AI automation, built for the work you actually do
We design, build, and run AI automation for operations teams who need fewer manual steps and more time thinking. Not a platform. Not a consultant. A team that ships.
Targets the right work first
Anything done the same way more than 50 times a month is a candidate. We find it, scope it, and ship the first automation inside 30 days. No 6-month roadmaps.
Works in your stack, not ours
We connect to the tools your team already opens. Google Workspace, Microsoft 365, SAP, Salesforce, WhatsApp, or custom databases. No platform migrations.
Measurable from day one
Every automation ships with a baseline measurement and a target. You see the lift in the first week or we fix it before the next billing cycle.
Human review where it matters
AI handles volume. Humans handle judgment calls. You define the threshold. We build the routing logic that respects it.
Discovery
We map your highest-frequency tasks in a two-day workshop. You walk out with a ranked list of automation targets and a rough time-to-value estimate for each.
Scope and design
We pick the top target, design the automation flow, and get your sign-off before writing a line of code. No surprises.
Build and test
Build takes two to four weeks for most automations. Testing runs in parallel on a copy of your data. You review every edge case before it goes live.
Scale
Once the first automation runs clean, we move to the next target. Most clients automate three to five processes in the first six months.
01 What is AI automation and how is it different from RPA?
RPA records and replays clicks on a fixed screen interface. AI automation understands context, handles variation in inputs, and applies reasoning to decide what action to take. RPA breaks when a button moves or a field label changes. AI automation adapts because it reads the document or message the way a human would, not according to a rigid template. We use both in the right places, often in the same workflow.
02 How long does it take to deploy a first AI automation?
Most first automations go live in 30 days from signed scope. Discovery takes two days. Design and approval takes one week. Build and testing takes two to three weeks, running against a copy of your data. You review the output before the automation touches your live systems. 30 days is the target; complex multi-system integrations sometimes run to six weeks.
03 Can AI automation work with our existing tools without replacing them?
Yes. We connect to your existing stack via APIs, webhooks, and file-based integrations depending on what each system supports. We have worked with Google Workspace, Microsoft 365, Salesforce, SAP, various SQL databases, and dozens of industry-specific platforms. We have never asked a client to switch platforms to make an automation work. The automation connects to what you already use.
04 How do you measure ROI on AI automation?
We measure three things: time saved per task instance, error rate reduction compared to the manual baseline, and throughput increase at the same headcount. We measure the baseline before we start, not after, using a two-week time-and-motion study on actual instances. We report weekly during the first month so you see the lift before the next billing cycle, not after a quarterly review.
05 What happens to staff whose work is automated?
In every engagement we have run, automated staff have moved to higher-value work rather than out the door. The reason is consistent: the constraint was never the number of people, it was their capacity. When routine volume is handled by automation, the same team can take on more complex work, more clients, or better quality review. The constraint shifts from capacity to quality, which is a better problem to have.
06 Is our data used to train your AI models?
No. Your data is used only to run your automations and produce the outputs you have authorized. We do not use client operational data to train any shared model, fine-tune any shared system, or improve automations for other clients. Data access is restricted to the specific systems and fields required for each automation, and that access is documented in the engagement scope.