AI Automation
AI agents that read the inbox, prepare the quotes and chase the follow-ups, so your team spends its day on the work only people can do. A person approves what goes out. Every action is scoped, logged and auditable.
Plenty of AI projects stall between the demo and the Monday after launch. We build for that Monday.
Our agents know where they are in a workflow, ask before they act and leave a record of everything they did. They start small, on one workflow that costs you hours every week, and earn more responsibility as the logs show they can be trusted.
What you get.
Workflow audits
We map where the hours go today and pick the one workflow where an agent pays back first.
Inbox and email agents
Triage, classify and draft replies to the messages your team answers every day.
Quote and admin agents
Read a request, pull out the details, check your rules and prepare the reply.
Voice agents
Answer the phone, book appointments and take messages in your tone of voice.
CRM and follow-up agents
Keep records current and follow up with leads at the right moment, without anyone having to remember.
Answers from your files
Answers drawn from your own documents (retrieval, or RAG), with the source shown next to every answer.
Approval gates and audit trails
By default, nothing leaves without a person saying yes, and every step is logged.
Monitoring
A clear view of what the agents did, what it cost and where they asked for help.
See an example.
An inbox agent on three everyday requests: it reads, extracts the details, checks the rules and drafts a reply. A person approves before anything is sent.
One governed core under every agent.
Every agent we build runs on the same core, so we do the safety work once and each new one inherits it.
Workflow state
Each agent knows which step it is on and what has to happen next.
Approval gates
Sensitive actions wait for a person. You decide which ones.
Scoped permissions
An agent can only touch the tools and data its job needs.
Audit trail
Every read, draft, decision and send is logged with a time and a reason.
Memory and retrieval
Answers come from your documents, with the sources attached.
Safety checks
Screening for prompt injection, spending limits and alerts when something looks off.
How it works.
Map
Short sessions with the people who do the work today. We leave with a map of the workflow and the first agent worth building.
Design
Inputs, rules, tools, approval points and what good looks like, agreed before any code is written.
Build and test
We build on the governed core and test on your real cases, including the awkward ones.
Run and improve
It goes live with a person approving, then earns more autonomy as the logs show it gets things right.
Questions.
Not unless you decide it should. By default every outgoing message or change waits for a person to approve it. You can loosen that step by step once the logs show the agent gets it right.
Your email, calendar, CRM, spreadsheets and most tools that have an API. We connect only what the job needs, with the narrowest permissions that still let it work.
Agents only reach the systems their job needs, and we log what they read and wrote. We use AI providers whose business terms exclude training on your data, and we can keep sensitive steps inside your own systems.
We scope the first agent so it can go live quickly, then grow from there. You get the timeline with the plan, before any build starts.
It depends on the workflow. You get a fixed scope and price for each phase before we start, so the number never surprises you.
Point us at a problem.
Tell us what's slow, invisible or held together with spreadsheets. A person replies within one business day.