AWS Machine Learning

FEBRUARY 1, 2024

In the batch case, there are a couple challenges compared to typical data pipelines. The data sources may be PDF documents on a file system, data from a software as a service (SaaS) system like a CRM tool, or data from an existing wiki or knowledge base. He also holds an MBA from Colorado State University.

Best practices 131

Best practices Engineering SaaS Accountability 131

AWS Machine Learning

NOVEMBER 27, 2023

We’ll point our search data flow to the file and output a file with corresponding results in a new file in an Amazon S3 location. Preparing a prompt After we create a knowledge base out of our PDF, we can test it by searching the knowledge base for a few sample queries. Add a custom transform with Python (PySpark).

Engineering 89

Engineering APIs Big data Accountability 89

aircall

APRIL 16, 2021

SaaS works well for a variety of general use cases, including: Data backup. Big data analytics. Flexibility – SaaS uses an open API (application programming interface) technology. They’d rather take the lead and get an answer on their own using an automated voice response system or a knowledge base.

SaaS 62

SaaS Sales Coaching APIs 62

Balto

JANUARY 14, 2025

But modern analytics goes beyond basic metricsit leverages technologies like call center data science, machine learning models, and big data to provide deeper insights. Predictive Analytics: Uses historical data to forecast future events like call volumes or customer churn. Immediate access to knowledge bases or FAQs.

Call Center 52

Call Center Analytics Average Handle Time Big data 52

Enghouse Interactive

JULY 10, 2018

Knowledge based and FAQ’s are not a one and done. For Partner Colorado, Enghouse’s use of open APIs allows integration with the in-house CRM. Instead of having to toggle back and forth between different screens and applications, agents proactively receive relevant and useful data on callers via ScreenPop.

Self service 40

Self service CRM Contact Center Analytics 40

SmartKarrot

NOVEMBER 23, 2021

With time, it develops a massive knowledge base and can anticipate the user or customer requirements. AI can learn from its past experiences and formulates predictions based on data. Interpret big data. Industries collect mounds and mounds of data in a single day.

Calibration 10

Calibration Automotive Big data Chatbots 10

AWS Machine Learning

OCTOBER 23, 2024

Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. The integration with Amazon Bedrock is achieved through the Amazon Bedrock InvokeModel APIs.

Enterprise 75

Enterprise APIs Engineering Government 75

AWS Machine Learning

FEBRUARY 10, 2025

To solve this challenge, RDC used generative AI , enabling teams to use its solution more effectively: Data science assistant Designed for data science teams, this agent assists teams in developing, building, and deploying AI models within a regulated environment. Tools Tools extend agent capabilities beyond the FM.

Chief Customer Officer 89

Chief Customer Officer Banking SaaS Engineering 89

AWS Machine Learning

AUGUST 2, 2024

An approach to product stewardship with generative AI Large language models (LLMs) are trained with vast amounts of information crawled from the internet, capturing considerable knowledge from multiple domains. However, their knowledge is static and tied to the data used during the pre-training phase.

APIs 111

APIs Analytics Chatbots Engineering 111

AWS Machine Learning

APRIL 2, 2025

In this context, the term tools refer to external capabilities or APIs that the model can access and interact with to extend its functionality beyond text-based responses. By planning, the LLM can break down a complex question into manageable steps, making sure that the right APIs are called in the correct order.

APIs 96

APIs Engineering Analytics Healthcare 96

AWS Machine Learning

NOVEMBER 27, 2024

Enterprises are facing challenges in accessing their data assets scattered across various sources because of increasing complexities in managing vast amount of data. Traditional search methods often fail to provide comprehensive and contextual results, particularly for unstructured data or complex queries.

Enterprise 96

Enterprise APIs Accountability Engineering 96

AWS Machine Learning

DECEMBER 4, 2024

Tecton accommodates these latency requirements by integrating with both disk-based and in-memory data stores, supporting in-memory caching, and serving features for inference through a low-latency REST API, which integrates with SageMaker endpoints. Now we can complete our fraud detection use case.

Engineering 87

Engineering APIs Airlines Government 87

AWS Machine Learning

NOVEMBER 19, 2024

We showcase a variety of tools including database retrieval with Text2SQL, statistical models and visual charts with scientific libraries, biomedical literature search with public APIs and internal evidence, and medical image processing with Amazon SageMaker jobs. Architecture diagram showing Agents for Bedrock system flow.

APIs 68

APIs Healthcare Engineering Banking 68

AWS Machine Learning

MARCH 18, 2025

NIM microservices provide straightforward integration into generative AI applications using industry-standard APIs and can be deployed with just a few lines of code, or with a few clicks on the SageMaker JumpStart console. For inference request format, NIM on SageMaker supports the OpenAI API inference protocol (at the time of writing).

APIs 87

APIs Enterprise Engineering Accountability 87

AWS Machine Learning

JANUARY 7, 2025

Amazon Bedrock Flows provide a powerful, low-code solution for creating complex generative AI workflows with an intuitive visual interface and with a set of APIs in the Amazon Bedrock SDK. The agent submits the following query to the knowledge base: Product specifications and market context for Interest Rate option USD_2Y_1Y.

Technical Support 98

Technical Support APIs Government Analytics 98