Rowvyn

    Workflow Automation & AI

    Give repetitive work a reliable workflow.

    Connect the handoffs, reporting, and repeated tasks that take your team away from useful work. Rowvyn uses rules, integrations, and practical AI where they fit the job.

    Start with one recurring task, its exceptions, and the person responsible for it. A useful automation also explains what happens when something goes wrong.

    Connected
    to the existing tools in the workflow
    Reviewable
    clear checks and approval boundaries
    Observable
    success, failure, and recovery made visible

    The operating problem

    What starts breaking first.

    Recurring admin work can be a good starting point when the inputs, desired result, exceptions, and responsible owner are understood.

    The same data is copied between tools every day

    Status checks and handoffs happen through repeated messages

    Reporting depends on somebody remembering to run it

    An AI experiment needs reliable data and a controlled scope

    The build

    What Rowvyn puts in its place.

    Some tasks need a simple rule or integration. Others benefit from AI-assisted interpretation. We choose the approach around reliability, access, and the consequence of an error.

    Scheduled data movement, reporting, and operational alerts

    Connections that trigger the next step from a defined business event

    AI assistants that retrieve and summarize authorized business information

    Review, failure handling, and documentation matched to the workflow

    The process

    A practical build, in the right order.

    The sequence is simple on purpose. We inspect the operation, choose the highest-leverage move, ship it, and make sure the team can use it.

    1. 01

      Choose one workflow

      Map the trigger, inputs, desired output, frequency, and current manual effort.

    2. 02

      Set boundaries

      Define access, exceptions, review points, and actions that must remain with a person.

    3. 03

      Build and exercise

      Connect the workflow and check both expected results and realistic failures.

    4. 04

      Hand over the controls

      Make status and recovery visible, document maintenance, and agree ongoing support.

    Proof from the field

    Rowvyn's open-source ServiceTitan MCP gives compatible assistants 264 read-only tools by default. It demonstrates controlled access to operating data; customer-contact automation remains a separate scoped workflow.

    Review the ServiceTitan MCP project
    264
    read-only tools in the default surface
    15 domains
    of operating data
    Explicit opt-in
    for experimental mutation tools

    Before we start

    A clear scope, from the first conversation.

    These are the questions worth settling before a project becomes a build.

    Read a practical starting guideUnderstand ownership and running costsExplore business applications
    What happens before a build starts?

    We inspect the workflow, the people using it, and the available systems. If custom work is a fit, the proposal sets out deliverables, boundaries, acceptance checks, estimate, timeline assumptions, and responsibilities.

    Can you work with the software we already use?

    Often, yes. We check the specific tools, account permissions, APIs or exports, and data quality before committing to an integration. Sometimes configuration or an existing product is the useful first step.

    What changes the cost and timeline?

    The number of workflows, integrations, users, exceptions, and access constraints all matter. Data cleanup, review requirements, and the agreed support/handoff also affect scope. We estimate the actual job rather than publish a generic delivery promise.

    Who owns the code, accounts, and data?

    The project agreement defines client-specific code, existing components, account control, and data ownership. Third-party services retain their own terms. The handoff should make the dependencies and access responsibilities clear.

    What does it cost to keep the result running?

    Hosting, storage, provider usage, maintenance, and support can remain ongoing costs. The proposal separates the build from operating assumptions and any agreed support. Owning a tool gives you control over those decisions.

    How do you handle business data and AI access?

    We define which data the task needs, who can authorize access, and which providers are appropriate for the project. Review and approval boundaries depend on the sensitivity of the information and the consequence of an incorrect result.

    What happens after launch?

    Documentation, operating responsibilities, training, and any maintenance or support are defined in the scope. Your team should know how the system runs, what its limitations are, and who handles an exception.

    Start with the bottleneck

    Let's figure out what you actually need.

    Start with one task your team repeats. We'll check whether an integration, a simple rule, or an AI-supported workflow makes sense.

    Talk through a repetitive taskReview the case studies