AI and Workflow Automation
We automate the repetitive work in your business: moving data between systems, handling routine requests, and producing reports and documents. AI models handle the steps that need reading, writing, or judgment; plain code handles the rest. Every run is logged and reviewable, in accounts you own.
What we automate
- Intake and triage. Inbound emails, forms, and support requests read and classified, with the key details extracted and the request routed to the right person or system.
- Documents. Quotes, proposals, reports, and routine correspondence drafted from your data and templates, for a person to review and send.
- Data entry and sync. Records kept in step across your CRM, accounting, scheduling, and spreadsheets, so nobody retypes them.
- Reporting. Scheduled summaries of sales, operations, or pipeline, delivered by email or Slack.
- Research and enrichment. Information about leads, vendors, or listings gathered from the web and your own records, then summarized.
- Internal assistants. Answers to staff questions from your own documents and policies, with the source cited.
How we build workflows
- Code first, AI where it earns its place. Deterministic steps are plain code; models handle only the steps that need reading, writing, or judgment.
- People approve what matters. Anything that reaches a customer or moves money waits for a person, until the workflow has a track record.
- Every run is logged. Inputs, outputs, and model responses are recorded, so mistakes are visible and fixable instead of silent.
- Models chosen per task for quality and cost, from providers such as Anthropic and OpenAI whose commercial API terms exclude training on your data.
- Your accounts. Workflows run on infrastructure and API keys in your name, connected to the tools you already use.
Where to start
Pick one workflow that runs several times a week, follows the same steps each time, and that people dislike doing. Note how long it takes today. That makes a good pilot, and the before-and-after is easy to see.
What not to automate
Rare tasks, tasks where every case is genuinely different, and tasks where an error is expensive and hard to spot are poor fits. We will say so when that is the case, and suggest the part of the process that is worth automating instead.
Not sure where AI fits in your business yet? See AI consulting. For assistants that answer from your documents, see AI chatbots and knowledge bases. For automations that need their own interface, such as a dashboard or a review queue, see custom software.
Frequently asked questions
- Will an AI workflow make mistakes?
- Sometimes, which is why workflows are designed around it: steps with consequences need a person’s approval, every run is logged, and outputs are checked against rules where possible. The goal is fewer errors than the manual process, with the remaining ones easy to catch.
- Is our data safe?
- Data goes only to the providers a workflow needs, under API terms that exclude training on it, and stays in accounts you control. Sensitive fields can be removed before anything reaches a model.
- What does an automation cost to run?
- Mostly model usage fees, billed by the provider per request, plus any hosting. We estimate the running cost per task before building, so it is known up front.
- Do we have to change our tools?
- No. We connect to the tools you already use through their APIs or exports. If a tool has neither, we tell you before work starts.