Evaluation Consulting · Enterprise

RAG Evaluation Consulting

Measure retrieval recall, answer faithfulness, and citations on your questions — then gate every index and prompt change in CI.

Service
Evaluation
Industry
Enterprise
Updated
2026-08-25
Engagement
4 wks
The short answer

RAG evaluation consulting builds a golden set of real questions with verified answers, then measures retrieval hit@k, answer faithfulness, and citation quality, with refuse-when-empty and per-user ACL tests, wired as CI gates in the client cloud — typically a 4-week standard implementation, with the client owning the eval suite and IP.

The premise

If you cannot name hit@k, faithfulness, and citation coverage on a golden set, you are not evaluating RAG. You are demoing it.

Engagement
4 wks
eval harness to CI handover
Golden set
real questions with verified answers
CI
hit@k, faithfulness, citation gates
The path
01Discover
02Design
03Build
04Validate
05Enable

Why teams pick this engagement

Evaluation × Enterprise

ACL-aware evals

Restricted questions are run as the restricted user. A suite that searches as admin will not catch leaks.

Retrieval and generation split

Hit@k is scored before anyone debates the prose. Faithfulness is scored against retrieved context, not against the internet.

Harness in your CI

The suite runs in the client cloud on pull requests. A drop versus the last pin fails the build.

Labeling your people can sustain

Gold passages and answers are written by domain owners with a review queue. We do not leave you a one-off spreadsheet.

Four-week harness

Question sampling, gold labels, metrics, CI wiring, handover. Thirty days on-call for triage.

Citation as a metric

Every answer must point at a span. Missing, wrong, or decorative citations fail the check.

Key takeaways

  • 01

    If you cannot name hit@k, faithfulness, and citation coverage on a golden set, you are not evaluating RAG. You are demoing it.

  • 02

    Split retrieval from generation. Fixing prose will not help if the gold chunk is not in the top 10.

  • 03

    Golden sets plus CI evals are the release control. Offline notebooks that nobody runs on pull requests do not count.

  • 04

    Eval as the asking user. Admin-only suites miss ACL leaks. Refuse-when-empty must have dedicated cases.

  • 05

    Four weeks in your cloud. You own the suite. No shared training. You pay inference for judges and generators. Thirty days on-call.

What the engagement covers

01

Golden Set Construction

Sample real questions, write gold passages and answers with domain owners, stratify identifiers vs paraphrases vs empty-retrieval cases.

02

Retrieval Metrics

Hit@k, MRR, and hybrid-vs-vector deltas on BM25 plus embeddings. Report by source and query class, not a single vanity score.

03

Faithfulness and Citation Checks

Claim-level grounding against retrieved context, citation presence and correctness, refusal tests when retrieval is empty.

04

CI Gates

Suite in your pipeline. Pin metrics. Fail the build on regressions. Model-agnostic judges; you pay inference.

05

Label Ops Handover

Review queue, disagreement protocol, drift sampling. Client owns IP. Thirty days on-call. Fixed-scope plus platform fee.

How we work

  1. 01

    Discover

    Week 1: current evals, question sources, identity for ACL tests, metric targets, written scope.

  2. 02

    Design

    Strata, label schema, retrieval vs generation split, judge protocol, CI placement.

  3. 03

    Build

    Week 2: golden set, harness, traces, and pipeline jobs in the client cloud.

  4. 04

    Validate

    Week 3: shadow scores on the live retriever, inter-labeler checks, gate thresholds.

  5. 05

    Enable

    Week 4: CI live, runbooks, IP handover, 30 days on-call for eval triage.

Take the playbook with you

The working documents from real engagements — free, in exchange for an email. They’re useful whether or not we ever talk.

Flagship resource · XLSX scorecard

RAG Evaluation Scorecard

Score your current RAG evals on golden-set quality, hit@k, faithfulness, citations, refuse-when-empty, ACL tests, and whether they actually run in CI.

Get the scorecard ·
DOCX · 10 pages

RAG Golden Set Labeling Guide

How to write questions, gold passages, gold answers, and identifier strata so labels stay stable across reviewers.

Get the guide ·
PDF · 4 pages

RAG Eval Metric Sheet

Hit@k, faithfulness, citation coverage, refusal-on-empty, and ACL leak tests — definitions we wire into CI.

Get the sheet ·

Frequently asked questions

how do you evaluate a rag system

With a golden set of real questions and verified answers, then separate metrics: retrieval hit@k, answer faithfulness to retrieved context, citation correctness, and behavior on empty retrieval. Run those in CI against the last pin. Evaluate as the asking user so ACL is in the suite. That is RAG evaluation consulting in practice, delivered in four weeks in your cloud.

what is a rag golden set

A versioned list of questions drawn from real use, each with gold passages, a gold answer or refusal, and the user identity that should be allowed to see them. Fifty-plus is a starting point, not a trophy. Identifier questions and empty-retrieval cases must be in it or hybrid retrieval and refuse-when-empty will never be tested. You own the set.

do you use ragas or an llm judge

We use whatever scorer we can pin and reproduce in your CI. LLM-as-judge is allowed if the judge prompt and model are versioned and you pay inference. Unpinned vendor scores are not a gate. Retrieval hit@k does not need a judge. Faithfulness and citations often do. Model-agnostic: we can swap the judge the same way we swap the generator.

what metrics matter for rag

Retrieval: hit@k and the hybrid-vs-vector delta. Generation: faithfulness to retrieved context, citation coverage and correctness, refusal on empty retrieval. Operations: ACL leak tests. Leaderboard scores that ignore your corpus and permissions do not matter. We report by query class so identifier failures cannot hide inside a blended average.

how long does rag evaluation consulting take

Four weeks standard to a CI-wired harness and a first golden set, then 30 days on-call. Labeling capacity is the usual constraint. Financial services typically 8–12 weeks when validation packages are in scope. Healthcare typically 10–14. Ecommerce typically 6–10. Scope is fixed in writing.

can you evaluate a rag system we already built

Yes. Week 1 is an audit of what you measure today. Most teams have a demo notebook and no CI gate. We keep your stack, add the golden set and gates in the client cloud, and hand over IP. We do not require a rebuild unless retrieval or ACL cannot be tested as-is.

who owns the eval suite

You do. Client owns IP: questions, labels, harness, pins, runbooks, in the client cloud. No shared training on your questions. Thirty days on-call for failing gates. After that, label expansion is a new fixed scope. We are not a hosted eval SaaS you cannot export.

how much does it cost

Fixed-scope implementation fee plus platform fee, quoted after we see question volume and whether judges run on every pull request. You pay inference. No token markup. If you only need a labeling guide, we will say so rather than selling a four-week harness you will not run.

Keep reading

AI Agent × Financial ServicesAI Agent Consulting for Financial ServicesConversational AI × HealthcareConversational AI Consulting for HealthcareAI Automation × E-commerceAI Automation Consulting for E-commerceGenerative AI × EnterpriseGenerative AI ConsultingAI Strategy × EnterpriseGenerative AI Strategy ConsultingImplementation × EnterpriseGenerative AI Implementation ConsultingAI Strategy × EnterpriseGenerative AI ROI ConsultingAI Strategy × EnterpriseEnterprise Generative AI Roadmap ConsultingImplementation × EnterpriseGenAI Pilot to Production ConsultingAI Strategy × EnterpriseBuild vs Buy Generative AI ConsultingAI Strategy × EnterpriseFractional AI CTO ConsultingAI Strategy × EnterpriseAI Use Case Discovery ConsultingImplementation × EnterpriseScaling Generative AI in the EnterpriseRAG × EnterpriseRAG ConsultingRAG × EnterpriseEnterprise RAG Implementation ConsultingRAG × EnterpriseAgentic RAG ConsultingRAG × EnterpriseHybrid Search RAG ConsultingKnowledge AI × EnterpriseEnterprise AI Knowledge Management ConsultingKnowledge AI × EnterpriseAI-Powered Enterprise Search ConsultingRAG × EnterpriseGraphRAG ConsultingEvaluation × EnterprisePrevent LLM Hallucinations ConsultingRAG × EnterpriseAI Document Q&A Generative AI ConsultingAI Agent × EnterpriseAI Agent ConsultingAI Agent × EnterpriseAgentic AI ConsultingAI Agent × EnterpriseMulti-Agent Orchestration ConsultingAI Agent × EnterpriseMCP Agent ConsultingAI Agent × EnterpriseCopilot vs Agent ConsultingAI Agent × EnterpriseComputer Use Agent ConsultingConversational AI × EnterpriseVoice AI Agent ConsultingAI Agent × Customer ServiceCustomer Support AI Agent ConsultingAI Automation × EnterpriseAI Workflow Automation ConsultingAI Agent × EnterpriseAutonomous AI Agents for the EnterpriseEvaluation × EnterpriseLLM Evaluation ConsultingGovernance × EnterpriseLLM Governance ConsultingGovernance × EnterpriseAI Risk Management ConsultingGovernance × RegulatedEU AI Act Compliance ConsultingLLM Platform × EnterprisePrivate LLM ConsultingLLM Platform × EnterpriseOn-Prem LLM Deployment ConsultingSecurity × EnterpriseLLM Security and Red Teaming ConsultingLLM Platform × EnterpriseLLM Model Selection ConsultingLLM Platform × EnterpriseFine-Tuning vs RAG ConsultingImplementation × EnterpriseEnterprise Prompt Engineering ConsultingGenerative AI × LegalGenerative AI Consulting for LegalGenerative AI × HealthcareGenerative AI Consulting for HealthcareGenerative AI × InsuranceGenerative AI Consulting for InsuranceGenerative AI × ManufacturingGenerative AI Consulting for ManufacturingGenerative AI × HRGenerative AI Consulting for HRGenerative AI × MarketingGenerative AI Consulting for MarketingGenerative AI × SalesGenerative AI Consulting for SalesAnalytics AI × EnterpriseText-to-SQL ConsultingCode AI × TechnologyAI Code Generation ConsultingDocument AI × EnterpriseIntelligent Document Processing ConsultingLLM Platform × EnterpriseChatGPT Enterprise Implementation ConsultingLLM Platform × EnterpriseMicrosoft Copilot ConsultingImplementation × EnterpriseCustom GPT ConsultingLLM Platform × EnterpriseLLMOps ConsultingLLM Platform × EnterpriseAI Cost Optimization ConsultingImplementation × EnterpriseContext Engineering ConsultingEnablement × EnterpriseAI Change Management ConsultingAI Search × MarketingGenerative Engine Optimization ConsultingData × EnterpriseData Readiness for Generative AI ConsultingLLM Platform × EnterpriseAI Observability Consulting

Ready to bring evaluation to enterprise?

Book a scoping call — we'll map your highest-ROI use case, the controls it needs, and a realistic path to production in the first conversation.

Copyright © 2026
ReinforcedX, Inc.
All rights reserved