AI, Data & Governance
Every AI strategy runs on a stack. This is where yours lives.
From the lake to the agent, this map makes the enterprise toolchain visible: data, platforms, models, orchestration, evaluation, security, and human accountability assembled into an architecture you can understand, select, and operate.
The reference stack.
Ten layers, assembled per engagement. Each row shows up to three representative options selected from current primary-source evidence. Inclusion does not indicate partnership, endorsement, a required product, or a universal bill of materials.
Databricks
Snowflake
Apache Iceberg
Fivetran
Informatica
Airbyte
Incorta
Apache Superset
Confluent
Apache Kafka
Atlan
CollibraOpenMetadata
Sparkflows sole ML platform
Supabase Vector
Pinecone
Weaviate
n8n
LangGraph
Datadog
Privacera
Open Policy AgentReference options, not relationship claims. The right architecture depends on purpose, risk, installed platforms, data boundaries, operating capacity, and commercial diligence. Inclusion does not indicate partnership, endorsement, certification, reseller authorization, pricing rights, verified interoperability, or Scott-specific implementation experience.
Build the stack around what must remain authoritative.
Start with the system of record, consequential workflow, installed estate, and decision that is creating pressure. Scott can help turn those constraints into a smaller set of defensible platform choices and an implementation path.