Event-sourced decision audit trail for AI agents
Python
Updated Jan 30, 2026
Ali Uyar · AI Systems / Technical Product
AI Systems & Product, built for reliability.
I help teams move from prototypes to dependable AI products with clear evidence, deterministic execution where it matters, and architecture decisions that age well.
Deterministic workflows where reliability matters
Auditability and traceability by design
Privacy-first architecture decisions
Practical evaluation harnesses and quality gates
Product outcomes over model hype
Clear documentation for handover and scale
Featured Projects
See allReduces schema drift in evolving data pipelines by providing a guided schema validation and migration workflow.
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PECR target implementation repo
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Prevents context loss in complex workflows by modeling entities, links, and retrieval paths as a navigable graph.
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Selected Outcomes
View workPolicy-Enforced Context Runtime
Problem
Teams needed reliable, governed context handling for AI workflows in sensitive environments.
What I Built
Designed a deterministic runtime with policy/time constraints, typed operator controls, and immutable evidence units.
Result
Enabled auditable decision trails and safer production rollouts with clearer go/no-go signals.
PECRSchemaPilot
Problem
Teams struggled to keep evolving schemas consistent across tools, services, and delivery workflows.
What I Built
Built a schema-first workflow for aligning definitions, validation, and implementation touchpoints.
Result
Reduced schema drift and made contract changes easier to coordinate across engineering systems.
SchemaPilotContextGraph
Problem
Context dependencies in AI workflows were hard to trace, explain, and debug at scale.
What I Built
Created a graph-oriented context model to map relationships, surface dependencies, and improve observability.
Result
Improved debugging speed and decision transparency by making context flow explicit and inspectable.
ContextGraphResearch
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Services
Assessment Sprint
1-2 weeks. Audit architecture, risk, and readiness.
Build Sprint
3-6 weeks. Production-ready delivery with measurable quality gates.
Advisor
Monthly strategic and technical guidance for leadership teams.
About
- Experienced in AI systems, technical product strategy, and delivery alignment.
- Focused on measurable impact: lead time, quality, reliability, and user trust.
- Comfortable bridging engineering depth and executive-level communication.
- Available for selective consulting engagements across Europe and remote.
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