Selitia
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Enterprise data engineering & design
Selitia designs, builds, and monitors the strata an enterprise runs on: vector systems for meaning, SQL foundations for truth, and cloud architecture that holds both together. One firm, accountable for the whole stack.
The strata
Most enterprises have all four of these somewhere. Almost none have them designed as a whole. That gap is where pipelines rot, dashboards drift, and AI initiatives stall.
Embedding pipelines, similarity search, and retrieval layers built on pgvector and purpose-built stores. Designed for recall you can measure, not vibes. This is the layer your AI products stand on.
The moving layer: change data capture, event buses, and the pipelines that keep every downstream copy honest. Exactly-once where it matters, at-least-once where it doesn't, and documented which is which.
The layer of record. Warehouse and operational schemas modeled so that one question has one answer, with tested transformations and migrations that are reviewed like code, because they are code.
The ground everything sits on: object storage layouts, table formats, compute topology, network boundaries, and the Terraform that makes all of it reproducible instead of tribal.
What we do
2–4 weeks
A forensic read of the data estate you already have. We trace lineage, measure freshness and cost, find the queries that lie, and hand you a map: what exists, what it costs, what breaks, and in what order to fix it.
Deliverable: the estate atlas, a costed remediation sequence, and an executive readout.
6–16 weeks
Architecture as a real deliverable: layer boundaries, schema contracts, technology selection with written rationale, then the build itself. We ship the layers with tests, lineage, runbooks, and handover training, so your team owns it on day one.
Deliverable: running infrastructure, the design record, and a team that can operate it.
ongoing
Data observability as an operated service. Freshness, volume, schema drift, cost anomalies, and retrieval quality tracked against SLOs, with alerts that reach a human who already knows your stack.
Deliverable: a monthly reliability report and a pager that rarely goes off.
Monitoring
Every layer we operate carries explicit service levels: how fresh, how complete, how fast, how much. The console below is a live simulation of the signals we watch, the same four families we instrument on every engagement.
Method
We start in your existing systems, not a slide deck. The first artifact is always a map of what is, not a pitch for what could be.
Layer contracts get drawn first: what each layer promises the one above it. Vendor and tool choices come after, with the rationale written down.
Schemas, transformations, and infrastructure live in repositories with tests and review. If it can't be rolled back, we don't ship it.
An engagement ends when your team operates the stack without us, holding runbooks they've already used. Dependence is a failure mode, not a revenue model.
Contact
A warehouse nobody trusts, a vector search that misses, a cloud bill that grew a comma. Start with the specific pain and we'll scope from there.
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