Proprietary AI platforms built for real decisions
We don't just advise — we build. AiPi develops proprietary software platforms powered by AI, knowledge graphs, and geospatial intelligence that transform raw data into competitive advantage.
Patent Landscape Intelligence
Our proprietary landscape system generates structured competitive intelligence reports — mapping your IP position against the entire patent landscape in your domain. Each report includes patentability analysis, competitor mapping, disclosure depth scoring, and a filterable reference library.
Competitive Analysis
Direct competitor identification with feature-by-feature comparison across the patent landscape.
Disclosure Depth Scoring
Radar charts visualizing how deeply each patent discloses across your technology's key features.
Filterable Reference Library
Searchable database of relevant patents with assignee, filing date, status, and full-text access.
Analytics Dashboard
Quantitative insights on filing trends, geographic coverage, and competitive positioning.
110
Patents Analyzed
15
Deep-Dive Disclosures
50
Competitors with IP
10
Features Assessed
Most Relevant Disclosures
Each patent includes a radar chart showing depth of disclosure across each feature.
Natural language processing for searching security video data
Coram AI Inc · Filed: 2023-09-08
Reference Library
A knowledge graph of every US patent
We're integrating a comprehensive knowledge graph of all US patent information. Each node contains complete bibliographic data — assignee history, prosecution history, examiner information, citation networks — enriched with semantic embeddings generated via NVIDIA NeMo Retriever for deep similarity search.
Bibliographic Data
Full assignee history, inventors, classifications
Prosecution History
Office actions, amendments, continuations
Examiner Intelligence
Examiner stats, allowance rates, art unit data
Semantic Embeddings
NeMo Retriever vectors for deep similarity search
...and more
Selected County
Fresno, CA
1,234,567 planted acres
Top Specialty Crop
Almonds
342,100 acres
Agricultural Data IntelligenceBeta
Built for agricultural companies, our GroNatural Analysis Platform visualizes crop acreage distribution on an interactive map — replacing static tables with real-time, filterable geospatial intelligence. Users can sort by crop, state, and county, toggle layers, and identify land owners and farm data.
The platform scored 8.6/10 for UI satisfaction and 7.8/10 for data robustness in post-alpha client surveys. Data is sourced from the USDA Cropland Data Layer, Organic Integrity Database, and Web Soil Survey.
Pixel-Level Crop Prediction
We're building a machine learning pipeline to predict crop plantings at 30-meter resolution across the entire continental US — forecasting CDL 2026 and 2027 before satellite data is available.
Data Fusion
Align 5 years of CDL history, gSSURGO soil data, and NED terrain data to a unified 30m grid.
Feature Engineering
25 features per pixel: crop history, soil properties (pH, clay, AWC), terrain, and spatial coordinates.
GNN Training
Graph Neural Network trained on 50–100M stratified samples with specialty crop oversampling for balanced class representation.
National Inference
Tiled prediction across 9 billion pixels producing a predicted CDL raster that feeds directly into the existing platform.
> 85%
Overall accuracy target
> 0.60
Macro F1 score
9B
Pixels predicted nationally
30m
Resolution per pixel
Interested in what our platforms can do for your business?
We build custom intelligence platforms for organizations that need more than off-the-shelf tools.