AI automation, built and run for you
Every system we build starts with an outcome you can check: hours saved, costs cut, leads answered. We build the AI into the tools you already run and keep it running in production, so you can tell it’s working from the results alone.
Logistics
Shipment intake
Email → labels + bookings
Support
ERP assistant
Questions → answers + routing
Sales
Lead qualification
Inbound → hot / warm / cold
Fleet
Fuel monitoring
Telematics → alerts
Official partners
Not sure where AI fits?
We audit your workflows, tools and data, then rank each task by hours lost and risk. You get a shortlist of what to automate, what to leave alone, and what it should return.
How the engagement worksYour staff learn which of their own tasks AI can take over, using examples from your department, not generic demos.
You getTask list per department
We map where the hours go, check whether your data and tools can support automation, and tell you plainly where AI should not be used.
You getRanked workflow shortlist
We build the top-ranked workflow first, measure it against the baseline, then move to the next one.
You getFirst workflow live, measured
Build and deploy
Six capabilities we ship repeatedly. Most engagements combine two or three of them.
Example: ERP question to answer + ticket
AI agents that handle a full task, such as answering an ERP question or qualifying a lead, and hand off to a person when they are unsure.
Example: email to booking
Email-, form- or document-triggered workflows that create the record, booking or label without anyone retyping it.
Example: buying signal to CRM entry
Several agents split one process. For example, one finds buying signals, one drafts outreach, and one logs it to the CRM.
Example: your app to AI feature
AI features built into your own product or internal tool, connected to the systems you already use.
Example: live data to decision view
Operational views that surface the numbers a team actually decides on, such as fuel cost per route, wired to live system data.
Example: brief to running system
We own the project end to end for teams without an internal AI function, from scoping the first workflow to keeping it running.
Live, not pilots
Every system we ship runs in production for real clients. A selection of case studies is below.
Who we serve
If someone on your team spends hours a day copying, checking or chasing the same information, that is the work we automate first.
B2B companies and SaaS startups
Teams shipping product who need AI capability built in without diverting the core engineering roadmap.
Operations-heavy businesses
Logistics, finance, and service organisations where the cost sits in repeated manual handling.
Growth teams and founders
Small teams that need the output of another hire this quarter without the 6-month internal build.
Selected work
Each one started as a problem the client described in one sentence. Here is what we built and what changed. The numbers are the ones the client measures internally.
General
Systems that take over repetitive handling, pull insight out of existing data, and keep operations moving.
Problem
Shipment requests arrived by email, and staff retyped data into multiple tools.
AI implementation
AI now reads each email, validates details, and creates labels plus bookings automatically.
Result
Order handling became near-instant with 95% less manual work and zero monthly entry errors.
Problem
Leads dropped because intake was slow and setup took too long.
AI implementation
AI reads project emails, captures requirements, and auto-creates CRM project records.
Result
Setup became 80% faster, no offers were missed, and CRM data quality stabilized.
Problem
ERP support was costing $10k+/month due to repetitive requests.
AI implementation
We deployed an AI ERP assistant connected to internal knowledge and auto-routing.
Result
Support costs dropped 90% and users got faster, consistent answers.
Industry spotlight
Pipeline automation that qualifies inbound leads, finds new ones from live buying signals, and keeps event audiences showing up.
Problem
Inbound leads sat unsorted, so hot prospects went cold while they browsed competitors.
AI implementation
AI scores every inbound lead against the company's own criteria and sorts it into hot, warm, or cold.
Result
Hot leads are contacted immediately, and no ready-to-buy client is left unbooked.
Problem
Outbound relied on cold lists, missing prospects already showing buying intent online.
AI implementation
The system scrapes public buying signals, finds interested leads, and drafts personalised email or message outreach.
Result
Monthly lead flow grew 10% from a fully automated, signal-driven pipeline.
Problem
Webinar and workshop registrants forgot to show up, with attendance under 5%.
AI implementation
Recurring reminder emails now run automatically for every public event from registration to start.
Result
Attendance climbed to around 30% of registrants — a six-fold improvement.
Industry spotlight
A multi-workflow programme covering operational efficiency, cost control, and fleet oversight.
Problem
Paper travel sheets caused delays, typing mistakes, and missing documents.
AI implementation
A mobile OCR flow now reads sheets, validates fields, and syncs directly to fleet systems.
Result
Processing dropped 85%, document loss hit zero, and route visibility became real-time.
Problem
Fuel events were inconsistent, so cost drift was hard to detect quickly.
AI implementation
We unified fuel data in one live control layer with policy-based alerts.
Result
Cost variance dropped 40%, response moved to minutes, and transaction visibility reached 100%.
Problem
Fuel theft checks were monthly, so losses were found weeks too late.
AI implementation
We built real-time detection that correlates mileage, route behavior, and fueling patterns.
Result
Suspicious events are now flagged immediately with a full investigation trail.
Production delivery
Every workflow ships with a named owner, alerts when an input looks wrong, a person-in-the-loop path for exceptions, and a monthly review against the baseline we measured before go-live.
Pick your first workflowThe loop every workflow runs after go-live.
Next step
