How OPC Journey helps customers put AI to work

What does OPC Journey do for a customer?

We take one painful, repeating process and make AI run it inside the business you already have. That means your spreadsheets, your inbox, your CRM, your support desk and the steps that currently live in someone's head.

The person accountable is one named forward deployed engineer, not a rotating agency pod and not a chatbot subscription. They bring an agent fleet and the infrastructure to run it. They also answer for the result: what shipped, what it saved, and what broke.

Who is this for?

Small and medium businesses that already feel the mess: data in too many places, staff working around the new AI tools, and nobody owning it when an agent is wrong. We work with companies in the US, UK, Australia, Singapore and similar markets. Our engineers are based in Asia, and we agree a daily overlap with your working hours at kickoff.

You do not need a data team or a clean warehouse first. Mapping the mess is week one. We also work with IT providers, accountants and consultants: you keep the client relationship, and we do the build, the monitoring and the weekly reporting, through a referral or under your brand.

What does the engineer actually do?

Six jobs, in this order:

1. Map where the data really lives, and which workflows cost the most time.
2. Clean and connect the tools you already use, so the agent works from one source of truth.
3. Automate the repetitive spine: onboarding, quoting, invoicing, support triage, reporting and similar work, with approval gates.
4. Train the staff who will use, trust and approve the system. Adoption is part of the job.
5. Measure against a week-one baseline and 3 to 5 agreed KPIs. The weekly report says what ran, what it saved, and what is next.
6. Own the repair. When an agent gets something wrong, the engineer fixes it. Monitoring and the next automation are part of every month on Autopilot.

How does a project run?

Every client follows the same four stages.

1. Route mapping. We log each recurring process, where its data lives, who touches it, how long it takes and what it costs. You get a baseline and an automation map ranked by payback.
2. Ignition, in week one. The highest payback, lowest risk automation ships end to end. Something real is running in the business.
3. Autopilot, across the following weeks. Process by process, recurring work moves to agents with monitoring, alerts and human approval. The team is trained to work alongside them. Most clients reach this stage within six weeks.
4. Compounding. Each month the engineer fixes what broke, improves the KPIs and automates the next process. The system gets better instead of drifting.

The first automation is typically live in production within five working days of kickoff. Outside the overlap window, the agents keep running, so the work is on the board when your day starts.

What does it cost?

Three ways to start. Prices are in USD.

• Ignition, $4,900, one time, two weeks. A map of your data, tools and workflows. One painful process automated end to end. A week-one baseline and agreed KPIs. Handover docs and code you own.
• Autopilot, $3,990 per month. A dedicated engineer, part time. Agents monitored, fixed and improved. The next process automated every month. Staff training and 30 day reviews. A weekly KPI report and a live board. AI usage at cost, capped at your budget.
• Full OPC, custom. A full-time engineer embedded with you, with company-wide ownership of AI results, custom infrastructure, and a direct line on your hours and your stack.

There is no recruiting fee and no long lock-in. You can cancel at the end of any month. The full comparison is on the pricing section.

Will this replace our staff?

No. The point is to take repetitive work off their plate so they can focus on customers and decisions. The engineer needs the team's knowledge to build something that holds up, so staff are part of the rollout and get trained to run alongside the agents.

Anything that moves money, contacts a customer, deletes data or changes production needs a human approval first. Every agent run is logged. A sample of the work is reviewed each week, and the error rate is in the weekly report.

Who owns the code, the data and the accounts?

You do, from day one. Work is built in your repositories, your cloud accounts and your tools. If we part ways, you keep a documented system that is still running.

Your data stays in your own accounts. The engineer and each agent get separate, limited access that you can revoke. We sign an NDA and a data processing agreement before any access is granted.

How do you see the work day to day?

We set up a Monday.com board as the single source of truth, even if you have never used Monday. The engineer works on that board, and the agents write to it, so you can see status, outputs and cost without asking for an update.

What should you do next?

If you have one process that already hurts, start there. A fit call is enough to tell whether Ignition is the right first step. Founders who want Claude API credits before they build can also read how to apply to the Claude for Startups program. Credits help only after someone connects the model to the work your company already does.