closed. An approval that has to be collected from someone who is slow to answer. The narrower the work, the sooner the agent carries it right.
2. We build the agent
The agent is written for that work. It starts from the event that opens it or from a time it booked for itself, keeps a memory of who it asked and what is still open, and decides when to follow up, when to wait and when the work is done. It works inside the tools your team already uses; nothing moves to a new tool.
3. We secure it
Before it goes live, the agent runs through simulated days of work in Minutehand, against fake versions of the services it uses, with simulated people who answer late or not at all. Each run takes a few seconds and ends with a list of findings, each naming the declaration it was measured against. A run fails on the same words sent twice with nothing new, a move the service refuses, and acting before an approval. A follow-up sent before a person's declared time to answer is flagged for review. With a reviewer model, so is any fact the agent states that it was never given. Every run is an append-only log you can query with SQL and trace person by person.
4. It goes live
The agent reaches your people once the runs are clean. The scenarios it was tested against stay with it, so a change to the prompt, the model or the work is played through the same days before it ships.
What to bring to the first call
- The piece of work, in a sentence, and what "done" looks like.
- The tools the work happens in.
- The people involved, and how quickly each of them usually answers.
- What the agent must never do without a person's approval.
Price and timeline depend on the work, and the call is where they are set. Book a Google Meet or email [contact@alknoma.com](mailto:contact@alknoma.com). If you would rather build the agent yourself, Minutehand is free.
Frequently asked questions
- Do we need to be technical?
- No. You need to know the piece of work, who is involved and what the agent must never do without a person's approval. Alknoma builds the agent and writes the scenarios it is tested against.
- Which tools can the agent work in?
- The ones your team already uses. Minutehand, which the agent is tested against, today fakes Slack, Microsoft Teams, Asana, Jira, YouTrack, Notion, GitHub, Google Drive, AWS EventBridge, AWS SQS and Google Cloud Tasks, so an agent working in those is tested end to end before it goes live.
- What happens when the agent gets something wrong in testing?
- The run is an append-only log, so the mistake can be traced event by event. Any run can be forked from a checkpoint with the prompt, the model, a person or the world changed, and played forward again until the finding is gone.
Keep reading
When should an AI agent interrupt a human?
A proactive agent should interrupt a person for two reasons only: a decision it may not make, or news the person does not have. Here is how to tell, and how to test the timing before go-live.
How do you know an AI agent won't hallucinate before it goes live?
Buyers now treat hallucination as a security question. Here is how Alknoma tests an agent for it before it reaches a real person.
What are reactive, proactive and durable agents?
Reactive, proactive and durable are not three levels of one thing. They answer different questions about an AI agent: what starts it, and how long it lives.