Questions, answered.

Two weeks end-to-end. Week one is discovery, shadowing and stack review. Week two is scoring, prioritization and the deliverable readout with your leadership team.

Read access to the tools we're auditing (CRM, support, ops stack), an org chart, and 30-minute interviews with 4–6 people across functions. We sign NDAs upfront and work through your SSO.

No. Most of our clients don't have one. We bring the technical lens — your team brings the business context. If your stack is messy, that's the point of the audit.

An AI Readiness Score, a prioritized opportunity map with effort/impact scoring, cost-saving estimates per workflow, and a 90-day roadmap. Delivered as a live readout plus a written report.

Default is remote — it's faster and cheaper for you. We'll fly in for the kickoff and readout if you want it, billed at cost.

Yes, before any discovery call. We'll sign yours or send ours — whichever moves faster.

Whoever owns the budget and whoever owns the workflows — usually the founder or CEO plus one operator per function. Keep it under six people so decisions actually happen.

Then we tell you, and we tell you what to fix first. Sometimes the honest answer is 'clean up your data and your processes before you automate anything.' You still leave with a roadmap — just a different first step.

We score data quality, process maturity, stack compatibility and team readiness per workflow, then weight by business impact. It's a prioritization tool, not a vanity metric — the point is knowing what to build first.

Yes. The audit is a standalone deliverable with everything documented — roadmap, scores, estimates. Some clients implement it with their own team. We'd rather earn the build than trap you into it.

Typically 3–4 weeks after the audit wraps. We don't wait for the perfect spec — we ship the highest-ROI workflow first and iterate from production.

A senior strategist owns the relationship, plus 1–2 builders depending on scope. No account managers, no offshore handoffs. You'll know everyone shipping your work by name.

Ideal starting point, actually. We get to pick the right stack from scratch instead of working around legacy decisions someone else made.

Week 1: audit. Week 2: strategy & roadmap. Weeks 3–6: build, integrate, QA, rollout. Week 7+: monitoring, tuning and the next opportunity. You see working systems by week four.

Most of our clients are non-technical operators. We handle the technical depth; you stay focused on the business. Everything we ship comes with plain-English runbooks and training.

01 Audit & Strategy, 02 Implementation & Automation, 03 Training & Adoption, 04 Continuous AI Development. Every engagement moves through all four — the last one never really ends, because your systems keep improving.

During the audit, a few hours of interviews. During the build, one point of contact giving feedback in short weekly check-ins. We designed the process for operators who have a company to run.

Configure first. Step one of our process is getting full value out of what you already pay for. We only bring in new tools where there's a real gap, and we only build custom agents when no existing tool does the job well.

We re-sequence the roadmap. The opportunity map from the audit makes trade-offs explicit, so changing direction is a conversation, not a crisis. Scope changes are quoted before work starts.

A shared Slack or Teams channel with the builders, weekly written progress notes, and a live dashboard once your systems are running. No weekly status-call theater.

Software that can read, reason and act — not just answer questions. An agent can qualify a lead, update your CRM, draft the follow-up and book the meeting, with a human approving the steps that matter.

Production-ready agents for six departments: sales, customer service, marketing, operations, finance and leadership. Each one is pre-built for the common workflows in that department, then configured to your tools and your rules.

Pre-built agents are proven workflows we install and configure — faster and cheaper. Custom agents are built from scratch for processes that are unique to your business. Our rule: pre-built first, custom only when needed.

Yes — and it should sound like you. We train voice and tone on your real communications, set strict escalation rules, and route anything sensitive to a human. You approve the guardrails before anything goes live.

Capture and qualify inbound leads, enrich contact data, draft personalized outreach, follow up on a cadence, book meetings into your calendar and keep the CRM clean — so your salespeople spend their time selling.

Answering common questions, looking up orders and accounts, triaging and routing tickets, drafting replies for your team, and escalating with full context when a human should take over.

They replace the work your staff shouldn't be doing — data entry, chasing, copy-pasting, first-line triage. The people stay; the busywork goes. Most clients redeploy hours into sales, service and growth.

Scoped permissions, approval gates on consequential actions, test suites before launch, and monitoring after. An agent drafts and recommends by default; it only acts autonomously where you've explicitly allowed it.

That's the default. Agents connect to your CRM, helpdesk, inbox, calendar, spreadsheets and industry software through APIs and integrations. From your team's perspective, the work just starts getting done.

It asks. Every agent has an escalation path — it flags the task, hands over full context, and a human decides. Stuck is a feature, not a failure: silent wrong answers are what we design against.

The operating layer underneath your AI workforce. It's how your agents, automations and data run as one system instead of a pile of disconnected tools — with one dashboard showing what everything is doing.

No. Single workflows run fine on their own. POP OS becomes valuable once you have several agents and automations that need to share context, be monitored and be improved together.

Kernel (the shared context and memory your agents work from), Orchestration (agents and automations coordinated as one workforce), Observability (every action logged, measured and visible), and Evolution (the system improves from real usage).

What every agent did, what it decided, what it cost and what it produced — tasks completed, time saved, escalations, errors. The same visibility you'd expect from any employee, applied to your AI workforce.

You do. Permissions, approval gates and spend limits are set with you during implementation and can be changed anytime. POP OS enforces them — an agent can't exceed its authority.

It's the layer we install and configure as part of your engagement — running in infrastructure you own. There's no separate license fee and no lock-in: if we part ways, it keeps running.

Every task, correction and outcome feeds back into the system. Stage 4 of our process — Continuous AI Development — is exactly this: assess, build, deploy, measure, improve, on repeat.

Yes. It's documented, built on standard tools, and handed over with full access. Your team can extend it, and we train them on it during rollout.

We work across a catalog of 50 tools — CRMs, helpdesks, marketing platforms, calendars, phone systems, accounting, e-commerce, and industry software like property management platforms. If it has an API, we can almost certainly connect it.

Usually, yes. We've integrated property management systems, legal practice software, logistics platforms and more. If there's no API, we use browser automation, file exports or email parsing as a bridge.

No. We recommend what's right for the workflow, at whatever price the vendor charges you directly. Our incentive is your outcome, not a referral fee.

That's the norm, not the exception. Part of the audit is mapping where data lives and how it flows; part of the build is connecting it. Agents are very good at being the glue between systems that don't talk to each other.

Yes — AI voice agents can answer inbound calls, qualify callers, book appointments and route urgent matters, with recordings and transcripts logged to your systems. Human handoff rules are set with you upfront.

Yes. Gmail, Outlook, Google Calendar and Calendly-style schedulers are standard integrations — agents can triage inboxes, draft replies and book meetings inside your existing accounts.

We meet you there. Agents can read, update and reconcile spreadsheets, and over time we help you graduate the critical ones into proper systems — without a big-bang migration.

If we're on a continuous engagement, we fix it — monitoring catches breakage and maintenance is part of stage 4. If the engagement has ended, everything is documented so your team or any developer can maintain it.

Yours. Always. We never train models on your data, never share it, and delete our working copies at the end of the engagement unless you ask us to retain them.

In your infrastructure or in vendor accounts you own (your OpenAI org, your database, your cloud). We don't run anything on AI Pop-owned servers in production.

All of the above, depending on the task. We pick the right model per use case — frontier models for reasoning, smaller fine-tuned ones for routine work. Vendor-agnostic by design.

95% of the time, existing models with strong prompting, retrieval and tool use beat custom training on cost and time-to-value. We only train custom when the data and the use case actually require it.

You do. Full code, prompts, configs and runbooks transfer to your team. No black boxes, no vendor lock-in to us.

We hand it over. We document everything as we build, train your team during rollout, and offer a 30-day transition window at no extra cost. Building a moat against your own team isn't a business model.

NDAs before discovery, least-privilege access during the build, secrets stored in proper vaults (never in code), and working copies of your data deleted at handover. We can also work under your existing security policies and vendor review.

We configure enterprise API tiers with zero-retention and no-training settings wherever available, and we tell you exactly which providers touch which data. For sensitive workflows, we can run models inside your own cloud account.

We design within your compliance requirements and use vendors whose certifications match them. We're not your compliance officer, but we've built in regulated environments and know how to keep auditors happy.

Yes. Every agent has a kill switch and every automation can be paused from the dashboard. Human-in-the-loop controls mean the consequential actions were never fully autonomous in the first place.

It depends on scope — the audit is a fixed fee, and build work is quoted per roadmap phase after the audit, so you always know the price before we start. Book an intro call and we'll give you a straight number for your situation.

The intro call is free. The full AI Audit is a paid, fixed-fee engagement — it's two weeks of senior work with a real deliverable. What you never get is a surprise invoice.

Fixed fee per phase, agreed before work starts. For stage 4 (continuous development), most clients move to a monthly retainer sized to how much improvement work they want shipped.

The first workflow we ship is chosen specifically for fast, measurable payback — usually within the first quarter. The audit's opportunity map includes cost-saving estimates per workflow so you can sanity-check the math before committing.

Two: the AI model usage (billed by the providers to your own accounts, typically modest) and any software subscriptions we recommend. We estimate both in the roadmap so there are no surprises.

No. Phases are contracted one at a time, and retainers are month-to-month. We'd rather keep you with results than with paperwork.

Start with the audit and one high-ROI workflow. AI done right pays for itself; AI done big-bang is how budgets die. We'll tell you honestly if the timing isn't right.

For the right engagement structure, we're open to tying part of our fee to agreed outcomes. It has to be measurable and attributable — that's a conversation for the strategy call.

By involving them early and being honest: the goal is to remove the work they hate, not the people. Stage 3 of our process is entirely about adoption — training, champions, and visible wins in the first weeks.

Role-based sessions for every team touching the new systems, plain-English runbooks, and office hours during rollout. Leadership gets a separate session on reading the dashboard and steering the roadmap.

We design for adoption from day one — the first workflows we ship are ones your team is actively begging for. With that, real usage typically lands within the first two weeks of rollout.

We watch usage in the dashboard and address it directly — usually it means something in the workflow is friction, and we fix the workflow rather than blame the user. Adoption is a design problem, not a discipline problem.

Yes. Every engagement includes handover training: how to monitor, how to adjust prompts and rules, when to escalate to us. The goal is capability, not dependency.

An operator, not necessarily a technologist — someone respected by the team who feels the pain of the current process daily. We help you pick and we equip them.

Yes — and we recommend it. Leadership needs to understand what AI can and can't do, how to read the results, and how to set policy. That's a focused half-day session, or the AI POP Academy for the deep version.

Consequential actions — sending money, contacting a key client, changing a record that matters — require human approval until you decide otherwise. You set the autonomy level per workflow, and you can tighten or loosen it anytime.

A private, three-day intensive where we teach you to build and launch real AI-powered systems — including professional websites — with hands-on guidance. It's 15 hours of one-on-one instruction, not a video course.

$1,950 introductory pricing (standard $2,500). A $975 deposit reserves your seat, and the remaining $975 is due three business days before your first session.

Either at the Pop House in the Dallas / Ft. Worth area or live online — same program, same hours, your choice.

Founders, operators and professionals who want to build with AI themselves — no technical background required. If you can run a business, you can learn this.

A working project you built yourself — for the website track, a live, professional site — plus the skills and templates to keep building. You leave with something real, not a certificate.

It's private — just you (or your small team) and your instructor. That's why spots are limited and why the program adapts to your goals.

No. The entire program is built around AI-assisted building — you direct, the AI executes, and you learn to judge the output. Curiosity matters more than syntax.

Bring a real project idea — a website, a workflow, a business problem. We send a short prep guide after enrollment so day one starts building, not brainstorming.

Yes — small teams can enroll together and build a shared project. It's one of the fastest ways to create internal AI capability. Ask about team seats when you inquire.

Through the inquiry form on the Academy page. We'll confirm dates, format (Pop House or online), and your project focus, then the deposit secures your seat.

Against the numbers from your own audit: hours saved, response times, conversion rates, cost per workflow. Every automation reports into the dashboard, so results are observed, not asserted.

Every engagement is different, and we'd rather show you than quote averages — our case studies walk through real systems we've built, with film of the actual work. What they share: faster response times, hours back per week, and pipelines that don't leak.

The first workflow ships within weeks of the audit and is chosen for fast payback. Compounding results — the kind that change how the business runs — build over the first quarter as more of the roadmap goes live.

We measure it, find out why, and fix it — that's what stage 4 is for. If something genuinely isn't viable, we say so and redirect the effort. Everything is visible in the dashboard, so underperformance can't hide.

We guarantee the work: the systems ship, they do what the spec says, and we fix what doesn't perform. Anyone guaranteeing exact revenue numbers before seeing your data is selling you something.

The dashboard exports the numbers that matter — hours, costs, throughput, conversion. We also help you frame the AI roadmap as a strategic asset, which boards increasingly ask about.

Lead capture and follow-up. It's fast to build, immediately measurable, and the leak is usually bigger than anyone expected. Second most common: customer service triage.

By starting with the audit instead of the technology. Most failed AI projects started with a tool looking for a problem. We start with your P&L, find where time and money leak, and only then pick the tool.

Typically founder-led and growth-stage companies — big enough to have real workflows, small enough to move fast. If you have a team, tools and a P&L, we can probably help.

We're industry-agnostic but workflow-specific — sales, service, marketing, ops, finance and leadership exist everywhere. Our case studies span energy, real estate and enterprise suppliers, and the audit adapts to any sector.

Especially for you. The biggest AI gains right now are in traditional businesses — real estate, services, logistics, energy — where the competition hasn't moved yet. Non-technical teams are our norm.

Yes, usually starting with one division or workflow as a proving ground. Enterprise security reviews, procurement and SSO are familiar territory — expect the audit to include your IT stakeholders.

Selectively. The fit has to be right: you need enough process volume for automation to pay back. For very early teams, the Academy is often the better starting point.

Great — they become our favorite collaborators. We handle the AI layer and hand over clean, documented systems they'll be happy to own. We make internal teams look good, not redundant.

Book a free intro call. Thirty minutes: you tell us where the business hurts, we tell you honestly whether AI can fix it and what the audit would look like for your company.

No pitch deck. We ask about your workflows, your tools and your goals; you ask us anything on this page. If there's a fit, we scope the audit. If there isn't, we say so and point you somewhere useful.

Audits typically kick off within two weeks of signing, depending on scheduling the interviews. If you have a burning problem, tell us — we've started faster.

Nothing formal. It helps to know your rough team size, your main tools (CRM, support, ops), and the one process that frustrates you most. That last one is usually where we start.