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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Your deal-closing process can be cut in half by leveraging the Ensemble+ framework and BattleFin’s marketing and promotional tools. Our system will help your team tackle repetitive, time-consuming paperwork such as NDA's or testing agreements. The built-in python 3 data toolbox allows you to load historical data, and provides pre-built data exploration tools for interested buyers. This allows you to focus on making your data a viable financial product. Your data will be seen by Ensemble+ and BattleFin, which will help you get your data noticed by some of the most prominent players in the alternative data space for finance. We have a steady stream of people looking for data because of our deep roots and premier partners Jefferies, AWS and Refinitiv. Join Ensemble today to begin the process of marketing your data and selling it on the Ensemble platform. You can create exploration kits using our Python 3 data sandbox to highlight key elements of your data to buyers.

Description

KServe is a robust model inference platform on Kubernetes that emphasizes high scalability and adherence to standards, making it ideal for trusted AI applications. This platform is tailored for scenarios requiring significant scalability and delivers a consistent and efficient inference protocol compatible with various machine learning frameworks. It supports contemporary serverless inference workloads, equipped with autoscaling features that can even scale to zero when utilizing GPU resources. Through the innovative ModelMesh architecture, KServe ensures exceptional scalability, optimized density packing, and smart routing capabilities. Moreover, it offers straightforward and modular deployment options for machine learning in production, encompassing prediction, pre/post-processing, monitoring, and explainability. Advanced deployment strategies, including canary rollouts, experimentation, ensembles, and transformers, can also be implemented. ModelMesh plays a crucial role by dynamically managing the loading and unloading of AI models in memory, achieving a balance between user responsiveness and the computational demands placed on resources. This flexibility allows organizations to adapt their ML serving strategies to meet changing needs efficiently.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

1010data Yes 
Amazon Web Services (AWS) Yes 
Bloomberg No 
Docker No 
Foursquare Yes 
Gojek No 
IBM Cloud No 
Kubeflow No 
Kubernetes No 
LSEG Due Diligence Centre Yes 
LexisNexis Campaign Analyzer Yes 
NAVER No 
NVIDIA DRIVE No 
Thinknum Alternative Data Yes 
Visible Alpha Yes 
ZenML No 
Zillow No 
vLLM No 

Integrations

1010data No 
Amazon Web Services (AWS) No 
Bloomberg Yes 
Docker Yes 
Foursquare No 
Gojek Yes 
IBM Cloud Yes 
Kubeflow Yes 
Kubernetes Yes 
LSEG Due Diligence Centre No 
LexisNexis Campaign Analyzer No 
NAVER Yes 
NVIDIA DRIVE Yes 
Thinknum Alternative Data No 
Visible Alpha No 
ZenML Yes 
Zillow Yes 
vLLM Yes 

Pricing Details

$2,750 per month
Free Trial Yes 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

BattleFin

Founded

2012

Country

United States

Website

www.battlefin.com/provider/ensemble

Vendor Details

Company Name

KServe

Website

kserve.github.io/website/latest/

Product Features

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration No 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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