Custom dashboards
One screen that answers the question you actually open five tabs to answer. Pipeline, campaign performance, content output and revenue in the same view, refreshed automatically.
AI systems
The dashboard your team keeps rebuilding in a spreadsheet.
Most companies already have the data. It is spread across a CRM, an inbox, an ad account and three spreadsheets nobody trusts. We build the systems that pull it together, score it, and put it somewhere a person can act on it.
Built in your cloud. Your data, your access rules, your source at handover.
- Qualified leads
- 128 +18%
- Avg. response time
- 3.4h -42%
- Score accuracy
- 91% +6pt
- Enrich new inboundAutomated
- Score against ICPAutomated
- Route to ownerAutomated
- Draft first replyNeeds approval
What we build
Four things, all of them boring in the best way.
Most of this is data plumbing and interface: getting the right numbers into one place and making them actionable. A model is used where it earns its place, not as the product.
Lead scoring and enrichment
Inbound leads scored against the profiles that actually close, enriched with firmographic data, and routed to the right person before they go cold.
Assistants trained on your data
A retrieval assistant that answers from your documentation, past proposals and product notes, so the answer is yours rather than a generic one.
Workflow automation
The repetitive chain between tools: enrich, summarise, draft, file, notify. Built so a person approves the output rather than being replaced by it.
How we work with your data
The three rules we do not bend.
Anything touching company data has to be trustworthy before it is clever. These are written into the engagement rather than promised on a slide.
Your data stays yours
Systems run in your accounts and your cloud. We do not train anything on your data or move it somewhere you cannot reach.
A person stays in the loop
We automate the work around a decision, not the decision. Anything customer facing is drafted for approval, never sent blind.
You get the source
No black box and no licence trap. The code, the prompts and the documentation are handed over at the end.
How it runs
A working prototype before a full build.
You use it on your own data in week three. If it is not earning its place, we stop there and you have paid for a prototype rather than a project.
- 01
Map the workflow
Two sessions to find where time actually goes and which decision is being made without data.
- 02
Prototype
A working prototype on your real data, not a mockup. You use it before we build the rest.
- 03
Build and integrate
Wired into the tools you already run, with your access rules and your data staying in your accounts.
- 04
Hand over
Documentation, training and the source. You can run it, change it, or take it elsewhere.
Questions
The ones that come up first.
No. We map the workflow with the people who do the job, then handle the build. You need somebody who can tell us how the work actually happens, not somebody who can read code.
In your accounts. We build inside your cloud and your tools, with your access rules. Nothing is copied to us and nothing is used to train a model.
Then you take it. The source, the prompts and the documentation are yours at handover, which is written into the engagement rather than negotiated afterwards.
It depends on how many tools it has to touch. The prototype stage is deliberately small so you can see it working before committing to the full build. Pricing on request.
No. Most of what we build is data plumbing and interface: getting the right numbers into one place and making them actionable. A model is used where it earns its place, not as the product.
Get started
Tell us what you rebuild every week.
If it lives in a spreadsheet and somebody updates it by hand, it is probably a system. Fifteen minutes, free, and you leave with a view on whether it is worth building.