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Kanon 2 Enricher

the first hierarchical graphitization model

Details

External ID
47229931
Source
HN
Company
—
Product
Kanon 2 Enricher
Website domain
isaacus.com
Launched
March 3, 2026
Cohort
—
Upvotes
10
Upvotes percentile
0.5781057810578106
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Hey HN, This is Kanon 2 Enricher, the first hierarchical graphitization model. It represents an entirely new class of AI models designed to transform document corpora into rich, highly structured knowledge graphs.In brief, our model is capable of: - Entity extraction, classification, and linking: identifying key entities like individuals, companies, governments, locations, dates, documents, and more, and classifying and linking them together. - Hierarchical segmentation: breaking a document up into its full hierarchy, including divisions, sections, subsections, paragraphs, and so on. - Text annotation: extracting common textual elements such as headings, sigantures, tables of contents, cross-references, and the like.We built Kanon 2 Enricher from scratch. Every node, edge, and label in the Isaacus Legal Graph Schema (ILGS), which is the format it outputs to, corresponds to at least one task head in our model. In total, we built 58 different task heads jointly optimized with 70 different loss terms.Thanks to its novel architecture, unlike your typical LLM, Kanon 2 Enricher doesn't generate extractions token by token (which introduces the possibility of hallucinations) but instead directly classifies all the tokens in a document in a single shot. This makes it really fast.Because Kanon 2 Enricher's feature set is so wide, there are a myriad of applications it can be used for, from financial forensics and due diligence all the way to legal research.One of the coolest applications we've seen so far is where a Canadian government built a knowledge graph out of thousands of federal and provincial laws in order to accelerate regulatory analysis. Another cool application is something we built ourselves, a 3D interactive map of Australian High Court cases since 1903, which you can find right at the start of our announcement.Our model has already been in use for the past month, since we released it through a closed beta that included Harvey, KPMG, Clifford Chance, Clyde & Co, Alvarez & Marsal, Smokeball, and 96 other design partners. Their feedback was instrumental in improving Kanon 2 Enricher before its public release, and we're immensely thankful to each and every beta participant.We're eager to see what other developers manage to build with our model now that its out publicly.

Enrichment

Theme
decision model runtimes and tools
Vertical
Horizontal
Function
Analytics & BI
Audience
Developer
AI stance
Not AI
Project type
Hobby / open-source project
Normalized one-liner
hierarchical graphitization model
Manually corrected
False

Could you build this?

No Developing a proprietary hierarchical graphitization model with sub-second latency requires foundational machine learning research, custom model training, and massive curated legal corpora.

What it would actually take: This requires training or fine-tuning transformer-based architectures with specialized token/relation classification heads optimized for nested structured schema extraction. The difficult parts include creating large-scale, high-quality annotated legal corpora, defining hierarchical knowledge representation schemas, and optimizing model inference (via TensorRT-LLM, vLLM, or quantization) to hit sub-second latency on multi-page documents. It necessitates dedicated ML researchers, legal NLP specialists, and large GPU training clusters.

Discussion

6 comments analyzed.

Concerns raised: Data leaving network/privacy concerns, Unclear pricing visibility on website, Terminology confusion around 'graphitization'

Feature requests: Self-hostable version on AWS Marketplace, Self-hostable version on Azure Marketplace, Air-gapped deployments with unmetered usage

Competitors

Other products that read as similar to this one — 70 launches clear the similarity bar, closest 8 shown.

Attention rank: #27 of 71 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 123 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a analytics & bi tool for Legal yet.