SmartDuke builds rag systems for legal and compliance teams — systems that ground AI answers in your own data, with citations and freshness guarantees. AI-augmented attorneys are 3–5x faster on review work. The firms that adopt now get the efficiency advantage; the ones that don't get squeezed. Our approach: Retrieval evals before any LLM call, citation-rate monitored as a first-class metric, and explicit refusal when confidence falls below threshold.
The problems
we keep solving.
AI-augmented attorneys are 3–5x faster on review work. The firms that adopt now get the efficiency advantage; the ones that don't get squeezed.
Document review consumes associate time
Discovery and contract review are the biggest billable-but-low-leverage categories in most practices.
Legal research is precedent-heavy and slow
Finding the right cases, statutes, and clauses takes hours that could be minutes with the right AI infrastructure.
Contract analysis at scale is unstaffable
Reviewing thousands of contracts for renegotiation or compliance changes is rarely worth the headcount cost — until AI changes the math.
Three things we'd build
first.
Concrete starting points for rag systems in legal and compliance teams. We pick the one with the highest leverage and the cleanest measurement story.
- Idea 01
Document-review agent that flags clauses, risks, and inconsistencies with citations to source language
- Idea 02
Contract-clause copilot inside the drafting tool, suggesting standard language and flagging deviations
- Idea 03
Legal-research RAG with jurisdiction-aware retrieval and explicit precedent attribution
Production-grade,
from day one.
Hybrid retrieval (BM25 + semantic + reranker), source-priority ranking, freshness gating, and answer-capsule generation with sentence-level citations.
Evals before launch.
Every loop, tool call, and structured output is graded with a frozen test set and an explicit rubric. Failed evals block the deploy.
Telemetry from day one.
Traces, latency budgets, token costs, and error rates wired up before the first user touches the system.
Guardrails as architecture.
Input validation, output verification, escape hatches, and human handoff paths designed in — not bolted on after incidents.
Boring stack on the edges.
Cutting-edge model in the middle. Reliable infrastructure around it. Stability where it earns its place.
- ×Hallucination on long-tail queries
- ×Stale documents silently used
- ×Missing or wrong citations
- ×Retrieval that fails on the queries that matter most
Common questions.
01How long does it take to build rag systems for Legal?
How long does it take to build rag systems for Legal?
Discovery is one week. A working prototype (Spark) is 2–3 weeks. Full production Build for legal and compliance teams typically runs 8–12 weeks depending on data complexity, integrations, and compliance scope. We commit to a precise timeline at quote stage.
02What does pricing for rag systems typically look like?
What does pricing for rag systems typically look like?
Every engagement is scoped to outcomes, not hours. Discovery starts in the low four figures. Spark and Build are priced per project. Embed retainers are monthly. We return a quote within 24 hours of inquiry.
03Can you take over an existing RAG project that's stalled?
Can you take over an existing RAG project that's stalled?
Yes — it's a common engagement. We review what's there, tell you honestly what stays and what we'd rebuild, then ship it to production. Legal engagements often start this way.
04What's different about your approach to rag systems?
What's different about your approach to rag systems?
Retrieval evals before any LLM call, citation-rate monitored as a first-class metric, and explicit refusal when confidence falls below threshold. We hold the same engineering bar across every engagement, regardless of industry — but the specifics for legal and compliance teams are tuned to your trends and pain points.
Same capability, different industry.
Same industry, different capability.
Have an AI product
that needs to ship?
Tell us where you are — early concept, broken prototype, or scaling something that already works. We'll come back within 24 hours with a take and a quote.