Custom agentic engineering for workflows that move revenue forward.

We architect and deploy custom AI agents across sales, marketing, support, and operations — helping businesses automate workflows, improve response quality, track performance, and move more opportunities toward revenue.

Workflow live

Lead to booked call

Qualified
  1. Lead captured Website form + call note
  2. Intent scored Urgency: high
  3. Owner routed Sales calendar matched
  4. CRM updated Next task created
90 sec responseBooked callClean handoff
Average weekly time returned to each owner
20+ hrs
Minimum revenue lift target for high-fit workflows
3×
Operating cost reduction target for routine-heavy processes
35%
The Gap

What is holding you back?

AI is moving fast, but most businesses still struggle to turn scattered experiments into systems that save time, improve decisions, and increase revenue.

  • The owner is stuck in daily operations

    You work 70 hours a week, and your calendar is full of follow-ups, approvals, team questions, and status checks — leaving too little time for strategy and growth.

  • AI feels hard to implement

    You know AI can change the business, but it is not obvious where to start, what to automate first, or how to avoid adding another disconnected tool.

  • AI experiments are not reaching the P&L

    The team may test prompts and AI tools, but those experiments rarely become lower costs, faster decisions, cleaner reporting, or measurable revenue movement.

  • Your system is not ready to scale

    Growth brings more leads, messages, decisions, and handoffs. Without AI built into the operating model, the business gets slower as demand increases.

Our Solution

AI employees built around time, cost, and revenue outcomes.

We design AI roles with clear ownership, data access, escalation rules, and KPIs. They are not disconnected bots — they become part of how the business responds, decides, reports, and moves opportunities forward.

30–50%
Routine work targeted for reduction in the first 2 months.
3 mo
Target payback window for each high-impact AI role.
P&L
Impact measured in operating and revenue numbers.
Mechanics

Digital employee mechanics

Each AI employee has a defined job — owner assistant, marketer, salesperson, analyst, or finance operator. The role runs 24/7, follows your business rules, and escalates when a human decision is required.

Method

How we measure success

  • Routine work is reduced by redesigning workflows, not just adding tools.
  • Each AI role has a business owner, KPI, and clear escalation path.
  • The system is optimized around time saved and revenue moved forward.
Connected stack

AI agents only matter when they sit inside the systems your team already uses.

We map the workflow around inputs, decisions, and outputs, then connect the agent to the tools where work already happens.

Inputs

Signals the system can listen to before work slows down.

  • Forms
  • Calls
  • Email
  • Chat
  • CRM notes
  • Ad leads
Decisions

Rules, models, and human approvals that keep the agent inside the operating model.

  • Qualification
  • Routing
  • SLA checks
  • Risk flags
  • Owner match
  • Policy rules
Outputs

The concrete work product your team can review, route, and measure.

  • Booked calls
  • CRM tasks
  • KPI briefs
  • Slack alerts
  • Review queues
  • Action lists
Coverage

AI roles that cover 60–80% of company routine.

Each AI role is designed around a real business function, clear ownership, and a measurable operational outcome.

  • R/01

    AI data analyst

    Turns business data into answers, weekly reports, anomaly alerts, and decision-ready insights.

  • R/02

    AI contract reviewer

    Reviews agreements, highlights risk, summarizes key terms, and prepares questions for legal review.

  • R/03

    AI marketing engine

    Generates brand content, campaign tests, SEO briefs, AI-search assets, and ROAS control reports.

  • R/04

    AI sales agent

    Responds to leads, qualifies intent, follows up, books meetings, and prepares clean sales handoffs.

  • R/05

    AI finance lead

    Maintains live P&L views, cash-flow scenarios, spend priorities, and revenue forecast signals.

  • R/06

    AI accounting operator

    Extracts invoices, receipts, and source documents, then prepares structured entries for review.

  • R/07

    Owner's AI chief of staff

    Manages briefs, meeting notes, research, calendar context, and team follow-through.

  • R/08

    + Custom AI role

    Have a workflow that doesn't fit a category? We design new roles around the function, data, and outcome.

    Scope a role →
Examples

What these AI roles can do.

Start with one high-value workflow, prove the operating model, then expand across the revenue engine. We also help your brand earn visibility in the age of AI search.

1 / 8

Scope a workflow on a free strategy call ->

Why Arq

AI architecture,
not another automation stack.

The market installs bots, adds GPT to processes, and counts saved hours. That is useful, but everyone does it. We focus AI on the revenue side — automation that works for your time and your revenue: speeding up decisions, protecting follow-up, and moving more opportunities toward cash.

  • D/01

    Revenue operating model

    Agents mapped to pipeline stages, owners, and KPIs — not floating tools without a manager.

  • D/02

    Connected business context

    CRM, inbox, calendar, and internal tools wired into one decision surface.

  • D/03

    Custom decision logic

    Approval rules, escalation paths, and governance encoded — not prompt-only demos.

  • D/04

    Ongoing AI operations

    Weekly tuning, KPI review, and iteration after launch — production, not one-off builds.

Process

The path to production. The entire team works within AI.

From strategy to working operating fabric in a focused 6-8 week pilot, with the foundation for long-term revenue and time leverage.

  1. Mapped

    Business diagnostic

    Map workflows, decisions, and revenue motion to find the highest-leverage AI roles.

    Signal
    Workflow inventory
    Output
    First build candidate
  2. Scoped

    AI systems blueprint

    Define each role's ownership, data access, escalation rules, and target KPI.

    Signal
    Operating rules
    Output
    Production blueprint
  3. Building

    Core build

    Engineer the agentic systems, connect data sources, and instrument the workflow.

    Signal
    Systems connected
    Output
    Working agent loop
  4. Live

    Workflow rollout

    Deploy AI roles into the live operating model with team training and clear handoffs.

    Signal
    Human handoff
    Output
    Managed deployment
  5. Tuning

    Optimization loop

    Tune prompts, models, and routing weekly against the business KPI and P&L signal.

    Signal
    KPI review
    Output
    Compounding system
Pricing

Plans built for different stages of AI adoption.

  • AI Pilot
    $3,500 / from

    Best for validating one workflow with a clear business outcome.

    • One priority AI role or workflow
    • Business KPI and launch scope
    • Fixed 2–4 week pilot window
    Start a pilot →
  • AI Operating System
    Custom / quote

    Best for businesses that need multiple connected AI systems.

    • Company-wide AI architecture
    • Advanced approvals, data flows, and governance
    • Ongoing optimization and technical partnership
    Request a quote →
Get Started

Ready to put your growth on repeat?

Book a free 30-minute strategy call. You leave with an AI business map, the first high-impact system to deploy, and a practical development plan.

Book a Free AI Strategy Call