You will get RAG Evaluation - Hallucination Certificate + Taxonomy + Receipt - NOTH v3.1
Project details
RAG Evaluation - Production-Grade Hallucination Measurement + Taxonomy + Receipt - NOTH v3.1
PROBLEM (Sep 2026): RAG still hallucinates 33% even with retrieval. 42% of AI projects failed in 2025 ($13.8B at risk). RAG evaluation platform market $1.99B.
WHAT I DO: Offline, deterministic, no external calls, PII-scrubbed (emails/phones/IDs), hash-locked evaluation of your 50-2000 rows RAG dataset (question, context, llm_answer).
DELIVERABLES (all deterministic, replayable):
OUT_A Certificate: fail rate, hallucination count, grounding gap, PII PASS
OUT_B Failure Slices: taxonomy - Context Misalignment, Missing Citation, Entity Swap, Numeric Hallucination
OUT_C Runnable Receipt: JSON log with hash/timestamp/trace - replay with D:\python3.11\NORD2.0\run_all.py
OUT_E Fix-It READY TO UPLOAD: corrected rows for fine-tuning
No live DB connection. You send CSV, I run offline. Measurement only, not removal. For due diligence/VC board/enterprise guard, not formal SOC2 audit. Image shows AUDIT wording but deliverable is EVALUATION certificate per new title - same NOTH v3.1 protocol.
Starter 50 rows 1d $249 | Standard 200 rows 3d $1499 | Advanced 500 rows 7d $3500
PROBLEM (Sep 2026): RAG still hallucinates 33% even with retrieval. 42% of AI projects failed in 2025 ($13.8B at risk). RAG evaluation platform market $1.99B.
WHAT I DO: Offline, deterministic, no external calls, PII-scrubbed (emails/phones/IDs), hash-locked evaluation of your 50-2000 rows RAG dataset (question, context, llm_answer).
DELIVERABLES (all deterministic, replayable):
OUT_A Certificate: fail rate, hallucination count, grounding gap, PII PASS
OUT_B Failure Slices: taxonomy - Context Misalignment, Missing Citation, Entity Swap, Numeric Hallucination
OUT_C Runnable Receipt: JSON log with hash/timestamp/trace - replay with D:\python3.11\NORD2.0\run_all.py
OUT_E Fix-It READY TO UPLOAD: corrected rows for fine-tuning
No live DB connection. You send CSV, I run offline. Measurement only, not removal. For due diligence/VC board/enterprise guard, not formal SOC2 audit. Image shows AUDIT wording but deliverable is EVALUATION certificate per new title - same NOTH v3.1 protocol.
Starter 50 rows 1d $249 | Standard 200 rows 3d $1499 | Advanced 500 rows 7d $3500
Machine Learning Tools
PyTorch, TensorFlowWhat's included
| Service Tiers |
Starter
$249
|
Standard
$1,499
|
Advanced
$3,500
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Scenarios | 50 | 200 | 500 |
Number of Graphs/Charts | 3 | 5 | 10 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | - |
Source Code |
Frequently asked questions
About Nagendra
RAG Evaluation Specialist - NOTH Protocol v3.1 - Hallucination Measure
Bangalore, India - 12:30 pm local time
PROBLEM (Sep 2026): RAG still hallucinates 33% even with retrieval. Legal research tools proven to hallucinate up to 33% (Towards AI Sep 2026). 42% AI projects failed in 2025 ($13.8B at risk). Market $1.99B.
WHAT I DO: Production-grade, offline evaluation of 50-2000 rows RAG dataset. Auto-detect columns (query, context/retrieved_docs, model_response, ground_truth), scrub PII offline (emails/phones/IDs), hash-lock for deterministic replay, validate schema. Zero external calls.
DELIVERABLES:
- OUT_A Executive Certificate: fail rate, grounding gap, taxonomy
- OUT_B Failure Slices: missing citations, entity swaps
- OUT_C Runnable Receipt: deterministic replay, hash-locked
TIERS: Starter $249 (50 rows, 1 day, 3 charts) | Standard $1499 (200 rows, 3 days, 5 charts) | Advanced $3500 (500 + custom 2000, 7 days, 10 charts)
STACK: Python, PyTorch, TensorFlow, NOTH v3.1, LLM Eval, Hallucination Detection, RAG Grounding
BACKGROUND: 19+ years Oracle & SQL Server Design & Dev - Now focused on RAG Hallucination Measurement. BASc Computer Science Bangalore University 1992-1995.
Offline, deterministic, no external calls, PII-scrubbed, hash-locked.
Steps for completing your project
After purchasing the project, send requirements so Nagendra can start the project.
Delivery time starts when Nagendra receives requirements from you.
Nagendra works on your project following the steps below.
Revisions may occur after the delivery date.
Ingestion & PII Scrub
Import 50-500 rows offline, auto-detect columns, scrub PII (emails, phones, IDs), hash-lock for deterministic replay, validate schema. No external calls.
RAG Audit & Failure Detection
Run NOTH Protocol v3.1 offline audit - detect hallucinations, grounding gaps, missing citations, entity swaps, numeric errors. Generate fail rate and trace log with hash.