AI Workflow Automation is Right.Link's service for putting AI agents and automations to work inside the systems your team already uses: CRM, ERP, helpdesk, email and back-office tools. We pick one repetitive, well-understood process, automate the part that is safe to automate, keep a person in the loop where mistakes are expensive, and measure the result on real examples before we widen the scope. It is built for companies that already run on these systems and want less manual handling, not a new platform.
Who is AI Workflow Automation for?
It is for teams where skilled people spend part of every day moving information between systems: reading an email, finding the customer in the CRM, checking the ERP, typing the result somewhere else.
Typically that means an operations lead, a head of support or a founder at a company with a working stack and a process that has grown by hand. You do not need a data team. You need a process you can describe and someone who can tell us what a correct result looks like.
If you have an AI product idea and no users yet, you probably want a prototype, which is what AI Development is for. If you want to add an AI feature inside your own software product, see AI Integration for Existing Products.
Which processes are good candidates?
The best candidates share three traits: they repeat often, the input is messy or unstructured, and a person can check the output quickly.
- Inbound requests: triage and routing of emails, forms and support tickets, with a drafted reply for a person to approve.
- Documents: reading requests for quotation, invoices, orders or contracts and turning them into structured records.
- CRM hygiene: updating records after calls and emails, logging next steps, flagging stale deals.
- Back-office handoffs: moving data between the CRM, ERP, spreadsheets and email without retyping it.
- Reporting: collecting figures from several tools into a regular summary a person can read.
- Internal questions: answering "where is this order?" or "what did we agree with this client?" from your own records.
Poor candidates: processes nobody can describe, and decisions where a wrong answer is costly and cannot be reviewed. We will tell you when a process is not ready.
Do I need an AI agent, or a plain automation?
Often a plain automation is the right answer. If the rule is clear ("when X happens, do Y"), ordinary code is cheaper, faster and easier to test than a language model.
We use a language model where the input is unstructured, such as free-text emails, scanned documents or loosely worded requests, and where judgement-like steps are needed: classify this, extract these fields, draft this answer. Around the model we keep ordinary, deterministic code for the parts that must always behave the same way, such as calculations, permissions and writes to your systems.
An agent that decides its own next steps is useful when the path really varies from case to case. We add that freedom only where it is needed, and with limits on what the agent is allowed to do.
How does Right.Link build an automation?
We work in small steps, because a narrow automation that works is worth more than a broad one that nobody trusts.
- Map the process. We follow the work as it is really done: inputs, systems, exceptions, who decides. You get a short written map with the steps ranked by value and risk.
- Choose one slice. One process, one input type, one clear definition of a correct result.
- Build the integration. We connect to your systems through their APIs, webhooks or supported connectors, and handle failures, retries and duplicates.
- Add the AI step where it earns its place. Classification, extraction or drafting, with structured outputs that the rest of the flow can check.
- Put a person in the loop. Approval queues for anything that sends, pays, deletes or edits customer data. Approvals can be relaxed later, with evidence.
- Test on your real cases. We build a test set from past examples and check results before launch and after every change.
- Launch, observe, widen. Logs, alerts and a review of what the automation got wrong. Then the next slice.
Which systems can it connect to?
We connect to what you have. Typical examples are CRMs, ERP and accounting systems, helpdesks, email and calendars (including Microsoft 365 and Google Workspace), databases, spreadsheets and team chat.
What matters is whether the system has a usable API or export. We check that early, before we promise anything. If a system has no API, we say so and discuss the options.
How do you keep people in control?
An automation that acts on your customers or your money needs limits. These are our defaults:
- Approval before side effects. Anything that sends a message, moves money or changes a customer record waits for a person, until you decide otherwise.
- Narrow permissions. The automation gets only the access its job needs.
- A full trail. Every action is logged with its input, output and the reason, so you can answer "why did it do that?".
- An off switch. One place to pause the automation without a deploy.
- A safe fallback. When the model is unsure or a system is down, the case goes to a person instead of being guessed.
What do you get at the end?
- A written map of the process and the decisions we made about what to automate.
- Working automations or agents, running in your environment or ours, as agreed.
- Integrations with your systems, with error handling and retries.
- Approval queues and an audit log.
- A test set from your real cases, and a way to re-run it.
- Documentation and a walkthrough for your team, or a sprint plan if we continue together.
What will Right.Link not do?
- We will not automate a step we cannot test. If we cannot define a correct result, we do not ship it.
- We will not give an agent broad access "to be safe". Access is limited to the agreed job.
- We will not promise savings in advance. We describe what will change in the process and measure it after launch.
- We will not send messages, move money or edit records on your behalf without the approval rules you have agreed.
Has Right.Link done this before?
Yes. Two projects that automated real business processes with AI:
- Microsoft 365 Quotation Automation Platform: an AI-powered quotation solution integrated into Microsoft 365. It processes incoming requests for quotation from Outlook, retrieves pricing from supplier price lists, calculates costs and generates quotations for review in Excel.
- Marketing Automation: an AI-powered platform for premium hotels in Japan that generates monthly social media content plans and publishes posts automatically.
Each case page describes the project in more detail.
Book a free 30-minute intro call
If this sounds like your situation, Book a free 30-minute intro call. Bring a short description of the process or product and what goes wrong today. You will leave with an honest view of whether we can help and what a sensible first step would be. The quote comes after the call and depends on what is needed.