Clean data, not new tools
The stack now runs to 15,384 tools at 33% utilisation. We will not sell you the 15,385th. We make HubSpot, Salesforce, and GA4 produce numbers that agree.
Start with the data
AI didn't fail. Your data did.
Half your deals have no contact attached. GA4 still has not reconciled to HubSpot. Fix that, then the AI finds pipeline your competitors are still hunting through dashboards for.
why ai & data
Why AI & Data
95% of AI pilots fail. Data is why.
MIT found it. Salesforce confirmed it. Every CMO has felt it. You cannot run agents on a CRM where half the deals have no contact attached. You cannot trust attribution on a 192-day cycle when LinkedIn's window is 30 days. Fix the foundation first. Then add the intelligence.
Get in touchAttribution your CFO defends
We build a pipeline number that survives a CRO challenge. It is not a dashboard that four stakeholders read four different ways every Monday morning.
AI where it earns its keep
Agents are embedded inside HubSpot, Salesforce, and Slack. There is no pilot and no sandbox. It is production from day one or we do not ship.
our approach
Our Approach
Foundation first. Intelligence on top.
We audit the data before we touch the AI. About a third of audits recommend you switch off a tool, not add one. The other two-thirds get a written rebuild plan.
The audit runs for thirty days. We map every data source, every event, and every gap, across GA4, CRM, warehouse, and ad platforms. 81% of GA4 migrations fail on misconfigured events. We find yours and write the diagnosis you can show the board.
We design the data model your sales cycle actually needs. That means 192 days and a 6–10-person buying committee, not a 30-day click window. The attribution model is named, the schema is documented, and an owner is assigned.
We install server-side tracking, warehouse-native pipelines, and consent flows that satisfy DUAA, PDPL, and IPP 3A. AI agents are wired into the tools your team already uses. Everything is shipped, not sandboxed.
We run data quality reviews every week, recalibrate models every month, and rationalise the stack every quarter. The infrastructure scales as you do, without a re-platform every 18 months.
Our AI & Data
Services
The service runs in four layers as one operating system. Every layer earns its keep against a number your CFO will defend.
Data Infrastructure
We set up the warehouse, server-side GTM with consent mode v2, and the contact-to-deal links your attribution depends on. This decides whether every dashboard above it lies.
Attribution & MMM
We build multi-touch attribution and MMM (Meridian or Robyn) sized for 192-day cycles, not 30-day click windows. The output is a number your CFO will defend at a board meeting.
AI Agents & Insight
We embed agents in HubSpot, Salesforce, and Slack. They answer the questions your analyst has not had time to run since March. It is not a ChatGPT wrapper in a platform jacket.
Generative Engine Optimisation
AI Overviews are cutting search traffic by 34–58% on affected queries. We get your brand cited inside the answer, rather than buried beneath it.
Stop buying tools. Start using them.
Your stack is 33% utilised. GA4 still has not reconciled to HubSpot. Cookie deprecation got cancelled and the consent problem did not. Your last AI pilot returned a slide deck, not a sale. We do not sell platforms. We make the ones you already own produce a number your CFO trusts.
why MxD
Why MxD for AI & Data
Vendor-agnostic. Compliance-native. Senior on day one.
We take no partner-tier kickbacks that distort what we recommend. We have people on the ground in London, Dubai, and Auckland, so DUAA, UAE PDPL, and NZ IPP 3A are built into the architecture rather than bolted on after the regulator updates the guidance. Senior data engineers and AI specialists run every account. The person at the pitch builds the thing.
Common
Questions
We've already bought an attribution platform. Do we still need you?
You often do. The buyers we speak to have spent 30,000 to 120,000 pounds on an attribution platform and still cannot agree on a pipeline number internally. The licence was the easy part. The work is modelling it to a 192-day cycle, fixing the contact-to-deal gaps that break the chain of truth in your CRM, and getting the board to trust the output.
How is this different from a fractional CMO or a data consultancy?
Consultancies hand you a strategy deck and leave. Fractional CMOs talk about data without touching it. We sit between strategy and engineering. Our senior people can write the dbt model, configure server-side GTM, and explain the attribution methodology to your CFO in the same meeting.
We've been burned by AI pilots. Why is this different?
We will not run a pilot. MIT found that 95% of generative AI pilots fail, and most failures trace back to the data, not the model. We fix the data first. Agents then go inside HubSpot, Salesforce, and Slack, so the answer lives where the work is done. There is no sandbox and there is no demo dashboard. It is not a ChatGPT wrapper dressed up as a platform.
What does the first 90 days look like?
Days 1 to 30 are the forensic audit and the written diagnosis. Days 31 to 60 are the foundation rebuild, covering tracking, warehouse, attribution model, and consent flows. Days 61 to 90 are the AI overlay and the first production agents. By day 90 you have a pipeline number you can defend, not one you have to apologise for.