I will audit and fix your rag chatbot giving wrong or hallucinated answers


About this gig
Your RAG chatbot returns confident answers that are wrong. The problem is almost never the model.
In most broken retrieval systems, the failure is upstream: bad chunking, weak embeddings, no re-ranking, or a retrieval step nobody ever measured. Swapping to a bigger LLM won't fix it, and it's expensive.
I'm a Ph.D. AI architect with 12+ years building production LLM and ML systems for enterprise clients in regulated industries. 5 awarded AI patents. I've architected retrieval pipelines that had to be right, not just impressive in a demo.
What you get:
Root-cause analysis of why retrieval is failing
Retrieval quality measured with real metrics (recall, precision, nDCG) not vibes
Chunking and re-ranking analysis with tested alternatives
A prioritized fix list, highest impact first
Plain-English findings your engineers can act on immediately
What I need from you: your document corpus (or a representative sample), example questions that fail, and read access to your current pipeline or a description of it.
Every deliverable is a written report you keep. No lock-in, no retainer.
Message me with what's breaking, and I'll tell you honestly whether I can help.
Get to know Dr. Allard
Director, AI Solutions Platform Architect
- FromUnited States
- Member sinceJan 2025
- Avg. response time2 hours
Languages
English
FAQ
Do you need access to our production system?
No. I work from a representative sample of your document corpus plus a list of questions that fail. If you'd rather not share documents, I can work from a redacted or synthetic set that mirrors your structure. I'm happy to sign an NDA before you send anything.
Will you fix the problem or just tell me what's wrong?
This gig delivers a diagnosis and a prioritized fix plan your engineers can implement. Premium includes architecture redesign and an evaluation framework. If you want hands-on implementation, message me and we'll scope it separately.
What if the problem isn't retrieval?
Then I'll tell you that, and where it actually is — prompt design, model choice, data quality, or chunking upstream of retrieval. The audit follows the evidence. You get the real answer, not a predetermined one.
We're not sure our system counts as "RAG." Is this still relevant?
If you built a chatbot that answers questions from your own documents, it's RAG whether or not you called it that. Message me a short description, and I'll confirm fit before you order.
What format is the deliverable?
A written report — findings, metrics, root causes, and ranked recommendations — plus a consulting call to walk through it. The report is yours to keep and share internally.
Do you work with sensitive or regulated data?
Yes. I've built AI systems under HIPAA, CJIS, and SOC 2 constraints. I can work entirely from redacted or synthetic data if compliance requires it, and I'll sign an NDA on request.

