The session began with a resonant comparison: a general-purpose LLM is similar to a talented law student. It is knowledgeable, articulate, and efficient, but lacks experience with prosecution, familiarity with firm-specific client guidelines, and understanding of the stakes involved in each matter.
A platform designed for the complete patent workflow is distinguished by several key factors:
Additionally, the AI’s style should be customizable by attorney, matter, jurisdiction, and specific client instructions. Firms prefer a platform that reflects their unique practice, rather than a single, uniform voice.
Currently used by thousands of practitioners at over 700 in-house and IP firms, Solve Intelligence focuses on the entire patent lifecycle, rather than a single point solution. Solve Intelligence supports:
For all of these workflows, the AI output includes clickable citations linking to the relevant source document. For attorneys, this traceability distinguishes a tool suitable for experimentation from one that can be relied upon in practice.
A key topic was how firms measure the return on their AI investments. Among approximately 700 firms using Solve Intelligence, attorneys consistently reallocate time saved by AI to higher-value work, advanced claim drafting strategy, portfolio cross-sell analysis, and client-facing IP insights, rather than simply increasing workload.
One team that adopted Solve Intelligence mid-fiscal year exceeded their billing targets by $1 million. However, software alone is not sufficient; effective change management is equally important. Successful adoption typically follows three stages:
Approximately 35% of Solve Intelligence’s team are fully qualified patent attorneys and agents dedicated to customer deployment and training, where ROI is ultimately realized.
Security was discussed as a critical factor for adoption, not merely a compliance requirement. Solve Intelligence’s infrastructure aligns with the standards law firm IT teams now expect:
A significant shift is driven by clients. In-house legal teams increasingly require outside counsel to use AI tools, and some are selecting firms based on their AI capabilities. AI fluency is now becoming a selection criterion rather than a differentiator.
FICPI’s ABC Nashville meeting demonstrated that patent attorneys are no longer debating whether to adopt AI. Instead, they are focused on identifying platforms that meet the rigorous demands of their work and on effective implementation. This is the core conversation Solve Intelligence seeks to address.
Looking ahead 6 to 12 months, a few shifts stood out from the discussion:
General-purpose models are trained broadly and reason well, but they lack grounding in legal doctrine, access to technical guidelines and case law databases, and the confidentiality standards firms are required to maintain. A specialized platform adds that legal-specific layer on top, along with jurisdiction-aware formatting so outputs are actually usable in practice, not just plausible-sounding text.
Solve Intelligence spans invention disclosure analysis, prior art search, claim drafting, office action response, SEP and standards analysis, portfolio-level infringement detection, and biotech/chemistry-specific claim support, with cross-jurisdiction prosecution history informing new work throughout.
Data is encrypted in transit and at rest, never used to train models, and sandboxed per user, enforced at the matter level. Firms can choose data residency in the US or EU, and the platform’s security has been reviewed and approved by law firm IT teams under SOC 2 Type II, ISO 27001, and enterprise-grade standards.
Across roughly 700+ firms and in-house teams, the consistent pattern is that attorneys reallocate the time AI saves toward higher-value work, deeper claim strategy, portfolio cross-sell analysis, and client-facing insight, rather than simply increasing volume. Change management is treated as equally important as the software, with adoption typically moving from initial appetite to internal champions driving peer use.
