USE CASE

Autonomous Digital Workforce

Deploy AI Workers that own workflows end-to-end. Scale operations without scaling headcount.

The Workflow Ownership Gap

Chat-based AI assistants help with single tasks, but they don't own workflows. Humans still coordinate across tools, gather context, and execute every step manually.

Organizations need digital colleagues that can actually move work forward — from trigger to completion.

Why Chat Assistants Aren't Enough

Without workflow autonomy, teams remain trapped in manual coordination

Trapped in Chat Interfaces

AI assistants only answer questions — they can't own a workflow from trigger to completion

No Workflow Ownership

Humans still coordinate across tools, gather context, and execute every step manually

Scaling Bottlenecks

Growth requires linear headcount increases — no path to leverage AI for operational scale

Repetitive Work Fatigue

Teams spend hours on manual tasks that could be automated, leading to burnout and attrition

DIGITAL COLLEAGUES IN ACTION

Pre-Configured AI Worker Templates

Designed to own complete workflows in your most critical functions — from support to sales to operations

01

Customer Support & IT Helpdesk Workers

Transform support operations by automating tier-1 resolutions while escalating complex cases with full context.

Target: 40-60% reduction
in tier-1 ticket backlog — typical pilot results

What They Do

Auto-triage and route incoming tickets to appropriate queues

Resolve routine tier-1 issues using runbooks, FAQs, and knowledge base

Draft detailed responses and knowledge articles for human review

Escalate complex cases with clean summaries and recommended next steps

02

Sales & Revenue Workers

Amplify sales productivity by automating CRM maintenance, account research, and outreach preparation.

Goal: 30% more time
for reps to focus on high-value selling — early results

What They Do

Maintain CRM hygiene — auto-update records based on email, calendar, and activity

Generate concise account briefs before customer meetings

Draft personalized outreach and follow-ups based on recent interactions

Flag at-risk deals and surface accounts requiring attention

03

Operations & Finance Workers

Eliminate manual report compilation and free finance teams to focus on analysis and strategic planning.

Target: 80% faster
monthly close process — pilot deployment goals

What They Do

Assemble recurring reports from approved data sources automatically

Surface anomalies, policy breaches, and exceptions for human review

Draft narratives and commentary for month-end financial packs

Monitor compliance and flag issues before they become problems

Core Design Principles

How we're building AI Workers to go beyond chat — autonomous workflow execution with built-in governance

Pre-Configured for Common Roles

Job-specific AI Workers come ready with domain knowledge and best practices for Support, Sales, Operations, Research, and more.

Pre-trained on common workflows and industry patterns

Customizable to your specific processes and tools

Plug into existing systems via MCP integrations

End-to-End Workflow Execution

Workers monitor triggers, gather context, execute permitted actions, and deliver completed tasks — not just answer questions.

Event-driven triggers and scheduled workflows

Multi-step task orchestration across tools

Handoff protocols for seamless human collaboration

Governed Autonomy

Every AI Worker operates within strict, auditable boundaries — what data it accesses, what actions it can take, when to escalate.

Data access scoped to role and department

Action whitelists with approval workflows

Automatic escalation for edge cases and high-risk actions

Human-in-the-Loop by Design

Workers know when to stop and ask for help. Ambiguous, high-stakes, or novel situations trigger human review automatically.

Confidence thresholds trigger escalation

Approval queues for sensitive operations

Full audit trail of decisions and actions

DEPLOYMENT PATH

Post-Release Deployment Timeline

Our target deployment path following initial platform release

Currently in early-access phase — we're partnering with select enterprises to co-design autonomous AI Workers for their specific workflows before general release.

Week 1

Select & Configure Worker Template

Choose a pre-built AI Worker for your target function. Connect to required tools and data sources.

Worker configured for target role
Tool integrations established
Initial policies defined
Week 2-3

Define Actions & Guardrails

Set what the worker can do autonomously vs. what needs approval. Establish escalation rules and thresholds.

Action permissions configured
Escalation rules set
Approval workflows defined
Week 4-5

Pilot with Limited Scope

Deploy to one workflow or team. Monitor closely, gather feedback, refine policies before broader rollout.

First workflow automated
Team feedback collected
Policies validated and refined
Week 6+

Expand Coverage & Scale

Apply learnings to additional workflows and teams. Measure impact and continuously optimize performance.

Multi-workflow deployment
Measurable productivity gains
Continuous improvement cycle

Target Business Outcomes

Goals we aim to help enterprises achieve with autonomous AI Workers

Scale Without Headcount

Goal: Handle 2-3x volume growth without proportional hiring increases

24/7 Availability

Consistent coverage and quality — no vacation, no sick days, no shift gaps

Focus on High-Value Work

Target: Free teams to spend more time on strategy, relationships, and complex problem-solving

Measurable Outcomes

Track tickets resolved, deals progressed, reports generated — clear productivity metrics

Impact targets based on deployment goals and initial pilot feedback. Actual results will vary by organization, workflow complexity, and implementation approach.

Co-Design Autonomous AI Workers with Us

Join our early-access program and help shape how AI Workers operate in your industry. Limited partnerships available for this co-design phase.