Even mature brands — ones that have already stood up the “basic” pieces of an AI or Data Stack — eventually run into serious systems-integration problems. Three kinds of proliferation drive it:
- SaaS proliferation — new platforms for agents, ad spend, commerce, CRM, and data lakes that all need to be configured into an existing stack.
- Use-case proliferation — new techniques and KPIs (Agentic AI, incrementality, media mix modeling, predictive analytics, data clean rooms) that expand what a team needs to know.
- Technology proliferation — more platforms, more custom code, more ad-hoc data lakes, and the ongoing burden of managing all of it.
There are literally tens of thousands of MarTech & AdTech SaaS applications, and every year the list gets a little longer.
Few brands have a full bench of AI engineers, data scientists, and systems integrators on staff — and even the ones that do face a constant tug-of-war between resourcing the core product and resourcing analytics. Left unmanaged, even a mature stack can sprawl into something like this:
Latticework Advanced bundles Latticework’s other services with the firepower of a traditional custom software team: agile development, database schema design, and systems architecture. It’s built on 7 years of coaching 70+ brands through problems like orchestrating multi-agent systems, taming unruly ETL pipelines, and mining insight out of sprawling data warehouses.
The right “Latticework” depends on where a brand is in its growth — which is why the services run from Lite, to Basic, to Advanced, to Copilot, each tailored to a different stage.