A patent intelligence workflow built around the invention
Kudra's AI agents search and iterate across global patent databases, scientific literature, research papers, technical standards, and public technical sources, then map the evidence against the invention.
From invention disclosure to patent draft
Start with the invention
Provide the technical context, invention disclosure, or matter information needed to frame the investigation. Kudra starts from the substance of the invention — not just a short list of keywords.
Substance, not keywordsInvention disclosure · Technical context · Drawings · Matter notes · Related filings
Search across technical evidence
Kudra's agents investigate patent and non-patent sources, including scientific literature, research papers, technical standards, and public technical material.
Patent and non-patent sourcesThe goal is broader evidence discovery across the places relevant technical information may appear.
Iterate as the investigation develops
Patent research rarely follows a single perfect query. Kudra explores related terminology, technical concepts, and evidence patterns as the investigation evolves.
No rebuilding searches from scratchMap evidence to the invention
Review the relationship between the invention and the discovered evidence, feature by feature, with each finding linked to its source.
Evidence-oriented reviewUse the resulting context to investigate potential novelty issues and identify areas that may deserve closer professional review.
Develop claim directions
Turn the research into structured thinking about what may distinguish the invention and where claim strategy could develop.
From references to strategyMove from a pile of references toward a more useful strategic starting point.
Begin the patent draft
Use the accumulated research and claim direction as the foundation for a complete patent draft.
Practitioner-reviewed work productAccelerate the path from technical disclosure to a draft you review, correct, and finalize.
One supervisor.
Specialist agents per stage.
Kudra's supervisor frames the investigation, breaks it into tasks, coordinates specialist agents across patent and technical sources, checks their outputs, and hands the reasoning back to you for professional review.
Searches global patent databases, scientific literature, research papers, technical standards, and public technical sources.
Reads invention disclosures, technical documents, figures, and specifications to frame the investigation around the substance of the invention.
Maps discovered references against the technical features of the invention and organizes the reasoning behind the comparison.
Turns the evidence into structured thinking about what may distinguish the invention and where claim scope could develop.
Cross-checks references against their sources and surfaces conflicting evidence, low-confidence findings, and gaps in coverage.
Carries the research and claim direction into a complete patent draft for practitioner review and correction.
Search where relevant technical information actually appears
Kudra investigates patent and non-patent sources together, so the investigation is not limited to one database or one search formulation.
Invention disclosures · specifications · claim sets · figures · scientific papers · standards documents · office actions · technical reports · and more
AI-assisted does not mean judgment-free.
Kudra is designed to support the practitioner — not replace the practitioner. Use it to expand and organize the investigation, then apply your own expertise to verify sources, evaluate legal significance, refine claims, and make the final professional decisions.
Built for confidential IP work
Invention disclosures can contain commercially sensitive technical information. That makes confidentiality a first-order requirement — not a footnote. Every practice should evaluate Kudra’s data-handling, security, retention, access, and deletion policies against its own client obligations.
- Inventions are not used for model training
- Designed to avoid permanently storing invention data
- Encryption at rest and in transit
- Granular roles and permissions
- Full audit trail
- Multi-region architecture
- SOC 2 Type II certified
- On-premise and private deployment options
No model training
Your inventions are not used to train models
Encryption
AES-256 at rest and TLS 1.2+ in transit
Retention
Architecture designed to avoid permanently storing sensitive invention data
Audit trail
Track searches, sources reviewed, agent actions, and document access across a matter
SOC 2 Type II
Independently audited security controls
On-premise deployment
Run Kudra in your own environment or a private cloud tenant



