AI LAB
Contract Clause RAG: Answer From the Right Clause
Build a project on contract-clause RAG that answers vendor-contract questions grounded in the right clause
Verified Certificate on Successful Completion
What is in it for you?
LLM tokens included
A metered token budget is bundled in, call real models from your code with no API key or extra cost.
AI mentor on tap
Stuck? An in-IDE AI mentor gives hints and debugging help, without handing you the answer.
Instant grading
Submit and get an objective, rubric-based verdict in seconds, pass, or actionable feedback.
Verified certificate
Pass and earn a shareable, verifiable certificate you can add to your LinkedIn profile.
Zero-setup cloud IDE
A ready sandbox with the libraries pre-installed, start building in the browser instantly.
Retry until you pass
Iterate as many times as your budget allows; a fail keeps the lab open to try again.
Grab your slot before the offer expires
Start solving today!
Basic Info
Select Offers
Project Statement
Business Problem
At firms like Clauseworks, associates burn 6-10 hours a week hunting through 40-page vendor contracts to answer routine questions like termination notice periods, initial terms, and late-payment penalties. With hundreds of active contracts and a team of only a dozen reviewers, answers arrive slowly and sometimes cite the wrong clause, exposing the business to compliance and renewal risk.
AI Solution
You'll build an assistant that indexes each contract clause as an embedding in a vector store, retrieves the clauses most relevant to a question, and generates an answer grounded strictly in that retrieved text. Crucially, the assistant quotes the clause it relied on so every answer is auditable and traceable back to the source.
Potential Impact
A grounded, citation-first clause assistant can cut contract lookup time from minutes to seconds, freeing an estimated 6+ hours per associate per week. Teams gain faster, more accurate answers with a verifiable source clause behind each response, reducing misquote risk and lifting reviewer throughput several-fold.
Skills that you will build
Solve a real AI-engineering problem that builds in-demand skills and a portfolio-ready, verified certificate.
.ffb97545.png&w=16&q=75&dpl=dpl_8zM6HG9D1ZAbdMYa1sGJ7PjNFzPo){kind=small}
Chunking documents into retrieval-friendly unitsGenerating and using text embeddingsBuilding an in-memory vector index with FAISSSemantic similarity retrievalGrounding LLM answers in retrieved contextPreventing hallucination via source-quotingDesigning a RAG pipeline end to endAI Lab Pre-requisites
- Comfortable writing Python functions
- Basic understanding of embeddings and vectors
- Familiarity with how LLMs generate text
Target Roles
- AI Engineer
- LLM Application Developer
- RAG Engineer
- AI Solutions Architect
Combo Offers
Most Frequently Bought
🛡 Verified certificate on pass
Super Saver Offer
🛡 Verified certificate on pass
Create Your Own Combo
🛡 Verified certificate on pass
for successfully completing the 'Contract Clause RAG: Answer From the Right Clause' project
Add a Industry Recognized
Project Certificate To Your Resume
Industry Recognized
Project Certificate
Career Advancements
Elevate your career with a respected certificate
Industry Respect
Gain credibility in the field
Networking
Connect with experts and peers
Opportunities
Attract exciting job prospects and promotions
for successfully completing the 'Contract Clause RAG: Answer From the Right Clause' project
Frequently asked questions
Are LLM tokens included?
Yes. The lab runs in a cloud IDE with a metered LLM budget, so you can build and test without your own API keys.
What do I earn on completion?
A verified, shareable credential you can add to your resume or LinkedIn.
Do I need legal knowledge?
No. The contract text is provided; your focus is building the retrieval and grounding pipeline, not interpreting law.
Is this a course with multiple lessons?
No. It's a single focused, hands-on lab where you solve one real problem and get auto-graded feedback.
What if I've never used FAISS?
That's fine. FAISS is available in the environment and this lab is a great way to learn vector indexing by doing.
Will my answers need to cite sources?
Yes. A core skill here is grounding answers in retrieved clauses and quoting the clause you relied on.