Legal RAG with citations
How do you build a legal assistant whose answers remain verifiable down to the cited passage?
3500 € per session, excl. VAT
In short
Two days, comprising 14 hours excluding breaks, to assemble a retrieval-augmented generation prototype using a controlled legal corpus. You prepare the sources, configure retrieval, require verifiable citations and measure errors. The result includes a human validation protocol and a pilot plan, without immediate production-scale deployment.
Why this training?
A plausible legal answer may cite a non-existent clause or an outdated version. Linking each assertion to the correct passage enables the professional to check the reasoning, without confusing the presence of a citation with legal relevance. RAG combines document retrieval with generation. Its quality depends as much on the corpus, metadata and abstention rules as on the model; these components must be tested separately before professional use. Running case study: The fictitious organisation Ordelune Métrologie wishes to query its anonymised supplier contracts. Its training corpus contains amendments, contradictory clauses and superseded versions; answers must identify the applicable passages without deciding on termination. Transfer to the workplace: Subsequently organise a limited pilot: an authorised corpus, designated users, legal review of answers, error tracking and a documented decision to continue, correct or stop.
Objectives of this training
- Define the documentary scope and its exclusions
- Structure chunks and their legal metadata
- Assemble a prototype that produces verifiable citations
- Measure retrieval, answer faithfulness and abstention
- Formalise the conditions for a supervised pilot
Who is it for and what are the prerequisites?
Roles and tasks concerned
- Legal professionals and compliance managers leading technology-enhanced document research
- Data managers and developers supporting a legal department
Prior skills
- Have practical experience of legal research and reading contracts.
- Know the principles of RAG and the uses of generative AI.
- Be able to work with structured files and configure a technical environment.
What you will work on
Define the scope of use
Objective: Set boundaries for legal assistance. Permissible questions, exclusions, supervision; no automated sensitive decisions.
Assess the corpus
Objective: Identify usable sources. Provenance, confidentiality, versions, dates and permissions.
Chunk without losing context
Objective: Preserve the meaning of clauses. Chunks, overlap, annexes, identifiers and pagination.
Configure retrieval
Objective: Retrieve the relevant passages. Lexical and semantic retrieval, document filters.
Assemble answers with citations
Objective: Link assertions to evidence. Provided context, stable references, excerpts and abstention.
Build the benchmark set
Objective: Establish an evaluation benchmark. Answerable questions, ambiguous questions and questions outside the corpus.
Measure quality
Objective: Distinguish categories of errors. Recall of expected passages, citation accuracy, faithfulness.
Test the limits
Objective: Test risky behaviours. Contradictions, missing sources, malicious instructions within documents.
Correct and rerun
Objective: Verify improvements. Retrieval settings, context and instructions; regression checks.
Prepare the pilot
Objective: Establish a framework for the experiment. Access, logging, corpus updates and human review.
What you take away
- RAG prototype and reproducible configuration
- Register of the corpus, versions and metadata
- Annotated evaluation set and error report
- Pilot plan with human validation
Method and assessment
- Short instructional sessions followed by immediate practical work on the running case study.
- Individual work followed by work in pairs, with peer review of the outputs.
- Guided group discussion: what works, what needs correcting and what remains a human decision.
- Preparation: Prepare a fictitious or anonymised corpus with versions and stable reference points. Check access to the tools authorised by the organisation and designate the qualified professional responsible for validation.
Observable criteria: Each citation tested opens the expected document and passage. ; The answers distinguish between clauses, interpretations and uncertainties. ; Numerical results state the method, denominator and observed errors. ; Cases without sufficient source material trigger an explicit abstention from answering. ; The pilot defines responsible parties, acceptance thresholds and stopping conditions..
Frequently asked questions
Is a citation enough to validate an answer?
No: its content, version and relevance must be checked.
Can real contracts be used?
The exercises use only fictitious or anonymised cases, within the authorised tools.
Does the prototype replace a legal professional?
No. The outputs require validation by a qualified professional.
What obligations govern the pilot?
Confidentiality, data protection and terms of use must be checked with your legal department.
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