The pattern library.
Architectures built for real systems.
These are architecture patterns built around the operational problems that appear once data and AI systems move beyond prototypes.
The library focuses on implementation decisions, production failure modes, ownership and measurable tradeoffs rather than diagrams alone.
Find the architecture you need.
Change Data Capture From Operational Systems to Lakehouse
A production architecture for capturing inserts, updates and deletes from operational databases and landing them safely into a replayable lakehouse.
Cost-tiered Model Routing
A production routing pattern for sending easy requests to cheaper models while reserving frontier-model capacity for cases that actually need it.
Data Quality Monitoring with Routed Ownership
A data-quality architecture that detects silent failures, assigns every check to an accountable owner and routes issues to the people who can act on them.
Human-in-the-loop Approval Gates for Agent Workflows
A durable approval architecture for agent workflows that take consequential actions, with reviewer context, pause-and-resume state, routing and an audit trail.
LLM Evaluation Harness for Production Systems
A production evaluation architecture for detecting LLM regressions, measuring quality numerically and preventing model, prompt or retrieval changes from quietly reducing quality.
Parallel-run Migration for Warehouse Replacement
A controlled warehouse migration pattern that runs old and new platforms in parallel, systematically reconciles their outputs and cuts over only after sustained parity.
Permission-aware Retrieval over Enterprise Documents
A retrieval architecture for enterprise knowledge systems where document permissions remain intact throughout search, retrieval and generation.
Semantic Layer as a Single Source of Metric Truth
A governed analytics architecture for defining business metrics once and serving the same definition consistently across BI tools, spreadsheets, APIs and applications.
We publish the tradeoffs too.
These patterns are not just diagrams. Each one explains what the architecture looks like, the operational assumptions behind it, what can fail and when a simpler design may be more appropriate.
A useful architecture pattern should help you decide when to use it as much as it helps you understand how to build it.
See how we build.
If one of these patterns looks similar to the system you’re trying to build or repair, we can talk through the architecture, constraints and practical tradeoffs.
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