AI playbooks for mid-market operators. One problem per page. What breaks and how we fix it.
Thirty-two short pages, each on one problem that costs a mid-market company time or money: slow intake, approvals that stall, missed calls, AI that breaks after launch. Pick the one that sounds like your week.
The library. Filter by the kind of problem.
Every playbook takes one problem and answers three questions: what usually breaks, how we build it so it does not, and when it is the wrong move. Each one links to one product that does the work and one industry where the problem shows up. Each takes about four minutes to read. If none of them fits your problem, or three of them do, ask Roo, Webaroo's AI, for a straight answer.
32 playbooks15 playbooks7 playbooks4 playbooks6 playbooks
AI and agents
- 4 min read
AI agents for operations
Operations teams know agents could take work off the floor. The first project usually goes to the most interesting workflow, not the most countable one.
- 4 min read
Document intake automation
Documents arrive by email, upload, and scan, and a person retypes them into the accounting system, the spreadsheet, and the tracker.
- 4 min read
Workflow automation with approvals
The workflow is clear and the steps are known, but each item still waits days for a person to push it through, because every step is a copy and paste between systems.
- 3 min read
Appointment booking agents
The front desk cannot answer the phone, check people in, and keep the schedule full at the same time, so booking calls go to voicemail and open slots stay open.
- 5 min read
Approval gates for AI actions
An agent that can write to your systems is a liability the moment it is wrong, and in a finance team it is wrong in front of an auditor.
- 4 min read
Choosing an AI model provider
Picking a model provider feels like a bet on the company, so teams either stall or sign with whoever demoed last.
- 4 min read
Ask your documents: answers from your own files
The answer exists in a document somewhere, and the person who needs it asks the one colleague who always knows instead.
- 4 min read
Copilots for your team
Everyone on the team already uses a chatbot, and each one answers from the open web with no idea how your company works.
- 4 min read
AI phone and chat agents
The phone rings while the one person at the desk is checking in a guest, and the call goes to voicemail.
- 4 min read
AI agent that answers every inbound lead
Inbound leads arrive at all hours and wait for the next person who checks the inbox.
- 4 min read
IT helpdesk agents
One person handles IT for the firm, and the same questions reach them every week: VPN, passwords, a locked account, a new laptop, access to a shared folder.
- 4 min read
Recruiting coordination agents
Hiring in a firm without a recruiting team runs on whoever is free: applications pile up until Friday, interview scheduling takes a week of email, and candidates go quiet because nobody told them where they stand.
- 4 min read
Content and campaign workflows
Content work stalls between stages: the brief lives in a chat thread, the draft lives in a doc, the approver is traveling, and the launch date arrives first.
- 4 min read
Memory and context layers
Every agent you add starts with its own memory, so the phone line, the chat widget, and the document bot each learn your company from scratch and never share what they learned.
- 4 min read
Model-agnostic AI architecture
The model market moves every few months, and the one you built on last year is now slower, costlier, or weaker than what shipped since.
Custom development
- 4 min read
API integrations for AI
The agent can talk, but the work lives in the ERP, the CRM, the phone system, and the payment processor, and it cannot touch any of them.
- 4 min read
Legacy modernization
Your business runs on a system nobody wants to touch. The people who built it are gone, nothing around it is tested, and the business cannot stop for a rewrite.
- 4 min read
Internal tools and admin panels
The work that runs your company lives in spreadsheets, shared inboxes, and an admin screen someone built years ago that nobody dares touch.
- 4 min read
Data pipelines for AI
The agent is ready and the data is not: three systems disagree, the policy it quotes is last year's, and it can read a folder it should never have seen.
- 4 min read
Custom web and mobile apps
The template did the job until the business grew around it, and now every change is a workaround on top of a workaround.
- 4 min read
Shopify and headless commerce
Shoppers arrive with a question about fit, shipping, or stock, and the store cannot answer it until a person reads the inbox the next morning.
- 4 min read
Your first AI product, from plan to production
The AI project gets approved on a slide and then spends six months becoming a demo that runs on a laptop.
Operate
- 3 min read
Running AI in production
The launch went fine. Then the system kept running on data nobody tested, through a model update nobody noticed, with nobody reading what it did.
- 4 min read
Testing AI after launch
An agent that passed every test in week three can be wrong in week nine, and nothing on the screen looks different.
- 3 min read
Security and access controls for AI
An AI agent is only as safe as the access it has, and most get more than the job needs.
- 4 min read
Cost control for AI apps
An AI feature that costs almost nothing in a pilot becomes a monthly line item once the storefront sends it every product question.
Industry
- 4 min read
AI for construction firms
Change orders, pay applications, and lien waivers arrive as PDFs, phone photos, and email threads.
- 4 min read
AI for logistics brokers
A quote request lands by email or web form and waits for whichever rep gets to it first.
- 4 min read
AI for clinics
New patient calls, reschedules, and refill requests arrive while the desk is checking people in, so the desk answers the room and the phone goes to voicemail.
- 4 min read
AI for members clubs
Member requests come in at all hours, by phone and chat, and wait until someone is on the desk.
- 4 min read
AI for CPA firms
Every client sends a different stack: prior-year returns, W-2s, 1099s, K-1s, brokerage statements, and a phone photo of a 1098.
- 4 min read
AI for consumer brand launches
The site goes up as a theme with placeholder copy, so early visitors leave without leaving a name.
What owners ask before the first call.
A Webaroo playbook is a short page, about four minutes to read, on one business problem. It names what usually breaks, shows how we build the fix, and says plainly when the fix is the wrong move. It is written for the owner or operator who has the problem, not for an engineering team.
Four groups: AI and agents, custom development, operate, and industry. AI and agents covers workflows, documents, approvals, booking, choosing a model, phone and chat, and memory. Custom development covers integrations, rebuilds, internal tools, data pipelines, sites, stores, and apps. Operate covers running AI after launch: monitoring, security, and cost. Industry covers six businesses: construction firms, logistics brokers, clinics, members clubs, CPA firms, and consumer brands.
Start with the one that names the problem costing you the most right now. If you are not sure which that is, ask Roo, Webaroo's AI, or book 15 minutes with Connor Murphy, our Founder and CEO. If there is a fit, the paid 10-day assessment delivers an AI inventory, risk tiers, the top 3 workflows with today's numbers and a 90-day plan.
Tell us what is costing you time. A straight answer first.
The first paid step is your AI strategy, a 10-day AI readiness assessment: AI inventory, risk tiers, the top 3 workflows with today's numbers and a 90-day plan.
Book 15 minutes with Connor