AI automation services that give your team hours back
Our AI automation services take the reading, sorting and retyping your staff do between systems and hand it to software. Each automation is custom code on the major model APIs, wired into tools like HubSpot, QuickBooks and Microsoft 365 through their official APIs, and maintained by us every month.
- One workflow finished before the next one starts
- Model output checked against a schema before it touches a record
- Cost per run logged, so you see what each job costs
Where the hours actually go
Copy and paste between apps that never talk
An order confirmation lands in Outlook, gets retyped into Pipedrive, then again into QuickBooks. Three entries, three chances for a transposed digit.
Inputs too messy for simple rules
Emails, scanned PDFs and free-text forms vary too much for if-then logic, so a person still reads every one.
Integrations that fail without a sound
A sync stops after a password reset or an API version change, and nobody notices until a customer asks where their order went.
Automations we design, build and keep running
Each one is scoped to a single job with a defined input, a defined output and a named person who handles its exceptions.
Inbox-to-record extraction
Requests, orders and forms arriving in Gmail or Outlook are parsed into fields such as customer, item, date and amount, then written to your CRM or ERP with the source email linked.
Document reading
PDFs, scans and spreadsheets are read by a model that must return a fixed JSON schema. Missing or low-confidence fields go to a review queue instead of being filled with a guess.
AI integration services
Systems without a native sync are joined through official APIs: Microsoft Graph for Outlook and SharePoint, the QuickBooks Online and Xero APIs, HubSpot private apps. Where a tool has no open API, we work from scheduled exports.
Classification and routing
Every incoming item is tagged by type, urgency and owner, then posted to the right Slack or Teams channel or work queue with a one-line summary.
Approval queues
Anything that moves money, changes a customer record or messages a customer waits in a queue where a person approves, edits or rejects it.
Run logs and cost tracking
Every run records its input, the model's output, the tools it called, how long it took and what it cost, so failures and cost creep are visible early.
Common first automations
Sales order entry from email
Customer POs read and keyed into the ERP as drafts for review.
Vendor bill capture
Bills read, checked for duplicates and staged in the books.
Help desk triage
Tickets sorted, prioritized and drafted with order history attached.
Client document chasing
Missing tax and bookkeeping documents requested until the file is complete.
Inbound lead qualification
New inquiries scored against your fit criteria and routed to a rep.
Maintenance request intake
Tenant requests sorted by urgency and routed to the right vendor.
How we build so it keeps working
Plain code where rules are enough
If a lookup or a formula does the job, we use it. Models are kept for reading and judgment, which holds down cost per run and the number of things that can fail.
Ready for vendor changes
APIs get versioned and retired. Each integration alerts on failed calls and holds work in a queue, so a QuickBooks or HubSpot change pauses a job instead of corrupting records.
Accounts in your name from day one
Cloud hosting, model API keys and the code repository sit in your company's accounts, so the usage bill and the access list are yours to inspect.
Scoped access for each automation
Every automation gets its own credentials with only the permissions it needs, such as read-only on the ledger and draft-only on bills.
“He got me 9 sales in my first 7 days of launching our campaign, which exceeded my expectations!”
Common questions
What is an AI automation service?
A team that builds and runs software for repetitive work involving reading, sorting or writing. The automation pulls information from emails, documents or apps, uses a model to turn it into fixed fields, writes the result to your systems and sends anything uncertain to a person.
What does an AI automation company actually deliver?
Working code in a repository you own, hosted in your cloud account, with model provider API keys in your name. You also get a short written description of what each automation does, who handles its exceptions and how to switch it off.
How do you decide whether a step needs AI or plain code?
If the input is consistent, such as a CSV export or a webhook with fixed fields, plain code is cheaper and more predictable. A model earns its place when the input is free text, a varied PDF or a long email thread, and even then its output is validated before use.
What drives the model usage cost of each run?
Mostly document length and the number of model calls a job needs. We log token usage on every run and report cost per job each month. Usage bills to your own provider account, so there is no hidden markup.
What happens if a vendor changes its API?
Failed calls trigger an alert and affected items are held, not dropped. We update the integration, replay the held items and note the change in that month's report. We also track deprecation notices for the APIs you depend on.
Can a malicious email trick an automation?
Prompt injection, where text in an email or document tries to give the model new instructions, is a real risk. We treat inbound content as data, limit which tools a model can call, and keep anything that moves money or changes records behind human approval.
See what you should automate first
Take the 2-minute AI audit for a readiness score and a ranked shortlist of automations for a business like yours.
- Collect a week of real inputs
We gather actual emails, files and records for the job, strip anything sensitive, and use them to define exactly what the automation must produce.
- Build and score against those samples
The first version is graded on that sample set. Prompts and rules are revised until accuracy on real cases meets the bar your team sets.
- Shadow your team for two weeks
It runs beside the person who does the job today. They accept or correct each output, and every correction becomes a new test case.
- Hand over, then review monthly
Approvals come off only where error rates justify it. Each month we check logs, cost per run and upcoming vendor API changes.