Sold by: Isaacus
Deployed on AWS
A state-of-the-art reranking model optimized for legal RAG, research, and classification, ranked first on Legal RAG Bench and the Massive Legal Embedding Benchmark (MLEB).
Overview
Kanon 2 Reranker is a state-of-the-art reranking model optimized for legal RAG, research, and classification. It achieves the highest possible retrieval accuracy on both the Massive Legal Embedding Benchmark (MLEB) and Legal RAG Bench, outperforming Voyage Rerank 2.5 by 7%, Qwen 3 Reranker 8B by 9%, and Voyage 4 Large by 24%.
Kanon 2 Reranker has a native context window of 16,384 tokens, however, it can reranker documents much greater in length thanks to Isaacus' semchunk semantic chunking library.
On a single g6e.xlarge instance, Kanon 2 Reranker can rerank 1 billion tokens (roughly 250k average-sized legal documents) per hour.
Like all other Isaacus SageMaker model deployments, your Kanon 2 Reranker deployment will be fully air-gapped, no data will enter or leave your AWS account.
Conveniently, Isaacus SageMaker model deployments are also compatible with the standard Isaacus Python SDK via the Isaacus SageMaker Python integration: https://docs.isaacus.com/integrations/amazon-sagemaker .
You can negotiate a discount by contacting us: https://isaacus.com/support .
Highlights
- Ranked first on Legal RAG Bench and the Massive Legal Embedding Benchmark (MLEB), outperforming Voyage Rerank 2.5 by 7%, Qwen 3 Reranker 8B by 9%, and Voyage 4 Large by 24%.
- Capable of reranking documents of almost any length thanks to Isaacus' semchunk semantic chunking library.
- Achieves throughput of 1 billion tokens per hour on a single g6e.xlarge instance, equivalent to 250k legal documents.
Details
Sold by
Categories
Delivery method
Latest version
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g6.xlarge Inference (Batch) Recommended | Model inference on the ml.g6.xlarge instance type, batch mode | $4.99 |
ml.g6e.xlarge Inference (Real-Time) Recommended | Model inference on the ml.g6e.xlarge instance type, real-time mode | $4.99 |
ml.g6.2xlarge Inference (Batch) | Model inference on the ml.g6.2xlarge instance type, batch mode | $4.99 |
ml.g6.4xlarge Inference (Batch) | Model inference on the ml.g6.4xlarge instance type, batch mode | $4.99 |
ml.g6.8xlarge Inference (Batch) | Model inference on the ml.g6.8xlarge instance type, batch mode | $4.99 |
ml.g6.16xlarge Inference (Batch) | Model inference on the ml.g6.16xlarge instance type, batch mode | $4.99 |
ml.g5.xlarge Inference (Batch) | Model inference on the ml.g5.xlarge instance type, batch mode | $4.99 |
ml.g6.xlarge Inference (Real-Time) | Model inference on the ml.g6.xlarge instance type, real-time mode | $4.99 |
ml.g6.2xlarge Inference (Real-Time) | Model inference on the ml.g6.2xlarge instance type, real-time mode | $4.99 |
ml.g6.4xlarge Inference (Real-Time) | Model inference on the ml.g6.4xlarge instance type, real-time mode | $4.99 |
Vendor refund policy
To the maximum extent permitted by law, there are no refunds for consumption of this product.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Initial release.
Additional details
Inputs
- Summary
For a user-friendly walkthrough of how to get started deploying Isaacus models on SageMaker, check out the Isaacus SageMaker quickstart guide on our docs.
This model runs on the fully air-gapped Isaacus SageMaker Model Server, which supports all the same functionality as the standard Isaacus API except that requests to the server must be proxied through the /invocations endpoint.
For example, if you wanted to send a POST request to /v1/rerankings with the data {"model": "kanon-2-reranker", "query": "confidentiality", "texts": ["You must keep this information confidential.", "Isaacus is a registered trademark."]}, you could so by sending /invocations the payload {"path": "/v1/rerankings", "method": "POST", "data": {"model": "kanon-2-reranker", "query": "confidentiality", "texts": ["You must keep this information confidential."]}}.
This means that minimal code changes are necessary to switch between the online Isaacus API and your own private Isaacus model deployments.
In fact, Python users can use the Isaacus SageMaker Python integration to automatically forward requests to the Isaacus API to SageMaker deployments using the standard Isaacus SDK.
Given that this is a private deployment and that authentication is managed by AWS, Isaacus API keys are not needed and are ignored.
As a reranking model, Kanon 2 Reranker currently only supports the /v1/rerankings endpoint. For more information on the arguments accepted and returned by that endpoint, please consult our API reference documentation .
- Limitations for input type
- All the same limitations applicable to the Isaacus API except for the need for an API key.
- Input MIME type
- application/json
{
"path": "/v1/rerankings",
"method": "POST",
"data": {
"model": "kanon-2-reranker",
"query": "What are the essential elements required to establish a negligence claim?",
"texts": [
"To form a contract, there must be an offer, acceptance, consideration, and mutual intent to be bound.",
"Criminal cases involve a completely different standard, requiring proof beyond a reasonable doubt."
]
}
}
{
"path": "/v1/rerankings",
"method": "POST",
"data": {
"model": "kanon-2-reranker",
"query": "What are the essential elements required to establish a negligence claim?",
"texts": [
"To form a contract, there must be an offer, acceptance, consideration, and mutual intent to be bound.",
"Criminal cases involve a completely different standard, requiring proof beyond a reasonable doubt."
]
}
}
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
path | The path of the API endpoint being invoked (e.g., `/v1/rerankings`). | As a reranking model, Kanon 2 Reranker currently only supports the `/v1/rerankings` endpoint. | Yes |
method | The HTTP method used for the invocation (e.g., `POST`). Defaults to `POST`. | One of `POST`. | No |
headers | The HTTP headers to include in the invocation request. Defaults to `null`/`None`, in which case no additional headers are sent. | Must be a mapping of strings to strings. | No |
data | The data to be sent as the body of the invocation request. This can be any serializable object. Defaults to `null`/`None`, in which case no body is sent. | - | No |
Resources
Vendor resources
Support
Vendor support
To get in touch with our support team, you can reach out via the support form on our website: https://isaacus.com/support . We endeavor to respond within 24 hours.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
State-of-the-art legal embedding and reranking models optimized for legal research, legal RAG, and legal document classification.
Best-in-class legal enrichment, reranking, and embedding models, optimized for legal knowledge graphs and legal RAG.
A state-of-the-art legal reranking and zero-shot classification/NLI model.
A state-of-the-art legal embedding model optimized for semantic search, RAG, and document classification, ranked first on the Massive Legal Embedding Benchmark.
A state-of-the-art legal extractive question answering model optimized for extracting metadata and relevant passages from legal documents.
A lightweight legal reranking and zero-shot classification/NLI model.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.