Instead of an attorney spending days manually searching patent databases, AI agents do the heavy lifting in minutes and keep improving with each round of feedback.

Stilta deploys specialized AI agents that orchestrate multi-step prior art searches across global patent databases (e.g., USPTO, EPO, WIPO). Each agent handles a subtask—query expansion, semantic matching, citation graph traversal, and relevance ranking—coordinated by an orchestrator agent that synthesizes findings into a structured report. The system uses retrieval-augmented generation (RAG) to ground LLM outputs in authoritative patent text, reducing hallucination risk. Attorneys interact iteratively: they review initial results, refine search parameters in natural language, and the agents re-execute with updated context. Claim-level analysis agents parse independent and dependent claims, map them against prior art references, and flag potential novelty or obviousness issues. The architecture supports jurisdiction-specific search strategies and integrates knowledge graphs that capture patent family relationships, inventor networks, and technology taxonomies. Continuous feedback loops allow the system to learn attorney preferences and improve retrieval precision over time.

It's like having a team of tireless research associates who read every patent ever filed, remember all of them perfectly, and get better at anticipating what you're looking for every time you send them back to the library.

The AI writes first drafts of patent applications and office action responses in your style, so attorneys can focus on strategy instead of staring at blank pages.

Stilta's drafting agents leverage domain-adapted large language models fine-tuned on millions of granted patents, prosecution histories, and office action exchanges. When an attorney provides an invention disclosure or technical description, the system generates structured patent application drafts—including specification, claims (independent and dependent), abstracts, and drawings descriptions—following jurisdiction-specific formatting and legal requirements. For prosecution support, agents analyze incoming office actions, identify examiner objections, map them to relevant claim elements, and draft proposed amendments and arguments. The system learns individual attorney writing styles and firm-specific conventions through few-shot learning and preference tuning, ensuring outputs feel native rather than generic. A built-in compliance layer validates drafts against patent office rules (e.g., USPTO, EPO formal requirements) before delivery. Attorneys review, edit, and approve all outputs, maintaining full control while dramatically reducing time-to-first-draft. The iterative workspace allows attorneys to refine drafts conversationally, with the AI tracking context across multiple revision cycles.

It's like having a brilliant junior associate who already read every patent your firm ever filed, writes in your voice, and never needs to sleep before a filing deadline.

The AI watches the entire patent landscape like a radar, instantly spotting where competitors are heading and where your best opportunities hide.

Stilta's portfolio analytics agents ingest and continuously monitor global patent filings, building dynamic maps of technology landscapes, competitor portfolios, and emerging innovation trends. Using supervised classification models and clustering algorithms, the system categorizes patents by technology domain, assigns quality and value scores, and identifies portfolio gaps and whitespace opportunities. Competitive intelligence agents track specific competitors' filing patterns, detect shifts in R&D focus, and flag potential freedom-to-operate risks or licensing opportunities. The platform generates executive-ready dashboards and narrative reports that translate complex patent data into strategic recommendations—such as where to file next, which patents to maintain or prune, and where infringement exposure exists. Knowledge graphs connect patent families, inventor mobility, acquisition signals, and litigation histories to provide a 360-degree strategic view. Alerts notify attorneys and IP strategists of relevant new filings, status changes, or competitive moves in near real-time. The system improves over time as users validate or override AI-generated assessments, creating a reinforcement loop that aligns the model's strategic lens with each organization's priorities.

It's like having a chess grandmaster who can see every move your competitors have made and are about to make on the patent board, then whispers the best counter-strategy in your ear.