You will get a System Where Your PMs Fix AI Quality Without Dev Tickets
Project details
Your PM knows your AI gives wrong answers. Your support lead catches the hallucinations. But every fix requires a developer ticket, a sprint, and a deploy.
I set up LangSmith so your domain experts — PM, support lead, sales manager — can review AI outputs, annotate quality, and improve prompts through the UI. No code, no sprint, no developer bottleneck.
Built this at Structed.ai: LangGraph agents in production, domain experts in the loop. Now available as a service.
Includes: LangSmith project hierarchy, domain-specific evaluators, annotation workflow, Prompt Hub onboarding, quality dashboard, and Slack alerts.
Stack: LangGraph, LangChain, LangSmith. Delivery: 2–3 weeks.
I set up LangSmith so your domain experts — PM, support lead, sales manager — can review AI outputs, annotate quality, and improve prompts through the UI. No code, no sprint, no developer bottleneck.
Built this at Structed.ai: LangGraph agents in production, domain experts in the loop. Now available as a service.
Includes: LangSmith project hierarchy, domain-specific evaluators, annotation workflow, Prompt Hub onboarding, quality dashboard, and Slack alerts.
Stack: LangGraph, LangChain, LangSmith. Delivery: 2–3 weeks.
AI Algorithms
Large Language ModelAI Applications
AIOpsAI Development Language
PythonAI Models
ChatGPTWhat's included $5,500
These options are included with the project scope.
$5,500
- Delivery Time 14 days
- Number of Revisions 1
- MLOps
- Model Monitoring
- Prompt Engineering
Frequently asked questions
About Denys
Fractional CTO | AI Systems Architect | Early-Stage Tech Leadership
Palm Coast, United States - 5:05 am local time
Available for:
- Fractional CTO (paid retainer, 1–2 startups at a time)
- Technical co-founder / CTO partnership (equity-based, right early-stage product)
What I bring:
- Technical architecture decisions (not just code review)
- AI integration strategy - LangGraph, RAG, LangSmith, agent pipelines, production AI systems
- Engineering team building - first hires, onboarding, defining standards
- Roadmap from prototype to production (I've been on both sides of that gap)
LLM Observability & LangSmith:
If your LangChain/LangGraph agents are in production (or heading there), I set up proper observability: tracing, evaluations, cost monitoring, and alert rules. I run this exact setup at Structed.ai. Available as a standalone engagement (1 week, $1,500–3,500) or as part of a broader CTO engagement.
My background:
- Structed.ai (current): Co-founder & CTO, building an AI Discovery Agent from zero - NestJS, FastAPI/LangGraph, PostgreSQL, Docker
- BigPanda: backend platform connecting 200+ enterprise monitoring tools (Datadog, ServiceNow, PagerDuty), 40+ microservices, real-time incident correlation at scale
- Autodesk: modernization of checkout & billing platform - revenue-critical infrastructure serving millions of subscribers globally
I work with founders who need someone to answer: "Is our architecture right for where we're going?" and "Who's going to make the technical calls while we're figuring this out?"
Entry points:
- Tech Snapshot (2 days, $500–800) - quick written verdict on your stack
- Architecture Audit (2 weeks, $2,500–5,000) - full report + 90-day roadmap
Ongoing: Monthly Advisor retainer for continued CTO-level guidance.
Who this works for: Pre-seed / seed stage, B2B SaaS or AI product, non-technical CEO, 1–5 engineers.
Send me a message with where you are technically and where you need to get to.
Steps for completing your project
After purchasing the project, send requirements so Denys can start the project.
Delivery time starts when Denys receives requirements from you.
Denys works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & stack audit
Review your codebase, map the agent pipeline, identify observability gaps and domain quality criteria.
LangSmith setup + tracing
Configure LangSmith project hierarchy, integrate tracing into your codebase, set up cost and latency monitoring.