For AI tools that fundamentally alter workflows, a simple software deployment is insufficient. Success requires a dedicated team of 'forward deployed' experts (e.g., ex-lawyers for legal tech) to manage the enormous change management undertaking, ensuring adoption and proficiency across the client organization.
In specialized AI verticals like legal tech, market dynamics are extremely skewed. The top player is expected to capture 90% of the market, leaving scraps for all other competitors. This necessitates an aggressive growth strategy focused solely on achieving leadership, as there's no prize for second place.
Legora pivoted its core model provider from OpenAI to Anthropic, driven by a strategic belief that Anthropic is aligning more with enterprise-grade needs while OpenAI is increasingly targeting the B2C market. This signals a potential bifurcation in the foundation model landscape based on end-market focus.
Despite high-profile deals, enterprise customers in nascent AI categories are not yet loyal. They are signing short (1-3 year) contracts and treating vendors as an 'extended pilot' or a 'call option on AI.' This indicates the market remains fluid, and incumbency is not yet a strong moat for early leaders.
Legora has successfully scaled its product organization by hiring former YC founders to lead autonomous 'pods.' This strategy leverages the fact that founders excel in environments with high ownership and delegated responsibility, allowing them to operate their product area like a mini-startup and maintain development velocity.
Early-stage AI startups should resist spending heavily on fine-tuning foundational models. With base models improving so rapidly, the defensible value lies in building the application layer, workflow integrations, and enterprise-grade software that makes the AI useful, allowing the startup to ride the wave of general model improvement.
After raising $35M, Legora's CEO made the bold decision to halt all sales for six months. This time was used to refactor the product for enterprise-level reliability and scale, preventing churn and enabling the company to later onboard thousands of users per day. This prioritizes technical foundation over short-term revenue.
AI is predicted to be the primary catalyst for a dramatic consolidation of the legal market. Firms that effectively leverage technology will gain significant competitive advantages, leading to market share capture and private equity-backed roll-up strategies. The landscape of 200 top US law firms could shrink to just 12-20 dominant players.
AI startups often use traditional per-seat pricing to simplify purchasing for enterprise buyers. The CEO of Legora admits this is suboptimal for the vendor, as high LLM costs from power users can destroy margins. The shift to a more logical consumption-based model is currently blocked by the buyer's operational readiness, not the vendor's preference.
European founders can de-risk US expansion by proving they can sell to and serve top-tier American enterprise clients from abroad. Legora's CEO set a goal to sign two 'AMLA 200' law firms from Europe first. Achieving this validated their GTM strategy and gave them the confidence to invest in a physical US presence.