SYS.ONLINEAIPOP // FAQ
FAQ // FREQUENTLY ASKED

Questions, answered.

Everything founders ask before working with us — the audit, the engagement, what it costs, and what happens to your data.

[01]

THE AUDIT

How long does an AI Audit take?

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.

What access do you need from us?

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.

Do we need a data team or technical staff?

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.

What do we actually receive at the end?

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.

Is the audit remote or on-site?

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.

Do you sign an NDA?

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

[02]

ENGAGEMENT & PROCESS

How long from audit to first deployment?

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.

Who do we work with on your side?

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.

What if we have no AI tools in place yet?

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

What does the typical 6–8 week engagement look like?

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.

Do you work with non-technical teams?

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.

[03]

PRICING & COMMERCIALS

Why isn't pricing listed on the site?

Because the honest answer depends on scope. A single-workflow build is very different from a full ops overhaul. We quote fixed fees after a 30-minute call so there are no surprises.

How do you scope projects?

Fixed-fee per phase. Audit is a flat rate. Build phases are scoped against the roadmap with a clear deliverable and a clear price. No hourly billing, no scope creep clauses.

Do you do retainers?

Yes — for clients post-build who want ongoing optimization, new agent rollouts, or a fractional AI team. Monthly, cancel with 30 days notice.

What's the typical investment range?

Audits start in the low five figures. Build engagements range from mid-five to low-six figures depending on scope. Most clients see payback inside the first quarter post-deployment.

What's your guarantee?

If the audit doesn't surface at least 3x its cost in identified savings or revenue, we refund it. For builds, we don't invoice the final milestone until the system is in production and hitting its agreed metric.

[04]

TECH, SECURITY & OWNERSHIP

Whose data is 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.

Where does the data live?

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.

Do you use OpenAI, Anthropic, Gemini, or something custom?

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.

Do you build custom models or use existing ones?

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.

Who owns the agents and automations you build?

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

What happens if we want to take it in-house later?

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.

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