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This post presents a solution where you can upload a recording of your meeting (a feature available in most modern digital communication services such as Amazon Chime ) to a centralized video insights and summarization engine. This post provides guidance on how you can create a video insights and summarization engine using AWS AI/ML services.
In the first part of the series, we showed how AI administrators can build a generative AI software as a service (SaaS) gateway to provide access to foundation models (FMs) on Amazon Bedrock to different lines of business (LOBs). It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker.
For more information about the SageMaker AI API, refer to the SageMaker AI API Reference. 8B-Instruct to DeepSeek-R1-Distill-Llama-8B, but the new model version has different API expectations. In this use case, you have configured a CloudWatch alarm to monitor for 4xx errors, which would indicate API compatibility issues.
These steps might involve both the use of an LLM and external data sources and APIs. Agent plugin controller This component is responsible for the API integration to external data sources and APIs. The LLM agent is an orchestrator of a set of steps that might be necessary to complete the desired request.
The software as a service (SaaS) platform offers out-of-the-box solutions for life, annuity, employee benefits, and institutional annuity providers. Verisk has embraced this technology and has developed their own Instant Insight Engine, or AI companion, that provides an enhanced self-service capability to their FAST platform.
Its software-as-a-service (SaaS) solution empowers leading banks and lenders with deep customer insights and AI-driven decision-making capabilities. Our initial approach combined prompt engineering and traditional Retrieval Augmented Generation (RAG). Tools Tools extend agent capabilities beyond the FM.
A number of AWS independent software vendor (ISV) partners have already built integrations for users of their software as a service (SaaS) platforms to utilize SageMaker and its various features, including training, deployment, and the model registry.
In this post, we highlight how the AWS Generative AI Innovation Center collaborated with SailPoint Technologies to build a generative AI-based coding assistant that uses Anthropic’s Claude Sonnet on Amazon Bedrock to help accelerate the development of software as a service (SaaS) connectors.
One aspect of this data preparation is feature engineering. Feature engineering refers to the process where relevant variables are identified, selected, and manipulated to transform the raw data into more useful and usable forms for use with the ML algorithm used to train a model and perform inference against it.
Fine-tune an Amazon Nova model using the Amazon Bedrock API In this section, we provide detailed walkthroughs on fine-tuning and hosting customized Amazon Nova models using Amazon Bedrock. We first provided a detailed walkthrough on how to fine-tune, host, and conduct inference with customized Amazon Nova through the Amazon Bedrock API.
Great examples of automated distribution include survey integrations and Application Programming Interface (API) connections. And, setting up APIs can link two applications to one another for data sharing/interacting purposes, making manual uploads a thing of the past. Create custom APIs for more complex use cases. Not to worry!
Programmatic setup Alternatively, you can create your labeling job programmatically using the CreateLabelingJob API. Whether you choose the SageMaker console or API approach, the result is the same: a fully configured labeling job ready for your annotation team. He has MBA from the Indian School of Business and B.
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies, such as AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.
It’s a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like Anthropic, Cohere, Meta, Mistral AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.
There are unique considerations when engineering generative AI workloads through a resilience lens. If you’re performing prompt engineering, you should persist your prompts to a reliable data store. There are three general types of vector databases: Dedicated SaaS options like Pinecone.
This emergent ability in LLMs has compelled software developers to use LLMs as an automation and UX enhancement tool that transforms natural language to a domain-specific language (DSL): system instructions, API requests, code artifacts, and more. The JSON artifact is directly integrated to the core SnapLogic integration platform.
These challenges led to the decision to create a new cloud-native system that can scale with increased demand and consists of serverless and software as a service (SaaS) components that externalize much of the domain-specific functionality to allow for easier operations and faster time-to-market for changes.
With this architecture, a software as a service (SaaS) business can break the linearly increasing cost of hosting multiple models and achieve reuse of infrastructure consistent with the multi-tenancy model applied elsewhere in the application stack. This instructs DJLServing to use the Python engine.
In this post: What is SaaS? What sets SaaS apart? How does SaaS add value to CX? CX strategies that SaaS makes possible. What is SaaS? SaaS stands for Software as a Service. Software as a service (SaaS). SaaS is the most commonly used model. What sets SaaS apart? Virtualisation ? ? ?
Furthermore, the use of prompt engineering can notably enhance their performance. With the batch inference API, you can use Amazon Bedrock to run inference with foundation models in batches and get responses more efficiently. The service is in preview as of this writing and only available through the API. split("/")[-1]}.out'
To classify and extract information needed to validate information in accordance with a set of configurable funding rules, Informed uses a series of proprietary rules and heuristics, text-based neural networks, and image-based deep neural networks, including Amazon Textract OCR via the DetectDocumentText API and other statistical models.
Deploy the model via Amazon Bedrock For production use, especially if you’re considering providing access to dozens or even thousands of employees by embedding the model into an application, you can deploy the models as API endpoints. Use the model You can access your fine-tuned LLM through the Amazon Bedrock console, API, CLI, or SDKs.
Job Opening: Sales Engineer. Our fast-growing startup is looking for a skilled, self-motivated problem solver to join our team as a Sales Engineer. As a Sales Engineer , you are the technical expert during the sales process. SaaS/Cloud experience strongly preferred. Strong verbal and written communications skills.
Since its launch a few months ago, the Visual Intelligence Platform has delivered analysis and insights within both TechSee’s products and via API integrations into third-party solutions like chatbots or workflows. The new VI Mobile SDK makes this possible. The VI Mobile SDK Advantages.
It’s a far cry from the expansive data engineering initiatives that likely still haunt your dreams. Most leading SaaS platforms have APIs and consider 3rd-party integrations to be a critical component of their value proposition. The world would be a beautiful place if all touchpoint data was available through APIs.
In our examples below, we’ve chosen to use a SaaS (software as a service) product that helps users build and design websites. Working with users who want to design sites using our API. Triaging technical tickets and bugs before they are sent to our engineering team. HTML, CSS, JavaScript, APIs, and debugging tools (i.e.,
We have developed a MONAI Deploy connector to AHI to integrate medical imaging AI applications with subsecond image retrieval latencies at scale powered by cloud-native APIs. AHI provides API access to ImageSet metadata and ImageFrames. Metadata contains all DICOM attributes in a JSON document.
In every interview, engineers ask: “What’s your Tech Stack, and what tools do you use?”. The Aircall engineering team is nearly 200 people, organized in agile teams owning different business domains like Telephony, User Management, Dashboard, Integrations, and so on, with more than 30 teams in total. SaaS Tools. Harvestr.io
Hear best practices for using unstructured (video, image, PDF), semi-structured (Parquet), and table-formatted (Iceberg) data for training, fine-tuning, checkpointing, and prompt engineering. Additionally, SaaS providers need scalable and cost-effective ways to serve hundreds of models to their customers. Reserve your seat now!
Deploy the model with SageMaker For production use, especially if you’re considering providing access to dozens or even thousands of employees by embedding the model into an application, you can deploy the model as an API endpoint. Locate the model with the prefix canvas-llm-finetuned- and timestamp.
Boomi is an enterprise-level software as a service (SaaS) independent software vendor (ISV) that creates developer enablement tooling for software engineers. These tools integrate via API into Boomi’s core service offering. Markov chains are best known for their applications in web crawling and search engines.
Align subscription-based or usage-based pricing models with long-term revenue strategies for SaaS or service-driven businesses. Use APIs and middleware to bridge gaps between CPQ and existing enterprise systems, ensuring smooth data flow. Implement event-driven architecture where updates in CRM (e.g.,
One of their products is ExaDeploy , an easy-to-use SaaS solution to serve ML workloads at scale. On some large batch ML workloads, ExaDeploy has reduced costs by over 85% without sacrificing on latency or accuracy, with integration time as low as one engineer-day. Nicholas Jiang, Software Engineer, Exafunction.
Terraform is an IaC tool that allows you to manage AWS resources, software as a service (SaaS) resources, datasets, and more, using declarative configuration. Your data remains in the Region where the API call is processed. Tyler leads Terraform provider engineering at AWS and is a Core Contributor for Terraform.
Prior to AWS, Michael led business development activities for B2B technology companies across semiconductors, SaaS, and autonomous trucking industries. He is currently focused on combining his background in software engineering, DevOps, and machine learning to help customers deliver machine learning workflows at scale.
As democratization of foundation models (FMs) becomes more prevalent and demand for AI-augmented services increases, software as a service (SaaS) providers are looking to use machine learning (ML) platforms that support multiple tenants—for data scientists internal to their organization and external customers.
Customer Operations means everything from Customer Success to Customer Support, Engineering Support, and Professional Services. I watched Account Management transform and evolve over the past few years, especially with the subscription-based economy and the growth of SaaS.
CCC is a leading software-as-a-service (SaaS) platform for the multi-trillion-dollar property and casualty insurance economy powering operations for insurers, repairers, automakers, part suppliers, lenders, and more. Step-by-step solution Step 1 A client makes a request to the AWS API Gateway endpoint.
With RAG, the data external to the FM and used to augment user prompts can come from multiple disparate data sources, such as document repositories, databases, or APIs. Engineer the prompt with the snippets with the original query so that the foundation model can generate an answer from the retrieved documents.
APIs (Application Programming Interfaces) are used to publish content, product, and banners, for example. SaaS (software as a service) ecommerce platforms are highly recommended for companies that don’t want to deal with the IT infrastructure and coding part of having an online store. Ecommerce Platform: Hosted X Self-Hosted.
Let’s admit to the fact that it is the Recurring Revenue that is going to make or break your SaaS business and the three factors that are responsible for your SaaS Revenue growth are-. Upselling to existing customers , which is more or less the direct window to the Recurring Revenue for your SaaS Business. New Customers.
You will learn the needed software skills to acquire a software engineering job. Integrate React with advanced browser features, even geolocation API’s! WordPress REST API (AJAX). Bootstrap 4. Javascript ES6. DOM Manipulation. Bash Command Line. Git, GitHub and Version Control. Backend Web Development. Express.js.
to model products/services and guide the user to valid configurations Pricing Engine: Applies pre-defined pricing rules, discounts, bundles, etc. This Software-as-a-Service (SaaS) approach delivers the same CPQ features on demand with a lower barrier to entry and speeds up deployment. What are some key benefits of CPQ cloud solutions?
Our detailed API Documentation , which helps customers build advanced implementations using their subscription data. Going through this exercise really energized the team, so we used the learnings to create SLAs for the whole team, including when the success team collaborates with product and engineering.
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