Mayia gives law firms a firm-owned knowledge layer (clients, matters, positions, workflows) that automatically feeds the right context into the LLMs they already use, so every AI interaction starts informed instead of from zero
Mayia gives law firms a firm-owned knowledge layer (clients, matters, positions, workflows) that automatically feeds the right context into the LLMs they already use, so every AI interaction starts informed instead of from zero. Most legal AI companies compete on workflow execution (drafting, review, research). That layer is already commodity: every capability gets absorbed into foundation models within a couple of release cycles. The real incumbent isn't Harvey or Legora, it's 'Claude with some documents attached.' Lawyers already get decent output from general LLMs. The actual pain is that every session starts from zero, and the lawyer manually shuttles context in. The durable asset is a structured, firm-owned record of that knowledge that compounds with use. The record has to be explicit and human-confirmed (not silently inferred), because professional secrecy and GDPR make 'the AI watched you and remembered' a non-starter for European firms. And it has to be portable and owned by the firm, not held inside a vendor's platform. Mitchell has product and applied AI experience, built KiKi end-to-end as CEO, and ran an AI automation consultancy focused on getting context into models. Co-founder Michiel is a practising Belgian IT lawyer who lived the problem daily. CTO Amir builds the graph layer. The team combines legal domain depth, product thinking, and AI engineering. Mitchell demonstrated at KiKi that he can solve hard distribution problems outside the product itself (seeding the app through real-world events and business partnerships), and he's applying the same approach to Mayia. The legal AI market is exploding: Harvey raised at $11B and Legora at $5.6B, but all that capital is pointed at the workflow layer, which Mitchell argues commoditizes into foundation models. The more telling signal is buyer behaviour: Kirkland & Ellis is reportedly spending $500M building its own AI and refuses to sell it. When the most profitable law firm in the world treats its AI-plus-knowledge stack as proprietary infrastructure, that confirms the thesis that the firm's knowledge layer is the asset and firms want to own it. Kirkland can afford $500M; the other 99% of firms can't build this themselves.