AI Readiness + Workflow Review

Score readiness first. Then design the workflow.

Four short steps. The form takes most people 10–14 minutes. We score you across five readiness domains, identify the weakest constraint, and recommend a path before any tool is selected.

Readiness is a gate, not a label. The first three steps describe your business and the workflow pain. The fourth step measures the foundation — SOPs, source of truth, approval owner, error tracking, known-good examples — that determines whether AI implementation is safe today or needs a cleanup sprint first.

  1. Business basics
  2. Workflow pain
  3. Goals & constraints
  4. Readiness foundation

Your name*
Company*
Email*
Phone*
City*
Business type*
e.g., HVAC, accounting, e-commerce, real estate brokerage
Company size*

  • Solo
  • 2–5
  • 6–15
  • 16–50
  • 51–200
  • 200+
    Website Optional

Biggest operational bottleneck*
Where does delay or rework most accumulate today?
Repetitive tasks*
What does your team do repeatedly that feels mechanical?
Customer communication problems
Reply backlog, tone drift, missed escalations, etc.
Lead handling process
How do leads come in and get followed up today?
Quoting / reporting / documentation pain
Where do quotes, reports, or SOPs slow you down?
Tools currently used
CRM, inbox, ticketing, accounting, etc.
Monthly lead volume*

  • 0–10
  • 11–50
  • 51–200
  • 201–500
  • 500+
  • Unsure
    Team adoption concerns

Desired outcome*
What does success look like 30 days after launch?

Timeline*

  • 1–2 weeks
  • 1 month
  • 1–3 months
  • 3–6 months
    Exploring budget range*
  • Under $2k
  • $2k–$5k
  • $5k–$15k
  • $15k–$50k
  • $50k+
  • Unsure
    Risk tolerance*
    Low
    Medium
    High
    How conservative do you want the rollout to be?
    Data sensitivity*
    Low
    Medium
    High
    Human approval needed*
  • Always
  • Sometimes
  • Rarely

Anything AI should never do
Hard limits on tone, channels, decisions, or data.

These nine questions feed the AI Readiness Gate. They take 2 minutes and decide whether your business is ready to automate, needs a cleanup sprint first, or should pilot a single workflow.

SOPs / written procedures*

  • None — work happens by memory
  • Tribal knowledge — senior staff know the steps
  • Partially documented
  • Documented but not always followed
  • Current and followed
    Source of truth for customer/work data*
  • No system — paper or memory
  • Scattered across multiple systems
  • One system but messy
  • One clean system
    Data quality*
  • Unknown — never audited
  • Messy — known gaps and duplicates
  • Fair — usable but inconsistent
  • Good — clean and current
  • Audited and trusted
    Systems integration*
  • None — siloed systems
  • Manual export between systems
  • Partial integration
  • API-ready (not yet wired)
  • Fully integrated
    Human approval owner*
  • No owner
  • Ambiguous — depends on the day
  • Shared across a team
  • Named individual
    Who would approve AI output before it goes to a customer?
    Known-good examples for validation*
  • None
  • A few in staff heads
  • Documented handful
  • Twenty or more
  • Past output we could use to validate AI against.
    Error / issue tracking today*
  • None
  • Informal — email or chat
  • Spreadsheet
  • Ticketing system
  • Monitoring / alerting in place
    Permission / data sensitivity*
  • Low — public-style data
  • Medium — internal business data
  • High — customer PII or financial
  • Regulated — HIPAA, PCI, etc.
    Where institutional knowledge lives*
  • In one person's head
  • Scattered across emails and chats
  • Partial wiki / docs
  • One documented source