Clean data. Lower costs. AI that pays for itself.
We help companies cut unnecessary software spend, fix fragmented data and automate expensive manual work, then deploy AI where there is a measurable business case.
No sales deck. We’ll look at your stack and whether there’s a useful project.
Cost, data and AI, pulled in the right order.
Measurement, tracking, and attribution specialists. Analytics engineers with media and SaaS experience.
Cost
Reduce avoidable platform spend, overlapping tools and dependency on manual operating models.
Data
Replace disconnected reporting with trusted infrastructure and usable decision systems.
AI + Automation
Use Grok, ChatGPT, and Gemini where they cut real work, and automate the repetitive ops around them: speed, quality, visibility, operating leverage.
AI only works when the data and infrastructure beneath it are sound.
Platforms & models we work with
capture → activate → buildAds, Analytics, Tag Manager, and Cloud data for capture and reporting
Meta
Ads signal, measurement, and Conversions API for first-party events
Microsoft
Azure and Power Automate for workflows that move data into action
Salesforce
Marketing Cloud and CRM as the customer system of record
Vercel
Fast, shippable web and app surfaces for the work
Cursor
AI-assisted build and iteration on the implementation itself
Anyone can buy tokens. Value is in the pipes.
Better models arrive faster. Benchmarks converge. Pricing gets competed down. The hard part is connecting AI to real business systems: first-party data, GTM and event tracking, CRM, attribution, customer journeys, workflow automation, permissions and governance, data warehouses, and operational decisions.
That is where AI creates value, or becomes another expensive software line item.
Most 2026 businesses are still running on a 2020 stack.
Expensive reporting platforms
Legacy BI and agency-built dashboards that cost more than they return.
Multiple disconnected systems
Overlapping SaaS tools with no shared source of truth.
Manual spreadsheet processes
Reporting and ops still glued together by hand every week.
Agency dependency
Critical measurement and tagging owned by someone else.
Poor data visibility
Decisions lag because the numbers never land in one place.
AI with no measurable ROI
Pilots that never leave the lab, instead of Grok, ChatGPT, or Gemini cutting real work.
From assistants to ops that run.
Assistants
Ask one prompt at a time.
Connected AI
Wired into your tools and data.
Workflow agents
Keep working in the background.
Autonomous ops
Run with guardrails in place.
Practical audits, roadmaps and implementation support for modern technology teams.
Services are designed for leaders who need to reduce software waste, improve data visibility and make AI useful inside real operating processes.
AI & Technology Cost Audit
A focused review of your current software estate, reporting workflows, vendor dependencies and manual operating costs. The output is a prioritised list of opportunities to reduce spend, simplify systems and apply automation where it has a clear business case.
Marketing Technology Audit
Assessment of your measurement stack, tagging, attribution, CRM integrations, campaign reporting and platform governance. Designed for teams that need cleaner data, lower agency dependency and stronger visibility into marketing performance.
Data Infrastructure Review
A practical review of how data is captured, stored, transformed and served to the business. We identify brittle pipelines, duplicated reporting logic, data quality risks and opportunities to move toward cloud-native architecture.
AI Workflow Automation
Identification and delivery of AI-enabled workflows that replace repetitive analysis, reporting, QA, documentation and operational coordination. Every recommendation is tied to time saved, cost reduced or quality improved.
Implementation Roadmap
A board-ready plan that translates audit findings into a phased delivery programme, including commercial impact, dependencies, risk, governance and the right sequencing for modernisation.
Digital Sovereignty
Own more of your infrastructure, data and digital assets. We help clients reduce dependency on third-party platforms where ownership matters.
A practical path from technology waste to measurable improvement.
Discovery
Clarify business goals, current pain points, cost pressures and the systems that matter most.
Audit
Map platforms, data flows, reporting processes, integrations, manual work and hidden dependencies.
Roadmap
Prioritise the highest-value opportunities with commercial impact, implementation effort and risk clearly set out.
Transformation
Support implementation across automation, cloud infrastructure, AI workflows and reporting modernisation.
Work you can picture yourself in.
Specialist measurement vs another dashboard
All-in-one commerce analytics tools promise clarity, but the pipes underneath stay brittle when events, CRM, and ads don’t agree.
Own the measurement layer as analytics engineers: GTM, server-side tracking, Meta CAPI, GA4, and CRM joins so attribution and AI sit on trusted data.
Cleaner attribution and a stack you control, without swapping one black-box dashboard for another.
Commerce measurement rebuild
Shopify tracking was heavily dependent on browser-side tags, limiting data quality and making conversion measurement more vulnerable to signal loss.
Reworked the measurement setup around Google Tag Manager and server-side tracking. Connected Shopify conversion events with Meta CAPI and improved the flow of first-party data into advertising platforms.
A cleaner, more resilient measurement setup with better control over conversion data and less reliance on browser-only tracking.
Automated conversion pipeline
Important customer actions were happening outside Meta’s standard browser tracking, leaving paid media without a complete view of downstream conversions.
Built an automated workflow in Microsoft Power Automate that captured conversion data from business systems and used HTTP requests to send structured events directly into Meta’s Conversions API.
First-party conversion events could flow automatically into Meta, reducing manual work and improving visibility into the actions that actually mattered.
I’ve worked agency, vendor, and client side, so I’ve seen the hurdles from every seat.
Connected CRM, digital, and website data so clients could personalise through Salesforce Marketing Cloud and Google Marketing Platform.
Ran complex Marketing Cloud Intelligence and MuleSoft implementations and turned goals into architecture teams could actually use.
Advised on ads and commerce measurement and delivery, and unblocked clients with Product, Engineering, and Sales.
One seat across architecture, implementation and support.
Companies need one trusted person who can guide solution architecture, implementation, tech support, solutions engineering, and account management. The days of working in siloed teams are over.
Many companies do not need more dashboards, more SaaS tools or vague AI strategy. They need a clearer view of where technology spend is creating value, where manual processes are slowing decisions down and where automation can remove real operational friction.
My role is to turn that complexity into a practical plan: simplify the stack, improve data quality, reduce avoidable spend and deploy AI only where it helps people make faster, better decisions.
Flexible support for shifting priorities.
Technology changes quickly. Your operating model should be able to change with it. endpointLabs works flexibly, without forcing clients into a rigid consulting model.
One-off projects
Some clients need a focused audit.
Retained advisory
Others need architecture or ongoing technical support.
Hands-on delivery
Implementation alongside your team.
AI for the sake of AI
If automation doesn’t save time, reduce cost or improve decisions, don’t build it.
Another dashboard nobody uses
Reporting should answer decisions, not create another login.
Technology lock-in
Architecture should increase your options, not reduce them.
100-slide transformation decks
We prioritise practical architecture and implementation.
Common questions.
What does endpointLabs actually do?
We help teams cut software waste and modernise how data, marketing tech, and AI work together: audits, roadmaps, and hands-on implementation.
Why start with data capture?
If GA4, GTM, and event pipes are wrong, BigQuery and the model don’t save you. Clean raw data first; warehouses and AI only amplify what’s already true.
Which marketing platforms do you work with?
Google Marketing Platform, Meta CAPI, Salesforce Marketing Cloud, plus the measurement stack around them, not generic “MarTech strategy” slides.
How do you use AI day to day?
Hands-on with Grok, ChatGPT, and Gemini: practical workflows and agents, not vague “AI transformation.”
What is digital sovereignty in your work?
Owning more of your infrastructure, data, and digital assets so you’re less locked into third-party platforms, including self-hosted options where they fit.