Shipagenticsystemsyoucantrust.
Orchestration, tracing, evals, and guardrails wrapped around real services and real data in production.
TRACE PREVIEW
p95 latency
342ms
cost / run
$0.014
eval pass
98.4%
gateway
12ms
orchestrator
38ms
tool-router
16ms
retrieval
44ms
model
210ms
guardrails
22ms
logger
9ms
Tracing + cost attribution
Eval-driven iteration
Guardrails + validators
Tool contracts
Production observability
//_SELECTED_WORKS
System Architecture
Applied engineering solving production constraints.
Event-Driven Platforms
Constraint
High-volume transactional traffic with strict latency and reliability requirements.
Engineering Focus
Event-driven services, async messaging, and database optimization under sustained load.
Outcome
Scalable ingestion and processing pipelines handling tens of millions of events.
:: Java
:: AMQ
:: Kafka
:: SQS
:: Postgres
:: Oracle
Real-Time Analytics Pipelines
Constraint
Millions of events per day with near-real-time visibility.
Engineering Focus
Streaming ingestion, schema evolution, backpressure control, and analytics-ready data models.
Outcome
Reliable real-time dashboards backed by high-throughput streaming and analytics systems.
:: Kafka
:: Kinesis
:: Confluent
:: Databricks
:: Java
:: Python
Enterprise Interface Architecture
Constraint
Complex data operations serving tens of thousands of users across teams and domains.
Engineering Focus
Type-safe UI architecture, shared components, and consistent data interaction patterns.
Outcome
Scalable frontends enabling faster iteration across a 15-person engineering team.
:: React
:: TypeScript
:: Design Systems
:: Accessibility
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System Capabilities
Four pillars of production-grade AI systems
Orchestration
→Tool routing and state
→Retries and timeouts
→Explicit contracts
Tracing
→End-to-end spans
→Correlation across services
→Cost attribution
Evals
→Regression suite
→Golden datasets
→Scorecards
Guardrails
→Schemas and validators
→Safe defaults
→Policy boundaries
//_SYSTEM_FLOW
Architecture Overview
A deterministic pipeline for AI-powered systems
// INGEST_OVERVIEW
Data Entry Points
Schema validation
Normalization and enrichment
Source connectors
Data contracts
Signal Produced
Validated Inputs
source: "kafka_topic_v1"
format: "avro_schematized"
valid: "true"
AVAILABLE FOR PROJECTS
Ready to build something real?
Applied AI systems with orchestration, tracing, evals, and guardrails