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24 resultsApplied AI & ML — Service Overview
Everything included in our Applied AI engagements: RAG, agents, fine-tuning, evals, and guardrails.
What is Retrieval-Augmented Generation (RAG)?
A plain-English explanation of RAG: why it beats pure LLM memory for production knowledge systems.
Building a Data Quality Framework
Dimensions of data quality, validation layers, and monitoring in production pipelines.
Apache Kafka — Core Concepts and When to Use It
Topics, partitions, consumer groups, and the use cases where Kafka excels.
Introduction to Data Pipelines
What a data pipeline is, the core stages, and when to build vs buy.
Customer telephony AI with live agent handoff
Real-time STT/LLM/TTS pipeline; cut hold time by 41%.
Diagnostic RAG for heavy equipment
Indexed 4M+ pages across PDFs & manuals; latency < 400ms; 32% fewer escalations.
CI/CD Pipeline Design — From Commit to Production
Stages, gates, deployment strategies, and keeping pipelines fast.
Batch vs Streaming Pipelines — Choosing the Right Pattern
Lambda architecture, Kappa architecture, and practical guidance for choosing.
Monitoring and Alerting for Data Pipelines
What to monitor, SLIs/SLOs for data, and building effective alerting.
ETL vs ELT — Which Pattern Should You Use?
Understand the difference between Extract-Transform-Load and Extract-Load-Transform and when each fits.
Schema Registry and Avro for Kafka Data Contracts
Why schema management matters for streaming pipelines and how to implement it.
Real-Time Analytics Architecture Patterns
Lambda, Kappa, HTAP, and choosing the right pattern for sub-second analytics.
Container Registry Management and Image Lifecycle
Tagging conventions, vulnerability scanning, retention policies, and registry options.
Data Observability — Detecting Silent Pipeline Failures
Freshness, volume, distribution, schema, and lineage monitoring for data reliability.
Airflow Best Practices for Production Pipelines
Idempotency, backfilling, SLA misses, and common pitfalls to avoid.
Snowflake Best Practices for Cost and Performance
Virtual warehouses, clustering, query optimization, and controlling spend.
DuckDB — Blazing Fast Local Analytics
When to reach for DuckDB instead of Spark, and how to use it effectively.
Stream Processing with Apache Flink
Event time vs processing time, windows, stateful operators, and production deployment.
Orchestrating Pipelines with Apache Airflow
DAGs, operators, scheduling, and production best practices for Airflow.
Data & Platform — Service Overview
Pipelines, vector stores, governance, and privacy-first data design.
Feature Stores — Bridging Data Engineering and ML
What a feature store is, online vs offline stores, and when to build vs buy.
Testing Strategy for Data Pipelines
Unit tests, integration tests, data contract tests, and regression testing for pipelines.
Product Engineering — Service Overview
APIs, dashboards, and services delivered with tests, CI/CD, and observability from day one.