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I will debug llm apps, ai agent, llm observability, ai evals
Brenda J
About this gig
Your LLM app or AI agent works great in testing until real users show up.
Suddenly you're dealing with hallucinations, broken tool calls, flaky chains, and inconsistent outputs. You patch one issue, another appears. That's not scalable.
The fix isn't more vibe checks.
Its AI evals + LLM observability.
I provide AI Technology Consulting to debug LLM apps, stabilize AI agents, and make your system production-ready using structured evaluations and deep observability so failures become predictable, measurable, and fixable.
What I'll set up for you:
- Debug LLM apps with full error logs & eval harness
Log every prompt, tool call, and response, catch issues before users do
- AI evals using LLM judges + code checks
Binary pass/fail signals validated against human data
- LLM observability
Tracing, latency & cost dashboards, alerts, and drift detection
- AI agent debugging & remediation
Root-cause clustering and clear playbooks to fix what is breaking
- Future-ready systems
Your next product version trains on real failure data, not guesses
The result:
A reliable, scalable, production-grade AI agent you can actually trust.
Let's make your AI product stable, observable, and ready for real users
Get to know Brenda J
Brenda J
- FromUnited States
- Member sinceDec 2024
- Avg. response time3 days
- Last delivery3 months
Languages
English, French, German, Spanish
Hello creative sellers on online space. Are you looking to create a strong online presence by creating a professional and well branded store on Etsy and other platforms? Look no further for you are welcome to my workspace.
With about a decade of experience setting up store, designing quality digital and print on demand products for tens of stores and also implementing the right marketing strategies that has improved their sales progress, I have maintained a high success track stores that has seen product brands grow tremendously.
Ready to start your journey to success? Contact me now
My Portfolio
FAQ
Which AI stacks do you support?
OpenAI, Claude, Qwen, OpenRouter, LangChain, LangGraph, LlamaIndex, custom agents—plus OpenTelemetry-style, Weights and Biases, Braintrust.dev tracing for debugging.
How do you get "ground truth" to test against?
Three sources: (1) Curated gold-standard examples from your domain experts. (2) Synthetic test cases we generate for edge cases. (3) Real production logs—especially failures—fed back into the test suite. The best datasets are living, not static.
Why do I need this—isn't the AI model already good enough?
Models fail silently. Evals catch hallucinations, PII leaks, cost spikes, and edge-case failures before users see them. You'll ship safer and fast
What's the fastest way to see ROI?
Week 1: Catch a critical bug before launch (prevents customer escalation). Month 1: Cut debugging time by 40%+ with trace graphs showing exactly where agents fail. Month 3: Ship new model updates in days instead of weeks, beating competitors to market.
How is this different from just "testing my prompts"?
Modern AI systems aren't just prompts—they're agents with tools, multi-step reasoning, and dynamic context. We evaluate the entire system: your prompts, tool definitions, tool outputs, data quality
How do you know if the evals are actually working?
Three signs: (1) You can ship new AI models in under 24 hours with confidence. (2) User complaints turn into test cases instantly. (3) You use evals offensively—to predict which features will work when better models drop—not just defensively to cat
