Math-Driven Patent Intelligence, Powered by AI

We help you avoid examiner-located art surprises before the first Office Action, improving allowance probability and reducing continuation re-drafting triggered by late-identified references.  

We work with prosecution teams to model how pending claim language is likely to be interpreted against CPC-adjacent disclosures under real-world examiner time constraints.

Our analysis applies similarity-scored semantic comparison across large CPC/IPCR-bounded patent families in order to identify where:

• terminological variation across otherwise overlapping disclosures may reduce perceived novelty during examination, or
• claim elements may read on to structurally analogous embodiments that are unlikely to be retrieved through classification-bounded keyword search alone.

The objective is to:   

• stress-test pending independent claims against semantically adjacent disclosures prior to first Office Action,
• reduce examiner-located art surprises during substantive      examination, and
• improve continuation drafting strategy by identifying where      claim scope appears saturated within the relevant CPC family.

This allows prosecution teams to refine:

• element-level terminology,
• structural limitations, and
• dependency layering

In a manner that may improve allowance probability while minimizing downstream IDS expansion or continuation re-drafting triggered by late-located art.

Our reporting pipeline is similarity-score driven and does not rely on generative drafting to identify overlapping subject matter, which helps ensure that mapped disclosures reflect claim-consistent structural correspondence rather than lexical coincidence.

We provide buy-side confidence by modeling claim novelty durability across the relevant CPC family under transaction timelines. 

We support IP diligence teams involved in portfolio acquisition, licensing evaluation, and freedom-to-operate analysis by providing similarity-scored comparison of issued claims across large CPC/IPCR-adjacent patent families.

Our platform applies transformer-based semantic scoring to identify disclosures that may write on to one or more limitations of a target independent claim under either:

• literal scope analysis, or
• Doctrine of Equivalents-consistent structural correspondence.

Because the comparison layer is CPC-bounded and similarity-ranked prior to report generation, the system is able to surface:

• semantically overlapping embodiments that may not share classification alignment
• inventor or assignee fragmentation across otherwise related filings, and
• terminology drift that obscures structurally analogous implementations across      continuation chains or affiliated portfolios.

   This allows transaction or licensing teams to:

• assess novelty durability across the relevant disclosure landscape,
• identify potential infringement adjacency prior to acquisition, and
• evaluate whether asserted claim scope appears commercially differentiated within its CPC family.

The resulting analysis is intended to supplement—not replace—traditional invalidity or clearance opinions by providing an examiner-scale comparison set that would otherwise be impractical to review manually during transaction timelines.

We help you find invalidity theory candidates faster.

We support litigation teams engaged in pre-suit assessment and post-assertion defense by providing similarity-scored comparison of asserted independent claims across CPC/IPCR-adjacent patent families.

Our platform applies transformer-based semantic scoring to identify prior disclosures that may write on to one or more claim limitations under:

• literal scope analysis, or
• structurally equivalent embodiments consistent with Doctrine of Equivalents frameworks.

Rather than relying exclusively on classification-aligned keyword retrieval, the system evaluates claim-consistent structural correspondence across large CPC-bounded comparison sets to surface disclosures that:

• implement functionally analogous architectures using non-identical terminology,
• are fragmented across continuation chains or inventor rotations, or
• reside in adjacent subclassifications unlikely to be retrieved through      traditional Boolean search strategies.

This allows case teams to:

• prioritize invalidity theory development based on similarity-ranked disclosure      overlap,
• assess whether asserted claim scope appears saturated within its relevant CPC      family, and
• reduce manual review burden when constructing claim charts across high-volume prior art sets.

The similarity-scoring layer operates independently from report generation in order to minimize lexical bias and better align mapped disclosures with claim-recited structural limitations.

Assess novelty durability at the point of inbound assertion demand — before committing to a licensing or litigation response strategy. 

 We assist defensive acquisition and assertion-risk screening teams by modeling asserted claim scope against CPC/IPCR-adjacent disclosures using similarity-ranked semantic comparison.

Our system evaluates whether one or more limitations of an asserted independent claim may read on to structurally analogous embodiments disclosed within:

• inventor-fragmented filings,
• assignee-diversified portfolios, or
• terminologically divergent implementations classified across adjacent CPC subclasses.

By applying transformer-based scoring across large disclosure sets prior to report generation, the platform is able to identify potential prior art overlap that may not be surfaced through classification-bounded or keyword-constrained retrieval strategies.

This allows inbound assertion triage teams to:

• assess novelty durability at the point of demand,
• evaluate invalidity adjacency prior to licensing engagement, and
• determine whether asserted claim scope appears commercially differentiated within its CPC family.

The resulting analysis is intended to supplement transaction-stage legal review by providing an examiner-scale semantic comparison set that would otherwise be impractical to review within typical response timelines.