AI workflow automation and integrations
Your tools, working as one system.
We automate the processes that repeat every day: a form comes in, a document arrives, a deal closes. The work moves between the software you already use, with AI doing the reading, sorting, and drafting, and a person approving what matters.
In practice
Practical automations, start to finish.
Illustrative examples of the processes we automate. Each step names a kind of tool rather than a product, because yours will differ.
When A new lead fills out your website form
- Look up the company
- Add the contact to your CRM
- Draft a reply in your tone
Result: A logged lead and a reply waiting for your OK
When A supplier emails an invoice PDF
- Read the invoice
- Match it to the purchase order
- Create a draft bill
Result: A draft bill to approve, with any mismatch flagged
When A client signs your proposal
- Create the project
- Send the welcome email
- Book the kickoff
- Draft the first invoice
Result: A new client set up without retyping anything
When Every Monday morning
- Pull last week’s sales
- Pull open invoices
- Summarize what changed
Result: One summary in your team channel before the first meeting
When A meeting ends
- Get the transcript
- Write the notes
- Create tasks
- Draft the follow-up
Result: Notes, assigned tasks, and a follow-up ready to send
Who it’s for
For processes that already have a pattern.
Operations-heavy businesses
Orders, invoices, scheduling, and intake that follow the same steps every time.
Teams living in many tools
A CRM, an accounting system, email, and shared drives that don’t talk to each other.
Document-heavy work
PDFs, forms, and attachments that someone reads and retypes into another system.
Technical owners
You want automations built properly, with error handling, logs, and documentation you can maintain.
- Someone copies the same data between two systems every day.
- Leads wait hours for a first reply.
- Month-end means a week of pulling reports by hand.
- An old automation breaks quietly, and nobody notices for days.
- Your software has an API, and nobody has had time to use it.
Supported or custom
How we connect your systems.
Most connections use something that already exists. When nothing does, we build it. We confirm which kind each connection needs during scoping, before we commit to it.
Built-in connectors
Integrations an automation platform or AI tool already offers for common software.
- When we use it
- Your tools are widely used and the connector covers what you need.
- What to expect
- Quickest to set up and maintained by the platform; limited to what the connector exposes.
Existing APIs
Your software’s own programming interface, called directly from the workflow.
- When we use it
- A built-in connector is missing an action or a field you need.
- What to expect
- More flexible; depends on what the vendor’s API allows on your plan.
MCP integrations
Model Context Protocol servers that let AI tools such as Claude use your systems, with defined permissions.
- When we use it
- You want an assistant or agent to look things up or take actions in your systems when asked.
- What to expect
- An existing MCP server where a good one exists; otherwise we build one on the system’s API.
Custom connectors
A connector we build when nothing usable exists, such as for an older system or an internal database.
- When we use it
- There’s no connector or usable API, or the data needs reshaping first.
- What to expect
- Scoped separately, documented, and maintained under a support agreement.
What you get
What we build and hand over.
Process maps
The process as it runs today and as it will run automated, with every step and owner.
Working automations
Built in your automation platform or as code, and connected to your systems.
Document processing
AI that reads invoices, forms, contracts, or emails and pulls out the fields you need.
Scheduled workflows
Jobs that run daily, weekly, or when something happens, without anyone starting them.
Error handling and alerts
Retries for temporary failures, alerts to a named person, and one place to see what failed and why.
Run logs and documentation
A record of what ran and what it did, plus docs your team or a future developer can follow.
For technical buyers
Under the hood.
For the people who’ll own these systems after we hand them over.
- Platforms
- Automation platforms you already use or we recommend, scripts, and AI platforms with tool use. We choose per process.
- Triggers
- Webhooks, schedules, new records, incoming email, file drops, or a person asking an agent.
- Data movement
- Field mapping and validation between systems, with every transformation written down.
- Retries
- Steps built to be safe to retry without duplicating records. Temporary failures are retried before anyone is alerted.
- Access
- Service accounts and the narrowest permissions each system allows. Credentials stay in the platform’s secret store, never in documents.
- Visibility
- Run history, failure alerts, and a summary of what ran, so problems surface before a customer notices.
- Approvals
- Approval steps are real gates: the workflow waits until a person decides.
- Handoff
- Documentation, access moved to your accounts, and a walkthrough with whoever will own it.
How it works
How an automation project runs.
Map the process
We walk through it with the people who do it today, including the exceptions.
Confirm the connections
For each system: built-in, API, MCP, or custom. Anything custom is scoped before we commit.
Build and test
We build it and run it on real data, including the cases that usually go wrong.
Launch and hand off
It goes live with alerts and logs in place, and your team gets the documentation and access.
Scope
What an automation project covers.
Included
- Process mapping, including the exceptions
- Automations built and connected
- Built-in, API, and MCP connections confirmed during scoping
- Error handling, alerts, and run logs
- Testing with real data
- Documentation and handoff
Scoped separately
- Custom connectors where nothing usable exists
- Changes inside the systems themselves
- Platform subscriptions and usage fees
- Monitoring after handoff
Set with you before we start
- Which processes are in scope
- Where approvals sit
- Who receives alerts
- Which platform runs the automation
FAQ
Common questions
Do we need new software?
Usually not. We build on what you already use where we can. If an automation platform is needed, we recommend one and explain why.
What is an MCP integration?
MCP (Model Context Protocol) is an open standard that lets AI tools such as Claude connect to other systems with defined permissions. An MCP integration lets an assistant or agent look up records or take actions in your software when asked.
Can you connect to an older or in-house system?
Often, yes. If it has an API or a database we can reach safely, we can build a custom connector. We confirm that during scoping, before we commit to it.
What happens when an automation fails?
Temporary failures are retried. Anything that still fails sends an alert to a named person saying what went wrong, and the run log shows where it stopped.
Who owns the automations?
You do. They run in your accounts, and you get the documentation and access when we hand them off.
How is this different from AI agents?
An automation follows a set sequence of steps across your tools. An agent works out how to do a defined job. Many systems combine both: the automation moves the data, and an agent does the reading or drafting in the middle.
Get started
Show us the process.
On the intro call, walk us through a process that repeats, and we’ll talk about how it could run on its own.