The data layer underneath everything.
AIOM Layers 1 and 2, heterogeneous unified data, schemas access, knowledge depot, identity resolution, are where the majority of AI pilots fail to reach production. XSparks architects this layer for agent-readiness, builds it, and operates it. Agents above the layer become productive when the layer underneath them is engineered for the workload.
Twelve percent.
Twelve percent. That's the share of mid-market companies whose data is in good enough shape to support AI at scale, by independent industry research. The other eighty-eight percent watch their pilots stall because the model is doing its job, and the data isn't.
The pattern is consistent: ingestion logic written for analytics, not agents. Tables that humans can read but machines can't reason over. Permission models that broke the moment an agent tried to act on a record. Lineage that nobody updated when the upstream system changed. The agent gets blamed. The data layer was the problem.
Most AI consultancies skip past this layer. They're optimized to ship a model, not to fix what's underneath it. We start here because AIOM Layers 1–2 are where every measurable outcome we've delivered started.
Architect the layer. Operate it in production. The customer owns what is built.
We architect AIOM Layers 1–2 to be agent-ready: HUL & Schemas Access, Knowledge Depot, Identity Resolution. The schemas, the lineage, the permissions, the observability that lets an agent act on a record without breaking everything downstream.
We operate it. Not "we deliver a doc and leave", we run it, monitor it, fix what breaks, evolve it as your operations evolve. The same team that builds it stays accountable for keeping it agent-ready.
Your team owns it. No platform lock-in. Everything we build runs on infrastructure you already pay for, in a configuration your engineers can pick up if you decide to bring it in-house.
Assess in one to two weeks. Build in four to six. Operate as long as the engagement requires.
"We didn't realize how broken our data was until they tried to put an agent on it. The agent failed for a week. They rebuilt the layer underneath. The agent now runs the workflow."
Talk to a Forward-Deployed Engineer.
A working architecture conversation. We walk your current AIOM state, Layers 1–2, orchestration, governance, name what we'd rebuild first, and scope the next 1–2 weeks of diagnostic work.
Or email hello@xsparks.ai