AI workflows for teams drowning in manual work.
Move37 builds fixed-scope AI systems that handle the repetitive parts of back-office work while your team keeps approval, judgment, and control.
Manual work hides in plain sight.
Your team probably has workflows everyone complains about but nobody has time to fix: PDFs, inboxes, spreadsheets, portals, CRM notes, internal policies, handoffs, and status updates.
The work still needs human judgment. It just does not need humans doing every mechanical step by hand.
The cost shows up as:
- Staff hours lost to repetitive review and data entry.
- Important details buried in inboxes and attachments.
- Customers waiting while simple steps bounce between people.
- Managers lacking visibility into where work is stuck.
- AI getting used quietly in unsafe, inconsistent ways.
Fixed-scope AI workflows, built around your actual process.
We build small, useful systems that sit around the work your team already does. The goal is not to replace your tools or rebuild your company. The goal is to remove slow, repetitive steps from one high-friction workflow.
Lead intake and follow-up
Turn calls, forms, emails, and voicemails into summaries, fit scores, missing-info checklists, draft replies, and CRM notes.
Document intake and summarization
Convert long PDFs, forms, reports, or applications into structured summaries your team can review.
Email and request triage
Sort inbound requests, extract details, draft responses, and route work to the right person with human approval.
Internal knowledge assistants
Answer questions from policies, SOPs, manuals, contracts, or internal docs with source citations and “not found” behavior.
Proposal and estimate drafts
Turn discovery notes and approved service menus into first drafts, assumptions, scope, and follow-up emails.
Management reporting
Turn KPI tables, project notes, and weekly updates into executive summaries, risks, trends, and next actions.
A simple build process. One workflow at a time.
Workflow audit
You bring one slow, repetitive, error-prone workflow. We look for volume, clear inputs, repeatable outputs, and a safe place to add AI.
Scope the build
We map the current process, define what AI should and should not do, and set human review points before work starts.
Build the system
We configure the workflow, connect tools where appropriate, test against real examples, and tune outputs with your team.
Train and hand off
Your users learn how to review outputs, catch edge cases, escalate issues, and operate the workflow safely.
Improve or expand
If the first workflow works, we improve it, extend it, or move to the next bottleneck.
Built for operators, not AI tourists.
Move37 is for teams that need practical implementation, not another lecture about the future of work. We focus on workflows where the rules are knowable, the value is obvious, and the risks can be managed.
- Done-for-you implementation
- Fixed-scope by default
- Human-in-the-loop guardrails
- Comfortable with regulated and process-heavy environments
- Existing tools first
- Measurable outcomes: time saved, faster response, cleaner handoffs
Messy lead conversations become clean follow-up packages in under 60 seconds.
Example: a Louisville commercial HVAC lead comes in through a phone call. The workflow produces a lead summary, fit score, missing information, next action, follow-up email, and CRM-ready note — all for human review before anything goes out.
Ask for the demoBring us one workflow that should not be this manual.
On the audit call, we will help you decide whether it is a good fit for AI. If it is, we will explain what a first build could look like. If it is not, we will tell you that too.
Book a 20-minute AI workflow auditBook an AI Workflow Fit Call.
Bring one repetitive workflow your team handles manually today. In 20 minutes, we will identify whether it is a fit for a fixed-scope AI workflow sprint, where the risks are, and what a practical first build could look like.
Schedule on CalendlyFAQ
What kinds of workflows are a good fit?
Repeatable workflows with clear inputs, enough volume to matter, and outputs that humans can review: document intake, request triage, policy lookup, report summarization, spreadsheet cleanup, and internal review queues.
Will AI make final decisions?
No. AI can prepare, summarize, classify, extract, draft, and route. Your team keeps final approval where judgment or risk matters.
Can this work in a regulated environment?
Yes, if scoped correctly. We design around data boundaries, source citations, review steps, logs, and escalation rules.
How long does a first build take?
Most first builds should be scoped in weeks, not months. The timeline depends on sample materials, tool access, review speed, and complexity.
Do you replace our existing software?
Usually no. Most MVPs work around the tools you already use: email, spreadsheets, shared drives, CRMs, form tools, project systems, and internal documents.