Managed AI workers that run the work between your tools.
We build reviewed AI-worker workflows that prepare lead, support, and operations work from approved sources, then stop for human confirmation wherever a real system change or customer promise needs it.
Prepare lead context before sales gets involved.
Map the source fields, qualification questions, and review boundary so your team sees need, timing, location, budget, and urgency in one place.
- Website chat
- Form enrichment
- Lead scoring
- CRM notes
Prepare support replies from approved knowledge.
Use source documents and escalation rules to prepare a useful reply draft and make the handoff rule visible for anything uncertain.
- FAQ answers
- Policy lookups
- Handoff rules
- Conversation logs
Map clean handoffs across tools.
Prepare the records, reports, reminders, tasks, and follow-up context that a person can review before a system update happens.
- CRM updates
- Calendar prep
- Report drafts
- Approval queues
Four jobs it runs inside the tools you already use.
Click a tool in the ring to inspect a possible workflow boundary. This is an interactive planning view, not a claim that your systems are connected.
Every inquiry has a defined first review
The intake questions, required context, and owner handoff can be defined before a lead workflow is connected to a CRM.
Repeat questions, prepared safely
Approved knowledge can support a response draft, while anything unusual stops with its source context attached for a person.
Clean records, reviewed handoffs
Report, calendar, and record workflows can prepare the right context so a team does not need to reconstruct it from several tools.
Humans stay in control
Permissions, approval gates, and logs are defined before launch. Risky moves always pause for review.
A clear build path you can actually follow.
Pick one workflow
We avoid broad assistant promises and start with the job that has the clearest business value.
One useful jobConnect trusted sources
The agent only uses the systems, documents, and fields approved in scope.
No mystery dataAdd approval gates
Risky sends, deletes, account updates, and customer promises stop for human review.
Humans stay in controlMeasure and tune
After launch, we watch output quality, handoffs, response time, and missed edge cases.
Improve with useAgents for business. Agents for people. And the protocols that connect them.
Today, your agent handles the work inside your business. Soon, your customers will have agents of their own. We are building for the moment they meet.
Agents for business
Scoped workflows that prepare lead, support, and operational context from approved CRM, calendar, and inbox sources before the permitted action is reviewed.
Agents for people
Personal agents that may help a customer compare options and prepare a request, subject to the person’s approval and the business workflow’s boundaries.
Agent-to-agent (A2A)
When a customer’s agent contacts your business, both sides will need clear source, permission, and approval rules around a request. We are researching the protocols that could make those handoffs inspectable.
Questions people ask before they buy.
What is the difference between an AI agent and a chatbot?
A chatbot mostly answers questions. A scoped agent workflow can prepare work across approved tools, such as a task draft, CRM-change proposal, reply draft, or lead handoff, with the required review boundary defined before it acts.
Can agents work with our current CRM?
Usually yes. We scope around your current tools and only connect what the workflow actually needs.
Will customers know when AI is involved?
That depends on the workflow. We recommend clear disclosure for customer-facing agents and human approval for sensitive communication.
How long does the first agent take?
A focused first agent often takes a few weeks. More complex workflows with many integrations or compliance needs take longer.
What is agent-to-agent (A2A) and why does it matter?
A2A describes the future case where both sides of a transaction have agents. That would require a customer request, business context, permissions, and approval rules to be exchanged safely. We are researching those protocol requirements, not presenting a finished A2A product.
Start with one agent that earns trust.
The first agent should be narrow, useful, measurable, and safe. Then you can expand from proof instead of hype.