Everything people ask before the call

Fourteen questions we hear from founders and operators sizing up AI and automation work — answered the way we'd answer them on the call, minus the scheduling.

Working with us

What does the discovery call look like?

Thirty minutes. We talk about where your team is spending time, which workflows you suspect are broken, and what success would look like in 90 days. No pitch deck, no obligation. By the end you will either have a clear next step with us, or two or three things worth trying on your own. Both count as wins.

How is this different from hiring an agency?

Agencies sell hours and handoffs. Oodaloli is operator-led: the person who scopes the work is the person who builds it, sits with your team, and stays accountable for the outcome. No junior delivery team, no offshore handoff, no context lost between the sales call and the build. The honest tradeoff is capacity — we take on a small number of engagements at a time, and we will tell you early if something is not a fit.

What if we already have a dev team?

That usually makes things faster, not slower. Your engineers keep building the product; we take the operational automation work that never makes it off their backlog — lead routing, reporting, internal tools, agent workflows. We work in your repos and your tooling, document everything, and hand off in a form your team can own. Some clients use a 2-week Sprint purely as a scoping exercise and have their own team do the build. That is a fine outcome.

How involved does our team need to be?

More at the start than in the middle. The first week of any engagement is observation, so we need a few hours with the people who actually do the work — watching real examples, not reading process docs. After that it drops to a weekly check-in, plus a review of anything customer-facing before it goes live. We would rather borrow 4 focused hours in week 1 than 20 scattered ones later.

How do you decide what to automate first?

Leverage over novelty. We score candidate workflows on four things: hours reclaimed, adoption risk, data access, and whether a human needs to review the output. The first build is usually the boring one — a report nobody wants to compile, a follow-up nobody remembers to send — because boring wins ship fast, prove the loop works, and fund the more interesting ones.

The technology

What stack do you work with?

Yours. We meet you where you are: HubSpot, Salesforce, Pipedrive, ClickUp, Asana, Notion, Slack, the Google or Microsoft suites, whatever ESP you are on, plus the modern AI and automation layer — Claude, OpenAI, Zapier, Make, n8n, Airtable, Retool, Vercel. The goal is fewer tools you actually use well, not new tools we happen to like. We do not resell a platform, so there is no tool we are incentivized to push.

Do we need to already be using AI tools?

No. Most clients start with a CRM, a shared inbox, and spreadsheets — that is plenty. If your team is already using ChatGPT or Claude day to day, we build on that habit; if not, we introduce only what the specific workflow needs and train the people who will touch it. Starting from zero often goes smoother than untangling six half-adopted tools.

What happens when something breaks after handoff?

Every Project includes 30 days of post-ship support, and everything we build ships with documentation and runbooks written for your team, not for us. We also build alerting into anything that runs on its own, so a failure shows up in your Slack or inbox instead of failing silently for a month. After the support window you have three options: fix it yourselves using the runbook, bring us back for a short fix, or move to an Embedded retainer if there is a steady stream of this work.

Data, security, and control

Do you sign NDAs and work with sensitive data?

Yes. Mutual NDA before the discovery call if you want one, standard MSA for paid work. We treat your data as your data: work happens in your environment whenever practical, with least-privilege access, proper secrets management, and audit trails on anything that acts autonomously. If a workflow touches customer data, it gets a human approval gate by default.

Do you use our data to train models?

No. Your data is used to run your workflows and nothing else. We build on commercial API tiers that do not train on your inputs, and we configure vendor data-retention settings as part of setup rather than leaving defaults in place. Nothing from your business ends up in a model, a template, or another client's build.

Who owns what you build?

You do. Code, workflows, prompts, integrations, documentation — all of it lives in your accounts and your repos, and ownership is fully yours. There is no proprietary platform underneath and no license that expires when the engagement ends. Part of every handoff is documentation written so you could fire us and keep everything running. We would rather earn the next engagement than lock you into this one.

Pricing and engagement

How fast can you actually ship?

For a Sprint, one working automation is in production within the 2-week window — that is the point of the format. For a Project, the first working version usually appears in the first 2 weeks, with full delivery in 6 to 12 weeks depending on scope, access, and review needs. We keep discovery close to the work instead of burying it in a long deck.

What kind of ROI should we expect?

The honest answer is that it depends on what is broken. We look for workflows where labor savings, fewer handoffs, or faster decisions can justify the work with numbers we can defend — not a slide of adjectives. The Sprint exists precisely so you get a defensible ROI estimate, based on your data, before committing to anything larger.

How does pricing work?

Sprints are fixed scope and fixed fee — you know the number before work starts. Projects are milestone-based with custom scope, set after a Sprint or a discovery call. Embedded is a monthly retainer you can pause, scale, or end with 30 days notice. All pricing is scoped on the call once we have seen your stack. We do not quote blind, and we do not do open-ended hourly billing.

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