AI-powered enterprise work

One platform to deploy AI employees across critical workflows.

Replace fragmented tools and generic assistants with specialized AI employees built for real roles like recruiting, intake, coordination, sales support, and analysis.

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Role-specific execution Human oversight controls Enterprise-ready rollout

AI employee command

6 roles active · 2 awaiting review

At-risk workflows

Task throughput

Team workload

Recruiter

52%

74%

148%

63%

81%

Coordinator

61%

90%

82%

44%

68%

Patient Intake

71%

75%

79%

56%

72%

Operator assistant

“The recruiting employee flagged a bottleneck in interview scheduling. Want me to queue a fix for review?”

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Built for teams moving beyond generic AI tools

Nexa

Ardent

Clarity

Northstar

MetricOS

VantaCore

Plan, deploy, oversee

Optimal visibility across AI employees, workflows, and departments

Control deployment, capacity, approvals, and execution quality from one command layer. Keep humans in the loop where it matters without slowing everything down.

Plan & resource

See role capacity before work breaks.

Understand where AI employees are overloaded, where human approval queues are growing, and where specific business functions need another synthetic operator.

Role capacity views

Approval bottleneck tracking

Operational coverage planning

Project team workload

Mon

Tue

Wed

Thu

Fri

Recruiter

50%

100%

50%

150%

80%

Coordinator

100%

90%

40%

90%

Analyst

70%

40%

90%

60%

80%

Execute work

Move from request to action without manual coordination overhead.

AI employees handle structured execution flows, browser tasks, messaging, analysis, and follow-ups while preserving boundaries and review.

Repeatable execution flows

Browser and inbox work

Cross-team handoffs

Workflow board

Review candidate interview notes

Validate intake answers before routing

Follow up on missing documents

Prepare weekly ops summary

Draft response to inbound lead question

Check browser task status

Push approved update into CRM

Escalate edge-case exception

Monitor & review

Review what happened, why it happened, and what needs intervention.

Track outcomes, audit decisions, inspect execution traces, and step in when confidence drops or business rules require a human.

Review queues

Confidence-aware interventions

Action and reasoning logs

Review dashboard

Pending review

Blocked actions

Low confidence

Learn & adapt

Build smarter operators over time without losing control.

Improve performance using feedback loops, reviewed outcomes, and company-specific operating context rather than one-size-fits-all prompting.

Feedback-driven refinement

Business-specific context layers

Safer adaptation over time

Learning signals

Reviewed outcomes

Updated role constraints

Knowledge additions

Built for actual teams

Start with the role you need most. Expand from there.

Roll out AI employees where the operational pain is real, then add more coverage as the model proves itself inside your workflows.

Recruiter

Interview candidates, summarize performance, handle early-stage screening, and keep hiring momentum moving.

Patient Intake

Collect information, guide intake flows, triage requests, and reduce administrative drag on staff.

Coordinator

Track requests, route tasks, manage handoffs, and keep internal execution from slipping between people.

Analyst

Review structured inputs, identify patterns, produce summaries, and surface what actually matters.

Shared workspace + execution

Human judgment and AI execution work better together.

Give your team a clear operational surface for planning, editing, reviewing, and approving work while AI employees handle the grunt work underneath.

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Next-gen operations board

What are the next high-value roles to automate?

Where are human approvals slowing output?

Which requests can be routed automatically?

What is the highest-friction workflow today?

Which exceptions should always stay human-owned?

What decisions need more context?

How should outcomes be measured?

What operating rules changed this week?

Why teams choose this model

Discover what makes role-based AI employees a better operating layer.

The goal is not another general-purpose chatbot. It is to deploy bounded, useful synthetic workers that carry real load inside the business.

End-to-end enterprise work management

Turn time-consuming, repeatable business work into structured execution with oversight. Reduce drift, dropped steps, and coordination overhead.

See the platform

Unmatched control by default

Permissioning, approvals, role boundaries, and review queues keep the system useful without asking you to trust blind autonomy.

Talk to sales

Support that scales with you

Start with one role, pilot in one workflow, and expand deliberately based on operational reality and measured outcomes.

Start a pilot

Connected work

Integrate core business systems with just a few clicks.

Give AI employees the context and surfaces they need to read, write, route, follow up, and execute without forcing your team into a brand new stack.

Slack

Google

Zoom

Salesforce

Gmail

HubSpot

Calendar

Docs

Drive

Jira

Dropbox

Okta

See what AI employees could look like inside your business.

Start with one high-value role. We’ll walk through where it fits, what it should own, where humans stay involved, and how a pilot rollout would work.