There is a line between experimenting with AI and practicing law with it.
Threshold takes legal teams across it — from scattered ChatGPT experiments to firm-wide infrastructure. Without the hype, the risk, or the wasted pilots.
Most firms have tried AI.
Few have a strategy.
The gap between a ChatGPT experiment and a defensible, firm-wide AI capability is larger than vendors suggest.
And the cost of getting it wrong is measured in client trust, not just dollars.
AI adoption is not a technology problem. It is a trust problem.
The firms that succeed treat AI like a first-year associate — capable but unverified, useful but supervised, and never turned loose on client work without a review layer.
Pilots that cannot be measured should not be run.
If you cannot define what success looks like before you start, you will declare victory based on enthusiasm instead of evidence.
The biggest risk is not AI getting it wrong. It is AI getting it wrong confidently.
The gap between a plausible answer and a correct one is where malpractice lives.
Three ways in.
Custom AI workflows
Intake, research, and drafting pipelines built around verification — designed for how your matters actually move.
- — CLIENT INTAKE TRIAGE
- — RESEARCH WITH CITATION CHECKS
- — FIRST-DRAFT SYSTEMS
Tool selection & implementation
The vendor landscape, minus the vendor incentives. We run the evaluation so you buy what holds up in practice.
- — STRUCTURED VENDOR BAKE-OFFS
- — SECURITY & PRIVILEGE REVIEW
- — PHASED ROLLOUT
Training & workshops
From partner-level fluency to associate-level skill — hands-on sessions built for each practice group.
- — PRACTICE-GROUP WORKSHOPS
- — PROMPT PLAYBOOKS
- — USE POLICY & ETHICS TRAINING
Audit. Prove. Build.
Workflow audit
We map your existing workflows against AI readiness. You get a prioritized implementation plan grounded in how your teams actually work.
Pilot design & evaluation
We design controlled pilots with measurable success criteria — and build the evaluation frameworks to know whether they actually worked.
Infrastructure & integration
We build the internal systems — prompt libraries, verification layers, human-in-the-loop gates — that make AI safe enough to trust with client work.
Proof over promises.
From vendor shortlist to a defensible go decision — in one quarter.
The practice group had three AI review tools under informal trial, no evaluation criteria, and partners split on whether any of it belonged near client documents. Sound familiar?
We ran a structured bake-off against their real matter data, built the evaluation framework — recall against a human-coded baseline, citation verification, privilege-handling checks — and designed the pilot as a controlled experiment with a defined go/no-go gate. The committee made the call on evidence, not vendor demos.
AI-assisted document review pilot, from vendor selection through go/no-go evaluation.
Firm-wide AI adoption strategy and policy framework.
Custom prior-art search workflow integrating LLM extraction with existing patent databases.
Contract review automation with human-in-the-loop verification architecture.
Deposition preparation tools and AI-assisted case timeline construction.
Asked and answered.
Does using AI put privilege or confidentiality at risk?+
Not if it's architected correctly. That means enterprise agreements with zero-retention terms, no training on your data, and matter-level access controls — plus a clear policy on what never goes into a model at all. We review vendor terms and data-processing agreements before anything touches client information.
What about hallucinations? We've all seen the sanctions stories.+
Every sanctions story shares the same failure: no verification layer. Our systems treat every citation and factual claim as unverified until checked against a source, and nothing reaches work product without human sign-off. The lawyers in those headlines skipped the step we build first.
How does this square with the billable hour?+
AI shifts where the hours go — it doesn't erase the value. Firms redirect recovered time to higher-value work, price routine matters on fixed fees with better margins, or take on capacity they'd otherwise turn away. We model the economics with you before rollout, so pricing follows strategy instead of panic.
Do we have to tell clients we're using it?+
Increasingly, clients ask first — AI questionnaires are showing up in RFPs and outside-counsel guidelines. We help you draft disclosure language and use policies so the answer is a documented "yes, with controls" rather than an awkward silence.
What happens when the courts or the bar change the rules?+
Standing orders and ethics opinions are moving targets — which is exactly why policy belongs in the infrastructure, not in a memo. We map your use policies to ABA Formal Opinion 512 and jurisdiction-specific orders, so a rule change is a configuration update, not a rebuild.
Cross the threshold.
A 30-minute conversation about where your firm is, where the line sits, and what it would take to get across it. No deck, no pitch.