From outside-in audit to a live workflow
A Meo engagement has seven steps. It starts with a free outside-in audit built from public information, and the first workflow typically goes live 8 to 16 weeks after you sign. Each step ends with your sign-off, and if a step fails its check, that work goes back to today's process. The week ranges below are planning ranges drawn from our own delivery work. Your proposal sets your dates.
Why many AI projects stall
Buyers have reason to be wary. MIT NANDA's 2025 report found that about 95% of enterprise generative AI pilots delivered little or no measurable impact on profit and loss (Fortune, 2025). Its authors note the findings are self-reported and correlational (Let's Data Science, 2025). Gartner predicted in 2025 that over 40% of agentic AI projects will be canceled by the end of 2027, citing cost, unclear business value and weak risk controls (Gartner, 2025).
The steps below answer those failure modes in order: find a real problem first, agree how success is counted before building, test with your staff, and go live in small steps you can reverse.
1. Free outside-in audit
Our people, working with our agents, review your business from public information: your website, phone readiness, booking paths, map listings, reviews, paid search, tracking and consent, and how AI assistants describe you. We score ten or more areas and attach evidence to each finding, such as a dated source, a screenshot or a measured value. Independent checks review every finding before it reaches you.
The audit ends with a list of what the outside view could not see, and for each item, the record that would settle it, for example 90 days of call logs. You share no data. You get a first reply within 24 hours and the audit typically within a week (Meo Advisors, 2026).
An offer: a working prototype
You can ask for a working prototype. With your agreement, we can rebuild one of your workflows from public information and test calls made by our own people, then walk you through it before you decide. You still share no data.
2. Findings and proposal
About a week later you get a proposal: scope, phases with sign-off gates, cost ranges per phase, the run cost next to what you spend on the same work today, and what is excluded. Ranges stay ranges until your own data firms them up. How fees are structured is on our pricing page.
3. Discovery with your engineer
Discovery takes about four weeks. A forward-deployed engineer, a role on our side, leads it, and the engineer who maps your process is the one who builds it. A design group from your team meets with them weekly. They walk through live work with a daily user, read 90 days of call or request logs exported under your data agreements, and map every hand-off into your EHR and CRM.
The output is a map of today's process, a written playbook that your team signs, and an integration plan. The playbook holds your rules: scripts, escalation contacts, and what agents may and may not do.
4. Baseline and targets
Inside discovery, we agree a scorecard with you. Each row has a counting rule, a data source, a dated baseline, a day-90 target, a month-12 target and an owner who accepts it. Where a baseline is unknown, it stays marked unknown until data exists; we do not fill it with an estimate. The comparison design is set here too: work handled by agents against today's process, and pilot sites against matched sites where you have them.
5. Build and test
Build and test typically takes four to six weeks. Access to your systems often takes five to nine weeks to arrange, so we request it in the first weeks and it runs in parallel. Your staff listen to and score test calls built from real scenarios before any patient hears one. Every build includes a way to switch back.
6. Pilot and staged rollout
The first workflow typically goes live 8 to 16 weeks after you sign (Meo Advisors, 2026). We start where the risk is lowest, for example after-hours calls, and run a pilot of about six weeks with weekly reviews of transcripts, errors and outcomes. At the end comes a go or no-go decision against the baseline. Rollout then follows in waves, each after your sign-off. A no-go returns that work to today's process while other tracks continue.
7. Run, monitor, improve
Monitoring is part of the build. Scheduled routines watch what was built and alert a named owner on your side when something drifts. They typically run in shadow for 14 days before they go live. You get a runbook and a monthly scorecard update. Who operates the system after go-live, and on what terms, is set in your proposal. The human review page covers monitoring in detail.
The forward-deployed engineer, and the lock-in question
Forward-deployed engineers have become common across the AI industry, and so has a worry about them. Tomasz Tunguz asks whether this spending is "a moat or a toll booth": once engineers build custom workflows on one AI vendor's interfaces, switching vendors can mean rebuilding (Tunguz, 2026). A widely reported healthcare example is England's NHS Federated Data Platform, where the National Data Guardian raised concerns about vendor lock-in (The Register, 2023).
Our answer is in how the work is built. Agents can run in your environment and connect to the systems you keep. Each step needs your sign-off, and any line can switch back to today's process. Models are compared on our benchmark, using our published testing method, so the choice of model is a decision you can see. Ask for the ownership and exit terms in your proposal. For how Meo compares with other ways to get this work done, see why Meo. For where agents run and which agreements cover them, see your systems and agreements.