Legal is the department that can stop a business transaction cold. A contract goes into review and two weeks disappear. Procurement waits. Sales waits. And the tools that were supposed to fix that — an assistant bolted into Word, a chat window with a contract pasted into it — ask an in-house lawyer to trust a system that can give one answer today and a slightly different answer next week. In a field where the human carries the liability and the model does not, that is not a rounding error. That is the whole problem.
In this episode of Talking AI, Matt Paige sits down with Emad Khazraee, co-founder and CTO of RiskVantage AI, previously VP of AI at Xometry, a data science and AI leader at Turing, an information science professor, and a fellow at Harvard’s Berkman Klein Center. For years Emad told his co-founder, Mark Afshar — a practicing lawyer turned in-house counsel for big pharma — that legal AI was a bad idea: a wrapper has no moat, and Anthropic or OpenAI will do it better than you overnight. What changed his mind was an architecture, not a market: a deterministic ontology that owns the legal reasoning, and small domain-specific language models that handle the language.
The conversation covers why a nine-billion-parameter model running sub-second on a commodity GPU can match a frontier model inside a single domain, how subsidized token prices are distorting the entire legal AI market, why RiskVantage AI sells to procurement and sales ops rather than to lawyers who bill by the hour, what a failed PhD project on symbolic AI taught him about where determinism belongs, and whether the billable hour survives the decade.
In this episode, you’ll hear about:
- What ChatGPT can’t know about your company: its risk appetite, its baselines, and the practices it expects every single time
- Why the legal services market — north of $900 billion, by Emad’s count — has every frontier lab gunning for it
- The objections that made him refuse to build a legal AI company, and the one that still holds
- Why a Word plugin stopped being defensible the moment Anthropic shipped its own
- How subsidized token pricing echoes Uber and Lyft, and who gets hurt when the subsidy ends
- The consistency problem: one answer today, a different answer next week, and a lawyer’s confidence gone
- Neuro-symbolic AI in plain English — a deterministic ontology for legal risk, LLMs for document understanding
- The three years Mark Afshar spent codifying legal risk before there was a product
- Why a 9B domain-adapted model is “dumb enough” that it can’t wander outside its sandbox
- Knowledge distillation, silver datasets, and self-distillation policy optimization in practice
- The sovereign-cloud niche: ITAR data, commodity GPUs, and customers whose data will never leave
- Outcome-based pricing, AI-enabled law firms, and what happens to the billable hour
- The access-to-justice case: pro se filings, public defenders, and what a $20 subscription changes
Key Moments
- 00:01:30 — What ChatGPT can’t know: your company’s risk appetite and baselines
- 00:05:12 — $700 an hour, a tenth at a time — and Coinbase’s AI mandate to outside counsel
- 00:08:12 — Why he told his co-founder no: a wrapper has no moat
- 00:10:22 — Subsidized tokens, Uber and Lyft, and Legora’s move to consumption pricing
- 00:14:31 — The sovereign-cloud niche: ITAR data, commodity GPUs, and data that can’t leave
- 00:16:56 — “I am on the hook for the liability, not which model I used”
- 00:18:15 — Same question a week later, a different answer, and confidence gone
- 00:22:13 — If a rule can govern it, you should never use an LLM
- 00:23:00 — The PhD failure: narrative machines, Frege, and symbolic AI’s rigidity
- 00:26:53 — Mark Afshar’s three years codifying legal risk into an ontology
- 00:29:00 — Neuro-symbolic AI, explained
- 00:31:03 — Don’t use a missile to hit a fly: why smaller models are safer
- 00:35:47 — A 9B model, sub-second on a commodity GPU, matching Fable 5 in-domain
- 00:38:00 — Does the billable hour survive? Outcome pricing and AI-enabled firms
- 00:42:40 — Why affordable legal access is a democratic-society problem
- 00:44:00 — The pro se surge: people filing their own cases with ChatGPT and Claude
- 00:48:30 — “I’m talking with Copilot.” “That’s not research.”
Key Links