AI Solutions · Agentic AI
Intelligent agents for IP workflows.
Goal-driven AI agents that plan, research, execute and verify multi-step IP processes — with expert checkpoints where judgement matters.
Direct answer
What is agentic AI for intellectual property?
Agentic AI for intellectual property uses goal-driven AI agents that plan, research, reason, execute and verify multi-step IP workflows such as prior art research, landscape construction, competitor monitoring and portfolio review. Unlike a single prompt-and-answer tool, an agent decomposes the objective, runs the tasks and checks its own output before an expert validates the result.
How an IP agent operates
Goal
A defined IP objective — e.g. monitor a competitor's filings in solid-state batteries.
Plan
Decompose into retrieval, classification and comparison tasks.
Research
Query patent and literature sources, expand via families and citations.
Reasoning
Cluster, compare, detect change and assess significance.
Execution
Assemble charts, summaries and alerts.
Verification
Self-checks plus analyst and IP professional review.
Output
Decision-ready briefing delivered to the team.
Agent capabilities
- Autonomous patent research
- Multi-step technology analysis
- Continuous competitor monitoring
- Prior art triage and shortlisting
- Landscape refresh automation
- Patent workflow orchestration
- IP docket and deadline support
- Portfolio review preparation
- Automated reporting and alerts
Workflows we automate
- Competitor watch programmes
- Recurring landscape updates
- Invention disclosure triage
- Prosecution status tracking
- Annuity and pruning reviews
- Licensing target discovery
- Standards activity monitoring
- Executive IP reporting
Where agentic AI pays back fastest.
Connected capabilities
Agents reason far better over connected data — a knowledge graph gives them the relationships between patents, products and competitors.
AI IP Knowledge GraphAgent output feeds the intelligence layer where analysts turn continuous signals into strategy.
AI-Powered IP IntelligenceRetrieval and analytics are the tools agents call — the same semantic engine underpins both.
AI Patent Search & AnalyticsWhen an agent flags a protectable disclosure, drafting picks up immediately with the research already assembled.
AI Patent DraftingTalk to us
Automate the collection. Keep the judgement.
We start with one high-frequency workflow, prove the time saved, then expand agent coverage across your IP operation.
FAQ
Questions we hear from IP and technology teams.
What is agentic AI?
Agentic AI describes goal-driven AI systems that plan, act, use tools and verify their own outputs across multiple steps, rather than answering a single prompt. An agent decomposes an objective into tasks, executes them, checks results and reports back.
How is agentic AI different from generative AI?
Generative AI produces content in response to a prompt. Agentic AI pursues an objective — it plans a workflow, calls search and analysis tools, evaluates intermediate results and iterates until the goal is met, with human checkpoints at decisions that matter.
How does agentic AI apply to intellectual property?
IP work is inherently multi-step: research, retrieve, classify, compare, chart, monitor, report. Agents run those sequences end to end — prior art research, landscape construction, competitor monitoring, docket-driven tasks and portfolio reviews — with expert validation before anything is acted on.
Can AI agents perform patent research?
Yes. Agents can plan a search strategy, run semantic and classification-based retrieval, expand via citations and families, cluster results and draft a findings summary for analyst review.
Can agents monitor competitors continuously?
Yes. Monitoring agents watch named competitors, technology classes and jurisdictions, detect new publications, grants and assignments, and raise alerts with context rather than raw feeds.
Do humans stay in the loop?
Always. Hashi designs agent workflows with human checkpoints: analysts validate research findings, and qualified IP professionals review anything with legal or strategic consequence.
Is agentic AI secure for confidential IP work?
Agent workflows run under controlled access with confidentiality obligations, scoped data access and no use of client material to train public models.
What workflows can be automated first?
The highest-return starting points are competitor monitoring, recurring landscape refreshes, prior art triage, docket and deadline coordination and portfolio review preparation.
How long does it take to deploy agent workflows?
A scoped pilot on one workflow typically runs in weeks, not months. We start with a single high-frequency process, measure the time saved, then expand.
Who benefits most from agentic AI for IP?
IP teams and law firms with recurring, high-volume workflows — monitoring, research, docketing and reporting — where analyst time is currently consumed by collection rather than judgement.