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Custom AI Agents AI Knowledge Assistant Custom Software & Apps Private AI Infrastructure All services →Workflow automation from Seqora takes the rule-based work your team repeats every day, like copying web forms into the CRM, sending reminders, routing requests and chasing overdue invoices, and runs it on its own. If a rule fits in one sentence, it becomes a workflow that runs the same way every time, with no per-run AI fee and nothing made up. When the real problem is that nobody can see the number, we build a live dashboard and a workflow that keeps it current. AI only comes in where the input is messy, like a scanned form or a free-text email, and we'll tell you when it isn't needed.
Workflow automation is software that carries out a repeatable business process on its own, following rules you can write in one sentence: when this happens, do that. It moves data between your apps, sends reminders, routes requests and raises alerts without anyone clicking. Paired with a live dashboard, it also puts the numbers your team keeps asking about on one screen, always current.
Copying a web form into the CRM, texting a reminder the day before, moving a file into the right folder, opening a spreadsheet every morning to see what's overdue. Each takes a few minutes, so nobody fixes it, and together they quietly fill someone's week.
The reflex now is to throw AI at all of it, and for most of this work that's the wrong tool. A language model costs money on every run, can answer differently on the same input, and can make things up, while a rule like "when an invoice passes 30 days, send the reminder" needs none of that. We explain the full test in our post on where AI actually belongs.
The other half of the problem is visibility. If someone gets asked the same question every week, such as how many consults were booked or which files are stuck, the fix is a screen that answers it, kept current by a workflow.
If it can be an if statement, make it an if statement. A plain workflow runs in milliseconds, pays no AI model fee per run, and never makes things up. We save AI for steps that need reading, like a scanned referral or a rambling email.
Cases completed in one production day by the scheduled, priority-ordered AI validation process we built for 100 Boulevard
100 Boulevard · Aug 2026
To select 20 cases in priority order and complete every one of them
100 Boulevard · first production week
Automated tests backing that same production process
100 Boulevard · Oct 2026
Most engagements combine several of these. The audit decides which ones pay back first.
Jobs that run on a timer or fire the moment something happens: a form arrives, a deal changes stage, an email lands, a file is uploaded. Same steps, same order, every time.
Appointment and payment reminders, overdue nudges, and requests routed to the right person by type, location or value, with a fallback when nobody picks them up.
Records kept in step across Google Sheets, HubSpot or Salesforce, your calendar and your database. Rows are matched on email or record ID with duplicate checks, so a new lead or booking is entered once, not three times.
When a portal or older system has no API, we automate the steps in a real browser, queue the work, retry failures and record each result in your sheet or database.
Pages, inboxes, feeds or figures checked on a schedule and compared with the last snapshot. When a value crosses a threshold you set, the right person gets one alert, not twenty.
Data pulled on a schedule from your CRM, Google Sheets, forms and database, de-duplicated and joined in a Supabase or Postgres database, then shown on one screen with trend lines, threshold flags and weekly CSV or PDF exports. It refreshes without anyone touching it.
A dashboard is only useful if it stays current without anyone updating it. Behind every screen we build, workflows do the unglamorous part.
Illustrative example · sample data
Every rule is written down and signed off before anything is built, so you know exactly what each workflow will do.
We sit with the people doing the work and list every repeated task: who does it, how often, and which apps it touches. Each one gets sorted into a rule, a dashboard, an AI step, or not worth automating.
Each workflow gets a written spec in plain English: the trigger, the conditions, the actions, and what happens when something fails. You approve it before we build.
We build in custom Python and Node workers, with Playwright where a system has no API, sized to your volume and budget. Scheduled jobs can run in your own cloud account, as our 100 Boulevard process does. Workflows are tested against past records, or realistic samples where data is sensitive, before they touch live work, and dashboards are wired to the same sources.
Workflows go live with logging, retries and alerts switched on while your team watches the results. Edge cases get fixed as they show up, not months later.
Workflows run in your own cloud account or on hosted workers, whichever we agreed at scoping, and either way you get the code and a short runbook for each workflow. We can stay on to monitor runs and add new automations as the business changes.
Both systems work through a queue of jobs, retry or explain what they can't finish, and record every result. The 100 Boulevard process runs on a schedule in production. The other was handed over as a self-contained app, and that client asked to stay anonymous, so the name is left out.
An AI step reads each proof document. Around it, a scheduled process picks up flagged cases in priority order, checks each amount against a tolerance, updates the record, explains anything it can't verify in plain language and moves the case to its next stage.
Zero extraction errors across the first 30 production cases, and 576 cases completed in a single production day.
A long, multi-step web process run across several browser sessions at once. A self-recovering queue retries failures on an escalating schedule, resumes interrupted runs and syncs every result to the team's spreadsheet, while companion services check pages on a schedule and send threshold alerts.
Packaged as a self-contained desktop app and handed over through five builds with operator and developer guides.
Every task is sorted into a rule, a dashboard or an AI step before we build. Plain rules are cheaper to run and easier to audit, so they're the default.
Escalating retries, resume after an interruption, and alerts that fire once with a cooldown. That's how we built a browser-automation engine and its companion monitoring services for a private client.
The code is yours wherever the workflows run, in your own cloud account or on hosted workers. Our browser-automation project was handed over as a self-contained app with operator and developer guides.
Many of our systems mix the two: rules for the routing, and an AI step only where a document or message needs reading. If the work needs judgment, see custom AI agents.
| Compare | Done by hand | Seqora Workflow Automation |
|---|---|---|
| When it happens | When someone gets to it | The moment the trigger fires or the schedule runs |
| Consistency | Depends on who did it and how busy they were | Same input, same result, every time |
| Cost per run | Staff time, every time | No AI model fee per run. The ongoing cost is mostly hosting |
| When it goes wrong | Noticed later, if at all | Retried, logged and flagged to a person with the reason |
| Seeing the numbers | Someone opens a spreadsheet and counts | A live dashboard kept current by the same workflows |
Recall and hygiene reminders, insurance verification checklists, and a dashboard of booked, confirmed and open chairs that updates itself.
DentalNo-show prevention with confirmation and reminder texts, review requests after each visit, and a live bookings dashboard by treatment and provider.
Med spaDeadline tracking with escalating alerts, scheduled lien and records-request follow-up, and a live case-intake dashboard by source and stage.
PI lawMost workflow projects are a fixed-scope build, quoted after the free audit, with optional monthly monitoring. These are the things that move the number:
What it costs to run: a plain workflow pays no AI model fee per run. Your ongoing bill is mostly hosting, in your own cloud account or on a small server, plus any paid API plans your apps require, and we estimate it before you commit.
The ones your team repeats most often across the most apps. On the free audit we list every repeated task, who does it and how often, then sort each one into a workflow, a dashboard, an AI step or not worth automating. A rule you can write in one sentence, like texting the on-call number when a form arrives after hours, becomes a workflow. Reading a scanned referral goes to an AI step such as AI document processing.
It depends mostly on how many workflows you need, how many apps they touch, and whether those apps have APIs. Most projects are a fixed-scope build quoted after the free audit, with optional monthly monitoring. Running costs stay low because rule-based steps don't pay for an AI model on every run, so the ongoing bill is mainly hosting plus any paid API plans your apps require.
A single workflow between two apps with APIs can be scoped at one to two weeks, including testing before it goes live. A set of workflows plus a dashboard is usually scoped at four to six weeks. From you we need admin access to the apps involved, an hour with the people doing the work, and someone to approve each rule before we build it.
Usually, yes. Most CRMs, calendars, inboxes, spreadsheets and accounting tools have APIs we can connect directly. When a portal or older system has none, we automate the steps in a real browser instead, with a queue, retries and a log of every result. We've built this kind of engine for a private client, syncing results to their reporting spreadsheet.
It retries, then it tells someone. Every workflow we build is designed to log each run, retry temporary failures on a schedule, and send one alert to the right person when it can't finish, with the record and the reason attached. It's built so nothing fails silently. If an app changes its API or a page changes its layout, the alert shows which step broke.
You own them. Workflows run in your own accounts or cloud, the code and configuration are yours, and each one ships with a runbook. Workflows are built so each connection gets only the access it needs and credentials are kept out of the workflow itself, and data is encrypted in transit and at rest. When a workflow touches patient data, we sign a BAA.
Further reading: AI agent, workflow, or dashboard: how to decide where AI actually belongs · Things you're still doing by hand (and what it's costing you)
Book a free call. We'll walk through the tasks your team repeats, sort each one into a workflow, a dashboard or an AI step, and show you which to automate first.