Best AI tools for< identify key moments in sales calls >

Pitch Patterns is an AI-powered sales performance tool that helps businesses improve their sales performance by analyzing sales calls and identifying patterns that lead to success. The tool uses AI to automatically find key moments in sales calls, such as when the customer is positive or negative, when the salesperson is mirroring the customer's emotions, and when the salesperson is using long speech monologues. This information can then be used to coach salespeople on how to improve their sales pitches and close more deals.

Fathom is an AI-powered note-taking tool that helps you record, transcribe, and summarize your meetings. It integrates with Zoom and Google Meet, and offers a range of features to help you stay organized and productive. **Key Features** * **Automatic recording and transcription:** Fathom automatically records and transcribes your meetings, so you can focus on the conversation instead of taking notes. * **AI-generated summaries:** Fathom uses AI to generate summaries of your meetings, which can save you time and help you identify key takeaways. * **Highlighting and bookmarking:** You can highlight and bookmark important moments in your meetings, so you can easily find them later. * **Sharing and collaboration:** You can share your meeting recordings and summaries with others, and collaborate on notes and action items. * **Integrations:** Fathom integrates with a range of other tools, including Zoom, Google Meet, Slack, and Asana. **Benefits** * **Save time:** Fathom can save you hours of time by automatically recording and transcribing your meetings. * **Stay organized:** Fathom helps you stay organized by providing a central place to store your meeting recordings and notes. * **Improve productivity:** Fathom can help you improve your productivity by providing you with easy access to the information you need from your meetings. * **Make better decisions:** Fathom can help you make better decisions by providing you with a clear understanding of what was discussed in your meetings. **Pricing** Fathom is free to use for individuals. There is also a paid Team Edition that offers additional features, such as: * **Unlimited storage:** The Team Edition gives you unlimited storage for your meeting recordings and notes. * **Team management:** The Team Edition allows you to manage your team's access to Fathom. * **Custom branding:** The Team Edition allows you to customize Fathom with your own branding. **Alternatives** * Otter.ai * Trint * Descript * Rev **Use Cases** * **Sales:** Fathom can help sales teams track their progress and identify opportunities. * **Customer success:** Fathom can help customer success teams build relationships with their customers and resolve issues quickly. * **Product development:** Fathom can help product development teams gather feedback from users and improve their products. * **Marketing:** Fathom can help marketing teams track the effectiveness of their campaigns and generate leads. * **Education:** Fathom can help educators record and share lectures and other materials with students. **FAQ** **Q: How much does Fathom cost?** A: Fathom is free to use for individuals. There is also a paid Team Edition that offers additional features. **Q: What are the benefits of using Fathom?** A: Fathom can save you time, help you stay organized, improve your productivity, and make better decisions. **Q: What are the alternatives to Fathom?** A: Some alternatives to Fathom include Otter.ai, Trint, Descript, and Rev. **Q: What are some use cases for Fathom?** A: Fathom can be used for a variety of purposes, including sales, customer success, product development, marketing, and education.

Laxis is a revolutionary AI Meeting Assistant designed to capture and distill key insights from every customer interaction effortlessly. It seamlessly integrates across platforms, from online meetings to CRM updates, all with a user-friendly interface. Laxis empowers revenue teams to maximize every customer conversation, ensuring no valuable detail is missed. With Laxis, sales teams can close more deals with AI note-taking and insights from client conversations, business development teams can engage prospects more effectively and grow their business faster, marketing teams can repurpose podcasts, webinars, and meetings into engaging content with a single click, product and market researchers can conduct better research interviews that get to the "aha!" moment faster, project managers can remember key takeaways and status updates, and capture them for progress reports, and product and UX designers can capture and organize insights from their interviews and user research.

Eklipse is an AI-powered tool that helps streamers and content creators automatically generate highlights from their Twitch, YouTube, and Facebook streams and videos. It uses advanced AI technology to identify key moments in your streams, such as exciting gaming moments or funny in-game experiences, and then creates short, shareable clips that are perfect for TikTok, Reels, and YouTube Shorts. Eklipse also offers a range of editing tools that allow you to customize your clips and add your own branding. With Eklipse, you can save time and effort on editing, and focus on creating great content that will grow your channel.

Powder is an AI-powered clipping software designed specifically for gamers and content creators. It analyzes your streams and automatically identifies the best moments, saving you hours of editing time. With Powder, you can easily create short-form videos that are perfect for sharing on social media. Powder is also packed with features that make it easy to edit and share your clips, including a built-in video editor, social media integration, and more.

ConvoZen.AI is a leading AI-driven conversational intelligence platform that provides businesses with insights and tools to improve their customer interactions. The platform offers a range of features, including AI-powered insights and key moment identification, conversation sentiment analysis, automated compliance audit, agent performance management, and custom reports and analytics. ConvoZen.AI integrates with enterprise CRM, emails, and other systems to provide real-time alerts and actionable insights. The platform is designed to help businesses improve sales, customer experience, compliance, and agent performance.

Munch is an AI-powered video repurposing platform that helps businesses and individuals extract the most engaging and impactful clips from their long-form videos. With its advanced machine learning capabilities, Munch analyzes video content to identify key moments, generate captions, and create social media posts. It supports multiple languages and provides insights into marketing trends to help users optimize their content for different platforms.

tl;dv is an AI-powered meeting note-taker that transcribes, summarizes, and generates insights from your calls with customers, prospects, and your team. It integrates with popular video conferencing platforms like Zoom, Google Meet, and Microsoft Teams, allowing you to automatically record and transcribe meetings. The AI technology used by tl;dv can identify key moments, summarize topics, and even create bite-sized video clips for easy sharing. Additionally, it offers seamless integration with various productivity tools and CRMs, enabling you to share meeting insights and automate workflows.

Graphite Note is a no-code AI tool that helps businesses transform data into key drivers, predictions, and next-best actions. It is designed to be user-friendly and accessible to businesses of all sizes, even those without a data science team. With Graphite Note, businesses can quickly and easily generate AI models, understand patterns in their data, predict future outcomes, and get actionable insights. This can help businesses make better decisions, improve their operations, and grow their revenue.

TMate is an AI-powered meeting assistant that helps teams and professionals streamline their post-meeting workflow. With automated transcripts, summaries, and AI-curated highlights, TMate analyzes conversations in minutes, saving users time and effort. The tool also offers AI-powered custom meeting notes, cross-meeting analytics, and real-time progress tracking, providing valuable insights and helping teams stay on top of critical project details.

Komodo Health is a healthcare technology company that provides software applications to enable users to deliver exceptional value to their customers, colleagues, and patients. The company's Healthcare Map is the industry's most precise view of the U.S. healthcare system, and it combines the world's most comprehensive view of patient-encounters with innovative algorithms and decades of clinical expertise. Komodo Health's software applications are used by life sciences companies, payers, providers, and consultancies to improve the certainty of pre-launch plans, calculate Rx-based ROI for digital marketing, find patients with complicated or rare conditions, and more.

Sybill is an AI-powered personal assistant designed specifically for sales teams. It uses advanced natural language processing (NLP) and machine learning algorithms to analyze sales conversations, identify key insights, and automate tasks. With Sybill, sales teams can save time, improve productivity, and close more deals.

Detangle is a legal document analysis tool that helps users understand complex legal documents without the need for an attorney. It provides a summary of the document, identifies key terms and concepts, and highlights potential issues. Detangle is designed to save users time and money by making legal documents more accessible and understandable.

Diligen is a machine learning powered contract analysis tool that helps teams streamline their contract review process. It can identify key provisions, generate contract summaries, and help teams manage review with machine learning powered analysis. Diligen is used by law firms, legal service providers, and corporations around the world to make high quality contract review faster, more efficient, and more cost effective.

SummarizeYT is a YouTube summary tool that uses ChatGPT to generate summaries of YouTube videos. It is a free and easy-to-use tool that can help you save time and get the most out of your YouTube viewing experience.

Umbrellabird is an AI-powered tool that automates the analysis and synthesis of user interview recordings. It uses natural language processing and generative AI to identify key insights and produce documents for collaboration and alignment. Umbrellabird is designed for product managers at software companies or UX researchers tasked with providing summaries of user/customer interviews.

Raijin.ai is an AI-powered Customer Discovery and Intelligence Hub designed to help teams aggregate and extract key insights from customer conversations. It accelerates product development by prioritizing features based on customer feedback. The platform offers features like AI Thematic Analysis, Report Writing, Segmentation, and Tags to streamline qualitative research and analysis processes. Raijin.ai is ideal for user researchers, product analysts, and teams looking to integrate AI seamlessly into their workflow to create customer-centric products and data-driven marketing strategies.

Olvy is an AI-powered platform that helps businesses manage user feedback efficiently. It offers a unified workspace for surveys, interviews, reviews, support tickets, and sales calls, all automated using state-of-the-art AI technology. Olvy turns customer feedback into actionable insights, empowering decision-making with data-driven insights and enabling companies to stay connected to user needs. It provides features like automated feedback organization, integration with multiple sources, bulk upload of survey responses, sentiment analysis, thematic analysis, and AI-generated reports. Olvy's Auto-Listener agent filters genuine feedback, while its AI capabilities summarize large data sets and identify key user concerns promptly.

Qlik AutoML is an AI tool that offers automated machine learning for analytics teams. It allows users to create machine learning experiments, identify key drivers in data, train models, and make predictions. With a focus on no-code machine learning, Qlik AutoML simplifies the process of generating predictive models and understanding outcomes. The tool enables users to explore predictive data, test what-if scenarios, and leverage AI-powered connectors for seamless integration with other AI and machine learning tools.

Insight7 is a powerful AI-powered tool that helps businesses extract insights from customer and employee interviews. It uses natural language processing and machine learning to analyze large volumes of unstructured data, such as transcripts, audio recordings, and videos. Insight7 can identify key themes, trends, and sentiment, which can then be used to improve products, services, and customer experiences.

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

x-crawl is a flexible Node.js AI-assisted crawler library that offers powerful AI assistance functions to make crawler work more efficient, intelligent, and convenient. It consists of a crawler API and various functions that can work normally even without relying on AI. The AI component is currently based on a large AI model provided by OpenAI, simplifying many tedious operations. The library supports crawling dynamic pages, static pages, interface data, and file data, with features like control page operations, device fingerprinting, asynchronous sync, interval crawling, failed retry handling, rotation proxy, priority queue, crawl information control, and TypeScript support.

Langroid-examples is a repository containing examples of using the Langroid Multi-Agent Programming framework to build LLM applications. It provides a collection of scripts and instructions for setting up the environment, working with local LLMs, using OpenAI LLMs, and running various examples. The repository also includes optional setup instructions for integrating with Qdrant, Redis, Momento, GitHub, and Google Custom Search API. Users can explore different scenarios and functionalities of Langroid through the provided examples and documentation.

Langroid is a Python framework that makes it easy to build LLM-powered applications. It uses a multi-agent paradigm inspired by the Actor Framework, where you set up Agents, equip them with optional components (LLM, vector-store and tools/functions), assign them tasks, and have them collaboratively solve a problem by exchanging messages. Langroid is a fresh take on LLM app-development, where considerable thought has gone into simplifying the developer experience; it does not use Langchain.

HybridAGI is the first Programmable LLM-based Autonomous Agent that lets you program its behavior using a **graph-based prompt programming** approach. This state-of-the-art feature allows the AGI to efficiently use any tool while controlling the long-term behavior of the agent. Become the _first Prompt Programmers in history_ ; be a part of the AI revolution one node at a time! **Disclaimer: We are currently in the process of upgrading the codebase to integrate DSPy**

Simple-OpenAI is a Java library that provides a simple way to interact with the OpenAI API. It offers consistent interfaces for various OpenAI services like Audio, Chat Completion, Image Generation, and more. The library uses CleverClient for HTTP communication, Jackson for JSON parsing, and Lombok to reduce boilerplate code. It supports asynchronous requests and provides methods for synchronous calls as well. Users can easily create objects to communicate with the OpenAI API and perform tasks like text-to-speech, transcription, image generation, and chat completions.

MARS5 is a novel English speech model (TTS) developed by CAMB.AI, featuring a two-stage AR-NAR pipeline with a unique NAR component. The model can generate speech for various scenarios like sports commentary and anime with just 5 seconds of audio and a text snippet. It allows steering prosody using punctuation and capitalization in the transcript. Speaker identity is specified using an audio reference file, enabling 'deep clone' for improved quality. The model can be used via torch.hub or HuggingFace, supporting both shallow and deep cloning for inference. Checkpoints are provided for AR and NAR models, with hardware requirements of 750M+450M params on GPU. Contributions to improve model stability, performance, and reference audio selection are welcome.

The 'unilm' repository is a collection of tools, models, and architectures for Foundation Models and General AI, focusing on tasks such as NLP, MT, Speech, Document AI, and Multimodal AI. It includes various pre-trained models, such as UniLM, InfoXLM, DeltaLM, MiniLM, AdaLM, BEiT, LayoutLM, WavLM, VALL-E, and more, designed for tasks like language understanding, generation, translation, vision, speech, and multimodal processing. The repository also features toolkits like s2s-ft for sequence-to-sequence fine-tuning and Aggressive Decoding for efficient sequence-to-sequence decoding. Additionally, it offers applications like TrOCR for OCR, LayoutReader for reading order detection, and XLM-T for multilingual NMT.

crewAI is a cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. It provides a flexible and structured approach to AI collaboration, enabling users to define agents with specific roles, goals, and tools, and assign them tasks within a customizable process. crewAI supports integration with various LLMs, including OpenAI, and offers features such as autonomous task delegation, flexible task management, and output parsing. It is open-source and welcomes contributions, with a focus on improving the library based on usage data collected through anonymous telemetry.

OpenAGI is a framework designed to make the development of autonomous human-like agents accessible to all. It aims to pave the way towards open agents and eventually AGI for everyone. The initiative strongly believes in the transformative power of AI and offers developers a platform to create autonomous human-like agents. OpenAGI features a flexible agent architecture, streamlined integration and configuration processes, and automated/manual agent configuration generation. It can be used in education for personalized learning experiences, in finance and banking for fraud detection and personalized banking advice, and in healthcare for patient monitoring and disease diagnosis.

The 100 Days in AI repository provides a comprehensive roadmap for individuals to learn Artificial Intelligence over a period of 100 days. It covers topics ranging from basic programming in Python to advanced concepts in AI, including machine learning, deep learning, and specialized AI topics. The repository includes daily tasks, resources, and exercises to ensure a structured learning experience. By following this roadmap, users can gain a solid understanding of AI and be prepared to work on real-world AI projects.

AutoNode is a self-operating computer system designed to automate web interactions and data extraction processes. It leverages advanced technologies like OCR (Optical Character Recognition), YOLO (You Only Look Once) models for object detection, and a custom site-graph to navigate and interact with web pages programmatically. Users can define objectives, create site-graphs, and utilize AutoNode via API to automate tasks on websites. The tool also supports training custom YOLO models for object detection and OCR for text recognition on web pages. AutoNode can be used for tasks such as extracting product details, automating web interactions, and more.

The AI Horde is an enterprise-level ML-Ops crowdsourced distributed inference cluster for AI Models. This middleware can support both Image and Text generation. It is infinitely scalable and supports seamless drop-in/drop-out of compute resources. The Public version allows people without a powerful GPU to use Stable Diffusion or Large Language Models like Pygmalion/Llama by relying on spare/idle resources provided by the community and also allows non-python clients, such as games and apps, to use AI-provided generations.

This Helm chart bootstraps an Airflow deployment on a Kubernetes cluster using the Helm package manager. The version of this chart does not correlate to any other component. Users should not expect feature parity between OSS airflow chart and the Astronomer airflow-chart for identical version numbers. To install this helm chart remotely (using helm 3) kubectl create namespace airflow helm repo add astronomer https://helm.astronomer.io helm install airflow --namespace airflow astronomer/airflow To install this repository from source sh kubectl create namespace airflow helm install --namespace airflow . Prerequisites: Kubernetes 1.12+ Helm 3.6+ PV provisioner support in the underlying infrastructure Installing the Chart: sh helm install --name my-release . The command deploys Airflow on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation. Upgrading the Chart: First, look at the updating documentation to identify any backwards-incompatible changes. To upgrade the chart with the release name `my-release`: sh helm upgrade --name my-release . Uninstalling the Chart: To uninstall/delete the `my-release` deployment: sh helm delete my-release The command removes all the Kubernetes components associated with the chart and deletes the release. Updating DAGs: Bake DAGs in Docker image The recommended way to update your DAGs with this chart is to build a new docker image with the latest code (`docker build -t my-company/airflow:8a0da78 .`), push it to an accessible registry (`docker push my-company/airflow:8a0da78`), then update the Airflow pods with that image: sh helm upgrade my-release . --set images.airflow.repository=my-company/airflow --set images.airflow.tag=8a0da78 Docker Images: The Airflow image that are referenced as the default values in this chart are generated from this repository: https://github.com/astronomer/ap-airflow. Other non-airflow images used in this chart are generated from this repository: https://github.com/astronomer/ap-vendor. Parameters: The complete list of parameters supported by the community chart can be found on the Parameteres Reference page, and can be set under the `airflow` key in this chart. The following tables lists the configurable parameters of the Astronomer chart and their default values. | Parameter | Description | Default | | :----------------------------- | :-------------------------------------------------------------------------------------------------------- | :---------------------------- | | `ingress.enabled` | Enable Kubernetes Ingress support | `false` | | `ingress.acme` | Add acme annotations to Ingress object | `false` | | `ingress.tlsSecretName` | Name of secret that contains a TLS secret | `~` | | `ingress.webserverAnnotations` | Annotations added to Webserver Ingress object | `{}` | | `ingress.flowerAnnotations` | Annotations added to Flower Ingress object | `{}` | | `ingress.baseDomain` | Base domain for VHOSTs | `~` | | `ingress.auth.enabled` | Enable auth with Astronomer Platform | `true` | | `extraObjects` | Extra K8s Objects to deploy (these are passed through `tpl`). More about Extra Objects. | `[]` | | `sccEnabled` | Enable security context constraints required for OpenShift | `false` | | `authSidecar.enabled` | Enable authSidecar | `false` | | `authSidecar.repository` | The image for the auth sidecar proxy | `nginxinc/nginx-unprivileged` | | `authSidecar.tag` | The image tag for the auth sidecar proxy | `stable` | | `authSidecar.pullPolicy` | The K8s pullPolicy for the the auth sidecar proxy image | `IfNotPresent` | | `authSidecar.port` | The port the auth sidecar exposes | `8084` | | `gitSyncRelay.enabled` | Enables git sync relay feature. | `False` | | `gitSyncRelay.repo.url` | Upstream URL to the git repo to clone. | `~` | | `gitSyncRelay.repo.branch` | Branch of the upstream git repo to checkout. | `main` | | `gitSyncRelay.repo.depth` | How many revisions to check out. Leave as default `1` except in dev where history is needed. | `1` | | `gitSyncRelay.repo.wait` | Seconds to wait before pulling from the upstream remote. | `60` | | `gitSyncRelay.repo.subPath` | Path to the dags directory within the git repository. | `~` | Specify each parameter using the `--set key=value[,key=value]` argument to `helm install`. For example, sh helm install --name my-release --set executor=CeleryExecutor --set enablePodLaunching=false . Walkthrough using kind: Install kind, and create a cluster We recommend testing with Kubernetes 1.25+, example: sh kind create cluster --image kindest/node:v1.25.11 Confirm it's up: sh kubectl cluster-info --context kind-kind Add Astronomer's Helm repo sh helm repo add astronomer https://helm.astronomer.io helm repo update Create namespace + install the chart sh kubectl create namespace airflow helm install airflow -n airflow astronomer/airflow It may take a few minutes. Confirm the pods are up: sh kubectl get pods --all-namespaces helm list -n airflow Run `kubectl port-forward svc/airflow-webserver 8080:8080 -n airflow` to port-forward the Airflow UI to http://localhost:8080/ to confirm Airflow is working. Login as _admin_ and password _admin_. Build a Docker image from your DAGs: 1. Start a project using astro-cli, which will generate a Dockerfile, and load your DAGs in. You can test locally before pushing to kind with `astro airflow start`. `sh mkdir my-airflow-project && cd my-airflow-project astro dev init` 2. Then build the image: `sh docker build -t my-dags:0.0.1 .` 3. Load the image into kind: `sh kind load docker-image my-dags:0.0.1` 4. Upgrade Helm deployment: sh helm upgrade airflow -n airflow --set images.airflow.repository=my-dags --set images.airflow.tag=0.0.1 astronomer/airflow Extra Objects: This chart can deploy extra Kubernetes objects (assuming the role used by Helm can manage them). For Astronomer Cloud and Enterprise, the role permissions can be found in the Commander role. yaml extraObjects: - apiVersion: batch/v1beta1 kind: CronJob metadata: name: "{{ .Release.Name }}-somejob" spec: schedule: "*/10 * * * *" concurrencyPolicy: Forbid jobTemplate: spec: template: spec: containers: - name: myjob image: ubuntu command: - echo args: - hello restartPolicy: OnFailure Contributing: Check out our contributing guide! License: Apache 2.0 with Commons Clause

MMStar is an elite vision-indispensable multi-modal benchmark comprising 1,500 challenge samples meticulously selected by humans. It addresses two key issues in current LLM evaluation: the unnecessary use of visual content in many samples and the existence of unintentional data leakage in LLM and LVLM training. MMStar evaluates 6 core capabilities across 18 detailed axes, ensuring a balanced distribution of samples across all dimensions.

This solution accelerator is built on Azure Cognitive Search Service and Azure OpenAI Service to synthesize post-contact center transcripts for intelligent contact center scenarios. It converts raw transcripts into customer call summaries to extract insights around product and service performance. Key features include conversation summarization, key phrase extraction, speech-to-text transcription, sensitive information extraction, sentiment analysis, and opinion mining. The tool enables data professionals to quickly analyze call logs for improvement in contact center operations.

CometLLM is a tool to log and visualize your LLM prompts and chains. Use CometLLM to identify effective prompt strategies, streamline your troubleshooting, and ensure reproducible workflows!

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